Credit and Debt Management and Debt Management – 2008 Survey Research and analysis by the Credit...

Credit and Debt Management – 2008 Survey

1 Research and analysis by the Credit Management Research Centre, University of Leeds Business School

2008

Credit and Debt Management Survey 2008 Credit Management Research Centre, Leeds University Business School



CONTENTS

1. Executive Summary

1.1 Consumer and Household Debt 1.2 Commercial Lending and Insolvency 1.3 Debt Collection Agents and Debt Sale 1.4 Survey of DCA’s 1.5 Large Volume Debt Management 2. An Overview of Consumer and Corporate Lending 2.1. Categories of Lending 2.2. Consumer Lending and Indebtedness 2.3. Consumer Credit and Indebtedness 2.3.1. Subjective Evidence 2.3.2 Statistical Evidence 2.4. A Summary of Lending Trends 2.4.1. Secured Lending 2.5 The Over-Indebtedness Debate 2.5.1 Arrears 2.5.2 Trends in Write-offs by Major Lenders 2.6 Personal Insolvency: bankruptcy and Voluntary Arrangements 2.6.1 Bankruptcy Modelling – Key Drivers 2.7 County Court Actions 2.8 Factors Affecting Indebtedness 2.9 Fraud 3. Commercial Lending and Trade Credit 3.1 Business Growth and Insolvency in the UK 3.2 Forecasting Corporate Insolvencies 3.3. Commercial Lending 3.4 Trade Credit 3.4.1 Credit Terms and Credit Management Practice 3.4.2 Motives for the Supply of and Demand for Trade Credit 3.4.3 Credit Management: The Impact on Corporate Performance 3.4.4 The Use of Trade Credit and Payment Behaviour:

The Demand Side Motivation 3.5 Late Payment and Bad Debt 3.6 Late Payment Trends 3.7 Impact of the Late Payment Legislation 3.8 Use of Third Parties in Credit Management 3.8.1 Factoring and Invoice Discounting 3.8.2 Credit Insurance and Related Services 4. Large Volume Debt Management – Case Studies 4.1 Introduction and Objectives 4.2 Background to the Credit Account Life-cycle 4.2.1 Customer Life-Cycle



4.2.2 Account Life-Cycles 4.3 Elements of ‘Best Practice in Collections’ and Implications 4.3.1 Credit Information and Scoring Technologies 4.3.2 Customer contact and Customer Retention and Collection 4.3.3 Collection department practices

4.3.4 Use of external debt collection agencies for telephone, letter and doorstep contact; litigation

4.3.5 Benchmarking 4.4 Summary 4.5 Short Case Interviews 2007 4.5.1 Collections Department Medium Sized Bank 4.5.2 Commercial Credit Card 4.5.3 Consumer Credit Card 4.5.4 Medium Sized Retail Bank 4.6 Large Volume Collections: Interview Survey 2003 4.6.1 Delinquency Cycles 4.7 Case Studies 2003: large volume collection activities 4.7.1 Case A: Debt Recovery Division of a Major Bank 4.7.2 Case B - Credit Card Provider 4.7.3 Case C: Large Volume Lender Retail Card, Personal Loans 4.7.4 Case D: International Bank Collections and Recovery 4.7.5 Debt Management and Collection in the Utilities Sector 4.7.6 Best Practice in Collections and Recovery: Evidence from US Utilities 4.7.7 Key Performance Indicators Used in Debt Management 4.7.8 Best Practice in Collections and Recovery: The Water Sector 4.7.8.1 Areas of Disadvantage 4.7.9 Credit and Debt Management Practice in the Water Industry 4.7.9.1 General Information 4.7.9.2 Direct billing and other methods 4.7.9.3 Telephone Contact 4.7.9.5 Scoring and Customer Profiling 4.9 Use of Debt Collection Agents 4.9.1 DCA: Case Study 4.10 Debt Sale and Purchase: Trends and Developments 4.10.1 Case Study: Debt Buyer 5. A Survey of Debt Collection Agents and Debt Buyers 5.1 Debt Collection Services 5.2 The Market for Debt Collection Services 5.3 Market Size 5.4 Value and Volumes in the Debt Collection Market 5.5 Quality and Volumes in the Debt Collection Market 5.6 Debt Purchase 5.7 Litigation and Bankruptcy References



CHARTS AND TABLES

Table 2.1 – Categories of Measurable Lending in the UK (Source:

Keynote Ltd)

Chart 2.3.1.1 – Debt Client Characteristics 2006 (source: Citizens Advice

Bureau Survey 2006)

Chart 2.3.1.2 – Consumer Credit Outstanding (source: Bank of England)

Chart 2.3.1.3 – Consumer Spending Growth (source: Bank of England)

Chart 2.3.1.4 – Total Personal Debt July 2007 (source: Bank of England)

Chart 2.3.1.5 – Total Lending to Individuals Per Month (source: Bank of

England)

Chart 2.3.1.6 – Mortgage Equity Withdrawal 1970-2006 £M (source: Bank

of England)

Chart 2.3.1.7 – Mortgage Equity Withdrawal as a % of Disposable Income

(source: ?????

Chart 2.4.1.1 – Approvals for Secured Lending to Individuals

(thousands) (source: Bank of England 2007)

Chart 2.4.1.2 – 12 Month Growth Rate of Secured Lending Approvals to

Individuals (source: Bank of England 2007)

Chart 2.4.1.3 – Monthly Value of Approvals for Secured Lending to


Chart 2.4.1.4 – 12 Month Growth Rate of Value of Approvals for Secured

Lending to Individuals (source: Bank of England 2007)

Chart 2.4.1.5 – Monthly Number of Approvals for Secured Lending to


Chart 2.4.1.6 – 12 Month Growth Rate of Number of Approvals for

Secured Lending to Individuals (source: Bank of England 2007)



Chart 2.4.1.8 – 12 Month Growth Rate of Value of Approvals for Secured


Chart 2.4.1.9 – Monthly Amount of Total Sterling Secured Gross Lending

to Individuals and Housing Associations (in sterling millions) (source:

Bank of England 2007)

Chart 2.4.1.10– Monthly Amount of Sterling Repayments of Secured

Lending by Individuals (in sterling millions) (source: Bank of England

2007)

Chart 2.4.2.1– Monthly Amount of Total Sterling Unsecured Gross

Lending to Individuals (in sterling millions) (source: Bank of England

2007)

Chart 2.4.2.2– Monthly Amounts Outstanding of Total Sterling Net

Unsecured Lending to Individuals (source: Bank of England 2007)

Chart 2.4.2.3– Monthly Amount of UK Resident Banks’ (inc. Central Bank)

Sterling Credit Card Repayments by Individuals (in sterling millions)

(source: Bank of England

Chart 2.4.2.4– Monthly Amount of UK Resident Banks’ (inc. Central Bank)

Sterling Credit Card Repayments by Individuals/Monthly Amounts

Outstanding of Total Sterling Net Credit Card Lending to Individuals

Chart 2.4.2.5 - End Month Weighted Average Interest Rate, Bank &

Building Societies (source: Bank of England 2007)

Chart 2.5.1 – Debt to Income Ratio (source: ONS and Bank of England

2007)

Chart 2.5.2 – Income Gearing (source: ONS and Datastream 2007)

Chart 2.5.3 – Debt to Wealth Ratio (source: ONS and Bank of England

2007)

Chart 2.5.4 – Credit Card Lending (source: ???

Chart 2.5.5 – Other Unsecured Lending (source: ???

Chart 2.5.6 - SecuredLending (source: ???

Chart 2.5.7 – Ratio of Write offs to Credit Card Lending (source: ???

Chart 2.5.8 – Major UK Banks Annual Write Off Rates (source: Bank of

England 2007

Chart 2.5.9 – Personal Bankruptcies and Individual Voluntary

Arrangements (source: DTI 2007)

Chart 2.5.10 – Personal Bankruptcy Ratio (Source ???)

Chart 2.5.11 – Consumer County Court Judgements 2002-2007 (Source:

Registry Trust)

Chart 2.9.1 – Fraud Trends 1997- 2005 (Source: CIFAS 2007)


Chart 3.1.1 – Register Size in Great Britain (1992-2006) (Source:

Companies House)

Chart 3.1.2 – Company Birth Rate (2001-2006) (Source: Companies

House)

Chart 3.1.3 – Company Insolvencies (1975-2006) (Source: Companies

House)

Chart 3.1.4 – The Relationship between Insolvencies and the Write-off

Rates of Banks (Source: Bank of England)

Table 3.2 – Variables used to Forecast Insolvencies (Source: CMRC)

Table 3.3.1 – Bank and Building Society Lending to Industrial and

Commercial Companies 1996-2006 (Source: Bank of England)

Chart 3.3.1 – Contributions to Annual Growth Rate from Non Financial

Corporations (Source: ?????)

Chart 3.3.2 – New Leasing and HP Business Finance by Client Size and

Business Investment

(Source: FALA and ONS)

Chart 3.3.3 – Small Business Borrowing and Deposits at Year End (£

Billions) (Source: Bank of England)

Chart 3.3.4 – Changes in Sources of External Finance for SME’s

(Source: ESRC Centre of Business Research)

Chart 3.3.5 – Aggregate Capital Gearing of UK companies

(Source: ONS and Bank calculations)



Chart 3.3.6 –Capital Gearing/Total Debt/Total Assets (Source:

Creditscorer)

Chart 3.3.7 –Income Gearing/Operating Profit (Source: Creditscorer)

Chart 3.3.8 – The Importance of Trade Debtors to the Balance Sheet

(Source: Creditscorer)

Chart 3.3.9 – DSO and Creditor Days Trends (1982-2004)


Chart 3.3.10 – Net Trade Credit Trends


Table 3.4.2.1 – Motivations for Trade Credit Extension (Source: CMRC)

Chart 3.4.4.1 – The Use of Trade Credit and Payment Behaviour – A

Strategy Map

(Source: CMRC)



Chart 3.6.1 – % of Accounts Paying beyond the Due Date (Source:

CMRC)

Chart 3.6.2 – % of Companies Paying on Time (Source: CMRC)

Chart 3.6.3 – % of Invoices Paid on Time – Sector Analysis (Source:

CMRC)

Chart 3.6.4 – % of Invoices Paid on Time – Sub Sector Analysis for the

Manufacturing Sector (Source: CMRC)

Chart 3.6.5 – Average Debtor Days (Source: CMRC)

Chart 3.6.6 – Payment Beyond the Due Date (Source: CMRC)

Chart 3.6.7 – Debtor Days - Size Analysis

Chart 3.6.8 – Debtor Days - Turnover Analysis

Chart 3.6.9 –Debtor Days – Sector Analysis

Chart 3.6.10 – Debtor Days – Sub Sector Analysis

Chart 3.6.11 –Interest Charged on Overdue Accounts

Chart 3.6.12 – % Firms Affected by Late Payment

Chart 3.6.13–Receivables Beyond 30/90 Days

Chart 3.6.14 – Accounts Beyond 30/90 Days - Sector

Chart 3.6.15 – Accounts Beyond 30/90 Days

Table 3.6.1 – Profile of firms suffering from Bad Debt

Chart 3.6.16– Types of Customer who are Slow Payers

Chart 3.6.17– Assertions about Late Payment

Chart 3.6.18– Possible Policy Measures

Table 3.6.2– % of Companies Pursuing Late Payments through the

Courts

Table 3.6.3– Awareness of the Late Payment Legislation

Chart 3.6.19– Awareness of the Late Payment Legislation

Chart 3.6.20 – Domestic Factoring Trends (Source: FDA)

Chart 3.6.21 – Domestic Invoice Discounting Trends (Source: FDA)

Chart 3.6.22 – Export Factoring and Invoice Discounting (Source: FDA)

Chart 3.6.23 – Firms using Invoice Finance (Source: Bank of England)

Chart 3.6.24 Growth in Demand for Factoring (Source: FDA)

Chart 3.6.25 – Credit Insurance Growth (Source: ICISA)

Chart 3.6.26 – World Market for Credit Insurance (Source: ICISA)

Chart 3.6.27 – Use of Credit Insurance by SME’s (Source: ICISA)

Table 3.6.4 – Reasons for not using Credit Insurance (Source: CMRC)

Table 3.6.5 – Reasons why companies use Credit Insurance (Source:

CMRC)

Table 3.6.28 – Traditional Benefits of Credit Insurance (Source: CMRC)

Chart 4.2.1 – Customer Life-Time Management

Chart 4.2.2 – The Customer Account Life-Cycle

Table 4.2.1 – Account Management Functions (Source: CMRC)

Chart 4.2.3 – Scoring in Account Management

Chart 4.2.4 – Applications to Collections

Chart 4.2.5 – Debt Management and Collection Trends

Chart 4.2.6 – Scoring to Determine Collection Strategies

Chart 4.3.1 – New Debt Management Approaches

Chart 4.3.2 – Motives for Credit Scoring in Consumer Credit

Chart 4.3.3 – Modelling for Collections Strategies

Chart 4.3.4– Behaviour Scoring: Principles

Chart 4.3.5 – Behaviour Scoring

Chart 4.3.6 – Example Behaviour Score Card

Chart 4.3.7 – Behavioural Scoring and the Account Life-cycle

Chart 4.3.2.1 – Champion vs Challenger Strategies in Collection

Chart 4.3.3.1 – Lender Time Horizons

Chart 4.6.1.1 – Delinquency Cycles

Chart 4.7.3.1 – Computer Systems Sued from Application to Collection

Chart 4.7.5.1 – Entire Billing Process (Source SAP Business Intelligence)

Chart 4.7.5.2 – Factors Impacting on Debt in the Utilities Sector

Chart 4.7.6.1 – Revenue to Recovery – Customer Impact

Chart 4.7.8.1 – A Guide to Good Practice

Chart 4.7.8.2 – Number of Customers using Prepayment Meters

Chart 4.7.9.1 – % of Directly Billed Customers

Chart 4.7.9.2 – % of Directly Billed Customers – by size

Chart 4.8.5.1 – A Large Volumes Collections Operation

Chart 4.8.5.2 – A Credit Management Model (1)


Chart 4.8.5.3 – Recovery Paths and Steps

Chart 4.9.1 – Collections: An Integrated Approach

Chart 4.9.2 – Turnover Trends in UK Debt Collection market

Chart 4.9.3 – Net Worth Trends in UK Debt Collection market

Chart 4.9.1.1 – Example of DCA Collections Process

Chart 4.9.1.2 – DCA Service Optimisation

Table 5.1 Debt Collection And Other Services Offered By Respondents

Chart 5.1 Client Base Trends For The Debt Collection Market

Chart 5.2 Number Of Debts Placed In Market

Chart 5.3 Market Size For Consumer Debt

Chart 5.4 Market Competitiveness For Consumer Debt

Table 5.2 Number Of Debts Worked Per Month – Whole Sample

Table 5.3 Value Of Debts Worked Per Month – Whole Sample

Table 5.4 Number Of Clients And Debts Worked Per Month – Agency

Size Breakdown

Table 5.5 Total Value And Total Number Of Debts Placed – Agency Size

Breakdown

Table 5.6 Sectors For Debt Collection Activities

Table 5.7 Growing And Declining Sectors For Consumer Debt

Table 5.7 Value Of Debts From Largest Client

Chart 5.5 Quality Of Consumer Debt

Chart 5.6 Age Of Consumer Debt

Chart 5.7 Number Of Clients Worked For

Chart 5.8 Debt Purchase Market Growth

Chart 5.9 Growth In Prices Paid In Debt Purchase - 2007

Table 5.8 % Of Purchased Debt Sent For Collection

Table 5.9 % Of Purchased Debt Sent For Collection

Table 5.10 % Of Purchased Debt In Litigation

Table 5.11 % Of Total Debt Referred To Court

Chart 5.10 % Of Agents With Accounts Operating Under An Iva

Table 5.12 Number Of Iva’s Agreed To In Last 12 Months

Table 5.13 Number Of Iva’s Agreed To In Last 3 Years


Table 5.15 Defaults Which Have Been Rescheduled In Last Year


Table 5.16 Bankruptices In The Last Two Years



1. Executive Summary 1.1 Consumer Lending and Household

Debt

The growth in household debt, both in absolute terms and


relative to household income, continues to cause some

concern. As the economic climate changes servicing debt

may become more problematic for a larger proportion of

the UK household sector particularly as mortgage

repayments rise and the opportunities for refinancing and

restructuring current debt decline with the tightening of

lender credit policies. Increases in financial distress and

insolvency in the corporate sector could threaten jobs and

household income in an already fragile economy.

Increases in arrears levels, bad debts and insolvencies

have peaked historically during and/or at the end of

recession due to losses of income. What is particularly

striking about the recent growth in bankruptcy and other

indicators of financial stress is that the trend increase

occurs against a background of generally good macro-

economic and monetary conditions, GDP growth, low

interest rates, high levels of employment and strong asset

prices. The 90’s peak occurred against a backdrop of

economic decline and nominal interest rates in the region

of 13-14% .

The rise in household debt in Britain gained headlines in

2005 when, for the first time, it rose to over £1trillion. By

the first quarter of 2007 the level of outstanding debts was

around £1.4 trillion. This total figure includes secured

lending, the majority of which is first mortgages and

additional ‘equity release’. This amounts to around 80% of

the total consumer lending. Unsecured lending, ‘consumer

credit’, however, has grown rapidly over the past decade

directly related to the growth in the number and type of

credit card products available to consumers. Increased

competition in financial services has fuelled the increase in

available credit products and the degree of product

differentiation. Households owe sums equivalent to 160%

of disposable income.

There are increasing signs that many households are

struggling to service their debts judging by the growth in

the use of private sector and voluntary sector debt

management services. The record levels of personal

bankruptcies as well as the steady rise in the indebtedness

of households, the dramatic increase in the number of fraud

cases, and excessive bad debt losses have prompted the

industry as well as the government to once again examine

the fundamentals of the consumer lending business.

Gauging the extent of the ‘household debt problem’

requires balancing the evidence provided by objective data

from national statistics and the Bank of England with the

vast amount of quasi-subjective information provided by

debt advice groups, lobbyists and surveys of the opinions

of debtors and lenders.

There has been much, often alarming, press and media

coverage that suggests something of a crises in household

finances. These headlines are often fuelled by surveys of

individuals that are in ‘financial difficulty’ and the

apparent increase in debt related problems being reported

to counsellors, debt advice groups, the Citizens Advice

Bureau and varies consumer lobbies.

The increased availability of credit products and the

competition for customers has facilitated a considerable

market for the ‘restructuring of debts’ i.e. moving debts to

lower interest rates (balance transfers) or more typically

extending the time period of the debt with lower monthly



repayments but, ultimately, at a significantly higher rate

(consolidation loans).

There is considerable evidence of households ‘juggling’

finances via balance transfer, the use of loan consolidation

products, making payments on instalments of secured

credit agreements with unsecured credit (e.g. mortgage

payments with credit card cheques). The Credit Reference

Agency, Experian reported that 8.2 million individuals are

in serious debt; 2.1 million are struggling with repayments;

2.5 million are concerned about their ability to manage

debt and 2 million do not know the extent of their debts.

A notable feature of borrowing in recent periods, since

around 1998, is the extent of mortgage equity withdrawal

as a source of borrowings. This primarily concerns

releasing funds tied up in property for expenditure outside

of the housing market (i.e. not used for house purchase of

home improvements). The considerable growth in property

prices since 2000 has created significant amounts of

‘equity’ relative to initial mortgage. Clearly, households

have been able to finance consumption (and unsecured

debt re-payments) on the back of rising house prices.

The buy-to-let and sub-prime (self-certified) mortgage

market appears to be particularly vulnerable in the UK as

well as the US. The quality of lending in these areas is

suspect. The terms ‘Liar Loans’ and ‘ninanj’ (No Income

No Assets No Job’) are phrases used to describe such

lending in the US press but the quality of sub-prime

mortgage portfolios in the UK is equally a risk to the

housing market

Reported statistics on debt servicing vary considerably and

are, of course, sensitive to the sample selected. Although

the ‘average household’ is spending around 12% of its

disposable income on interest payments if we take only the

‘credit active’ population then, in 2007, households are

spending around 30% of their income servicing debt, up

from around 20% 10 years ago.

The Council for Mortgage Lenders report that the number

of mortgages in short-term arrears rose to 125,100 in June

2007 which was slightly down on the previous year. The

Bank of England’s Financial Stability Report (2007,

October) concludes that arrears will be concentrated in a

small proportion of households with low income/high debt

and that “the number of arrears spanning the majority of

the income and debt distribution is small” but with changes

in interest rates and growth in indebtedness “there is a

growing tail of vulnerable households”

The ratio of write offs-to-amounts outstanding for credit

cards is also increasing steadily with a remarkable peak in

the first quarter of 2002. The secured lending write-offs

show a considerable increase in 2005 and 2006 with a peak

similar to the end of 1999. They have started to decline in

2007.

The levels of personal insolvency as gauged by the number

of bankruptcies and individual voluntary arrangements

show a quite spectacular increase since 2000. The

beginning of this upward trend pre-dates the changes in

bankruptcy law introduced in April 2004 although there is

a clear acceleration in the levels of declared insolvencies

post-2004. The Act appears to have encouraged individuals

on the path to bankruptcy to declare early.

The number of CCj’s against consumers has grown rapidly

since 2004 and reached a ten year high by the end of 2006

with 843,853 judgment orders. The growth has continued

in 2007 with almost 250,000 judgements in Q1 and

therefore the total could reach 1 million judgements by the



end of the year compared to just over half a million in

2004.

Registry Trust estimates that around 70% of judgements

are ‘credit related’ the remaining 30% being for unpaid tax,

utility bills and motor tax. Interviews with major lenders

found that county court action in order to gain a ‘charge on

the assets’ of a debtor were becoming common practice.

The Credit Industry Fraud Avoidance System (CIFAS)

report an escalation in fraudulent behaviour in the use of

financial products. Recent data released by CIFAS

(October 2007) suggests that fraud trends continue

upwards. Application fraud increased by 23% from 2006-7

with 57,321 detected cases reported to CIFAS and identity

fraud, although slightly down had 57,302 reported cases.

Recent international banking regulations (Basle II

agreement) have drawn much attention to the re-evaluation

of consumer credit risk (default probabilities) and portfolio

risk management. The Basel II rules have given an

impetus to banks to move debt more quickly from their

books to external debt collection agents and debt buyers.

1.2 Commercial Lending and Insolvency

There has been a trend increase in the number of active

companies registered with Companies House. The stock of

active businesses approached 2.3 million in 2006.

According to Companies House the number of new

incorporations has been growing rapidly year on year e.g

43% 2003-6. In total, unincorporated businesses and

SME’s account for a significant proportion of the business

stock. This is estimated to have grown by more than 1.4

million since 1980. The stock of small businesses is

estimated at 3.8 million. SME’s account for 52% of

aggregate business turnover and 56% of private sector

employment according to the SBS.

The number of company insolvencies (compulsory and

creditors’ voluntary liquidations) in the England and Wales

was 3,194 in the last quarter of 2006, nearly half of the

figure that was observed in the third quarter of 1992.

Although the trend fluctuated around 3,500 insolvencies

per quarter between 1995 and 2007, the figures have been

much lower than the levels of the early 1990s’ recession.

The seasonally adjusted figures provided by the Insolvency

Service show 3,032 liquidations in the second quarter of

2007, representing a 4.2% decrease on one year ago.

A forecasting model of aggregate corporate insolvencies

shows that in the long term insolvency rate increases when

income gearing or real CCJ values increase, and when the

employment rate or real money stock decrease. The

Growth in Real Short Term Loans and Business

Confidence are the short-run dynamics of the insolvency

rate. That is, whereas short term increases in the growth in

real short term loans are likely to create short term

increases in the insolvency rate, short term increases in

business confidence are likely to create short term

decreases in the insolvency rate.

The relatively high levels of indebtedness in the corporate

sector coupled with recent interest rate increases and a

decline in business confidence suggest that corporate

insolvencies are set to increase by over 20% in the next 2

years. More recent data derived from an analysis of UK

Company accounts suggests that the ratio of total debts to

total assets has risen quite sharply since 2004.

When we analyse ratios reflecting the ability of firms to

cover their interest repayments on debt we observe a

similar rise since 2004. This suggests that there are a large

number of companies that are not generating sufficient

profit to cover their interest payments. The considerable

growth in private equity-backed leveraged buyouts has



increased the role of debt in capital structures. It is

estimated that value of investments LBO’s in 2007 was

around £22 bn. Of course, financial distress and insolvency

in the corporate sector threatens jobs and household

income in an already fragile economy.

The late payment of commercial debt as a phenomenon is

enduring. The CMRC Quarterly Review monitors payment

behavior across a sample of 2000 enterprises. Accounts

which pay at or near the due date are currently reported at

54% by sales value. This leaves 46% of all sales accounts

being reported as overdue by our panel of respondents. In

terms of the number of customer accounts, the proportion

of customers paying at or near the due date is slightly

lower. 46% of our survey panel state that customers at an

account level pay on time. This equates to 54% of all

customer accounts currently being paid late. Recent survey

statistics show a deterioration in B2B payment behavior.

This trend is likely to continue since smaller firms rely

increasingly on trade credit when bank credit is restricted.

The Late payment of Commercial Debts (Interest) Act has

had an impact of the extent of outplacement to the DCA

sector. The fact that DCA’s can impose an interest charge

and recover some collection costs has made out-placing

debt more cost effective for the commercial sector and

particularly SME’s. 1.3 Debt Collection Agents and Debt

Sale

A number of trends and industry dynamics have impacted

on the out-placed debt collection and debt purchase sector.

These include: the surge in consumer debt and increase in

the volumes of delinquent debt that have to be processed;

the increased emphasis on cost effectiveness and

performance benchmarking; the continued re-engineering

of centralised in-house collection and recovery functions

and the development of technology and information

systems devoted to account management; the speed of

response of the major lenders in dealing with delinquent

accounts and a shortening of the time period to write-off.

Basel II rules have encouraged the lenders to shift debts off

of their books more quickly and to opt for debt sale rather

than commission-based collection since the former

mechanism transfers ownership of the debt.

The Credit Services Association reported that their member

organisations handle around £15 billion of debt on a

commission basis which consisted of over 20 million

individual cases. This represents a rise of £10 billion since

2000. The CSA membership bought around £6 billion of

debt in 2007 making of total of over £21 billion being

passed to the DCA sector. The CSA estimate that their

market will be worth over £24 billion in 2008.

A source of potential revenue growth for the DC industry

is as a provider of a wider range of out-sourced business

services across the credit life-cycle. Outsourcing

receivables management has increased, particularly for

commercial debt. Government and the public sector are

beginning to utilise the services of DCA’s. The growth in

the internet B2C and B2B has translated into more

collection activity on a global scale.

There has been and continues to be a general trend

amongst the large volume collectors to streamline and

rationalise their use of 'external' collection agents alongside

their 'in-house' collection agents. Debt Collection Agents

have turned to buying debt as an alternative to collection

on commission in 2004 there were over 60 debt buyers

although the DBSG suggests that currently there are

around 40 regular buyers in the market. The growth in the

market has been facilitated by the supply-side.



In the UK it is difficult to estimate the total size of the debt

sale market since the market continues to evolve quite

rapidly. The market size in 2005/6 was around £6bn face

value selling at an average price of around 8p in the pound.

By 2006/7 this had increased to £7bn and commentators

are expecting the market to peak at around £10bn. Debt

sale is still dominated by ‘distressed debt’ portfolios i.e.

debt that the financial sector would normally write-off

and/or is severely delinquent is sold to the highest bidder

for collection/recovery. It is clear that lenders have

developed an interest in selling younger debt as a means of

improving cash-flow and because of the costs of servicing

the debt collection sector when debt is placed on a

commission basis.

The major lenders and the majority of financial services are

now selling debt and developing specialist departments to

deal with debt sale and respond faster to debt sale

opportunities. The bulk of sales are distressed debt which

can attract only 2-5% of face value but there is evidence of

sellers selling debt earlier, as in the US, typically 90-180

days past due. The changes in accounting rules, Basel II

and resultant changes in internal default definitions and

capital requirements have had an impact on the propensity

of lenders to sell debt. A further development is the sale of

debt that has already been managed to achieve an

‘arrangement to pay’ via a debt management company.

This type of debt can attract 30-40 pence in the pound. The

development of a reseller market is expected to create

further growth in the market.

The main sources of debt sale are credit cards, loan and

overdrafts, retail credit, motor finance and increasingly

mortgage arrears. Further growth in the Debt Purchase

market is likely to come from the sale of non-delinquent

receivables, reselling and from commercial debt.

A problem that is probably hampering the growth of the

debt sale market is that of ‘pricing’. Interviews with major

lenders suggested that there is some lack of ‘trust’ in the

market as a result of extant price variations. If debt is to be

sold at earlier stages and /or segmented by ‘quality’ then

there has to be a mechanism for pricing the individual

debts and the debt portfolio. The development of a ‘broker’

market for debt sale and purchase has provided some uplift

in prices. 1.4 Survey of DCAs In terms of Debt Collection services offered by agencies in

2007 significant differences can be seen since 2003 in

Repossessions (up 25%) and Tracing (down 15%), The

offering of Process Services and Investigations/Status

Reports has declined between the two time periods. The

largest difference between services offered in 2003 and

2007 is in Debt Purchase which is up by 27% among the

sample. 46% of all agencies offer this service in the

marketplace.

The statistics suggest a healthy growth in the market for

debt collection with 75% of agencies indicate that market

size is increasing in 2007. This compares to just 45% in

2003. 99% of agencies believe market competitiveness to

be increasing.

The number of debts worked by agencies each month

across the entire sample has increased dramatically from

between 1,200 in 2003 to 19,000 in 2007. Among the

larger agencies this increase is most significant with

agencies with over 100 employess reporting a rise from

1000 debts per month to 40,000 debts per month. Overall

in the sample, the average value of a debt placed across the



entire sample has increased from less than £1000 in 2003

to £2400 in 2007.

There appears to be growth in a number of sectors. The

sectors that are generating a faster growth for the out-

placed debt industry are the fixed line telephone sector and

broadband providers. Collections within the retail sector

show the second largest growth among respondents with

85% of collection agents indicating this to be a growing

market. The credit card industry has continued to grow

with 72% of respondents indicating this to be a growth

market.

In 2003 43% of respondents thought that the quality of out-

placed debt was generally worsening. This figure in 2007

is 51% in the sample. 18% of respondents indicated that

the quality of consumer debt was improving.

Over 60% of collection agents generate their business from

under 50 clients and generally collection agents are dealing

with fewer clients than in 2003.

The largest buyer of debt purchased a face value of £458

million compared to just £28 million in 2003. Of the total

debt purchased in 2007 an average of £30 million was

collected during the last year.

In the sample prices paid for debts varied between 5p to

18p in the pound. The average price paid in the pound is 8p

in 2007.

The collection agents were asked if any of their collectable

debts were operating under an Individual Voluntary

Arrangement. 78% of the agencies responding to the

survey had accounts which were linked with an IVA.

The average length of time for an IVA is among the sample

is 4.75 years. Agents also indicated that they expect to

receive 38p in the pound under an IVA and would accept a

minimum of 32p.

In terms of default rates collection agents were asked to

state the the percentage of IVAs which had defaulted over

the last 3 years. The default rate has more than tripled

during the last three years and now stand at 13%.

1.5 Large Volume Debt Management

Organisations faced with large volume debt management

operations are setting up sophisticated customer focused

operations aimed at 'reforming' debtors, if possible, so that

the relationship with them can continue and generate future

profits. This has been partly a response to increased

competition amongst lenders, the emergence of

'consolidation companies' and recognition that changing

life-styles and patterns of work have precipitated periods of

'over-commitment' by debtors which need be managed

longer-term.

The introduction of enterprise wide data sharing has arisen

because of the emphasis being placed on having a

'customer-level' and/or ‘customer-life cycle’ view of each

customer and detailed management information systems.

The expansion of data-sharing closed user groups in the

UK and the development of ‘indebtedness indices’ means

that lenders have access to better information on other

lenders experience of a debtor, and can include this in their

decision making process. The differences in information

costs of in-house and out-placed debt collection are thus

reduced.

Collection cycles have become much shorter in financial

services but opened opportunities for debt buyers. Basel II

rules have resulted in reclassification of debtor portfolios

in financial services with the development of new default



probability models. Internally lenders have moved to a

‘time-based’ rather than ‘event-based’ view of the debtor

and emphasise re-aging or rescheduling debt away from

collections and back into account management where

possible and transferring ownership of delinquent debt.

The centralisation of collections activity in organizations

has produced an environment in which more sophisticated

decision support systems including statistical and

propensity models, such as behavioural/collection scores,

can be used to formulate the most effective collection

strategies by encapsulating the company's previous

experience of what works for customer segments and

creating variability in collection sequences. A range of

propensity models are employed to score the propensity to

‘self-cure’ (i.e. the customer will pay without being

chased) through to the likelihood of successful litigation.

Champion challenger methodologies coupled with activity-

based costing facilitates the evaluation of collections

effectiveness.

Sophisticated credit management in-house will inevitably

reduce the 'quality' or 'collectibility' of debt that is out-

placed. Many debts passed to debt collectors will already

have been through telephone and letter based collections

procedures, and may even effectively have already been to

one debt collector, if the company has a debt collection

subsidiary. In future it may be that such firms will only

want to make use of a sub-set of the debt collectors service

which they cannot provide for themselves, for example

outsourced services through to door-step collection.

A trend towards using debt sale as an alternative to

commission-based collection and using fewer agents with

closer contact and integrated information systems suggests

that there will continue to be rationalization with

fewer/larger and more sophisticated collection agents/debt

buyers in the future. A increasing role for debt brokers is

expected to increase the scale of the broking market.



2. An Overview of Consumer and Corporate Lending

In this section, we analyse the main trends in consumer

lending in the UK by examining aggregate time series

statistics. First, we provide a categorisation of the types of

lending activities by the major financial institutions and the

corporate sector.

2.1. Categories of Lending

The following table (2.1) adapted from Key Note Ltd

attempts to list all the categories of lending in the economy

by the source (lender) and ultimate borrower (debtor).

The banks, building societies, finance houses, retailers,

local authorities and insurance companies make various

forms of lending to both commercial and personal

borrowers.

Commercial organisations extend trade credit to their

commercial customers and may make sales on deferred

payment basis or credit accounts to individual households

(e.g. Utilities, Cable TV). These debts are the potential

source of business for the 'out-placed' debt collection

industry.

Lender Class of Lending Debtor(s) Banks & Building Societies Commercial Other financial institutions Commercial Industrial & Commercial Organisations Personal Secured on Dwellings Personal Consumer Credit, including Credit cards Personal Unincorporated and non- Profit-making bodies Finance Houses Personal Secured and unsecured revolving credit Commercial Motor finance Personal Motor finance Retailers and finance houses Personal Retail instalment lending Personal Store and credit cards Personal Mail order credit Local Authorities Personal Various Insurance companies and others Commercial Various Industrial and Commercial Commercial Trade Credit – on invoice Businesses Business to Business Personal Sales on deferred payment (utilities, cable & satellite TV) Source : Adapted from Key Note Ltd

Table 2.1 – Categories of Measurable Lending in the UK (Source: Keynote Ltd)



2.2. An Overview of Consumer Lending and Indebtedness: Trends


relative to household income, continues to cause some

concern. Much of the growth in consumer debt has

occurred within a confident economy with economic

growth, high levels of employment, growing asset prices,

easy access to credit and low interest rates and inflation.

Despite obvious signs of some financial stress within the

household sector most households have managed to service

their debts. The economic climate appears to be changing:

financial markets have highlighted the potential fragility of

some lending portfolios that appear to be riskier than was

anticipated; lenders have tightened credit policies and

borrowers are becoming more cautious; interest rate rises

are impacting on both the household and corporate sector;

confidence in the housing market continues to falter; oil

prices are rising. Servicing debt may become more

problematic for a larger proportion of the UK household

sector particularly as mortgage repayments rise and the

opportunities for refinancing and restructuring current debt

decline with the tightening of lender credit policies.

‘Trading out of trouble’ and’ buying time’ are not going to

be options. Any uncertainties about future income and

property values exacerbates the problem.

It is estimated that consumer credit has been rising by over

to £1 billion per month with total outstanding debt in the

region of £140 billion in 20071

. Households owe sums

equivalent to 160% of income2

. Since 2000, consumer

credit and debt has been the subject of several high profile

government investigations and regulatory initiatives. The

accumulation of household debt, defaults and arrears has

made headlines in the UK and other OECD economies. In

the UK, the “Task Force on Over-indebtedness” has

produced reports that raise many issues relating to lending

practices, risk management, debt management and social

policy. Initiatives and issues relating to Sub-prime lending,

‘Affordable Lending’, The Survey of Low Income Families

and ‘Credit Constraints’ have attracted some prominence

in government. The Competition Commission’s

investigation into the lack of competition in the ‘Home

Credit’ market highlighted asymmetries in available

consumer-level information and the pricing of sub-prime

products. The Data Protection Act raised many issues and

problems for consumer lenders. Recent international

banking regulations (Basle II agreement) have drawn much

attention to the re-evaluation of consumer credit risk

(default probabilities) and portfolio risk management. The

Basel II rules have given an impetus to banks to move debt

more quickly from their books to external debt collection

agents and particularly debt buyers.

At the consumer level, there are increasing signs that many

households are struggling to service their debts judging by

the growth in the use of private sector and voluntary sector

debt management services. The record levels of personal

bankruptcies, as well as the steady rise in the indebtedness

of households, the dramatic increase in the number of fraud

cases, and excessive bad debt losses have prompted the

industry, as well as the government, to once again examine

the fundamentals of the consumer lending business.

Gauging the extent of the ‘household debt problem’

requires balancing the evidence provided by objective data

from national statistics and the Bank of England with the

vast amount of quasi-subjective information provided by

debt advice groups, lobbyists and surveys of the opinions

of debtors and lenders. In the next section we examine the

statistics.



2.3. Consumer Credit and Indebtedness

The rise in household debt in Britain gained headlines in

2005 when, for the first time, it rose to over £1trillion. By

the first quarter of 2007, the level of outstanding debts was

around £1.4 trillion.3

This total figure includes secured

lending, the majority of which is first mortgages and

additional ‘equity release’. This amounts to around 80% of

the total consumer lending4

. Unsecured lending, or

‘consumer credit’, however, has grown rapidly over the

past decade, directly related to the growth in the number

and type of credit card products available to consumers.

Increased competition in financial services has fuelled the

increase in available credit products and the degree of

product differentiation. Lenders are concerned to cover all

segments of the personal credit market from ‘platinum’ to

‘sub-prime’ with offerings tailored to attract all types of

borrowers and interest rates (APR’s) priced to reflect the

differing risks in each segment. The scramble for market

share has led to a considerable increase in ‘balance

transfer’ activity where consumers are offered low or zero

interest rates for a period of up to 12 months if they

transfer the outstanding balance from one card to a

competitor. Moreover, the increased availability of credit

products and the competition for customers has facilitated

a sizeable market for the ‘restructuring of debts’, i.e.

moving debts to lower interest rates (balance transfers) or

more typically, extending the time period of the debt with

lower monthly repayments but, ultimately, at a

significantly higher rate (consolidation loans).

2.3.1. Survey and Subjective Evidence

There has been much, often alarming, press and media

coverage that suggest something of a crises in household

finances.

These headlines are often fuelled by surveys of individuals

that are in ‘financial difficulty’ and the apparent increase in

debt related problems being reported to counsellors, debt

advice groups, the Citizens Advice Bureau and various

consumer lobbies.

In early 2005, lenders saw a surge in payment arrears,

particularly, but not exclusively, on unsecured lending

products. The Financial Services Authority, in its Financial

Risk Outlook5

, reported that average outstanding balances

on unsecured debt had increased quite substantially for a

large proportion of households. They suggested that around

53% of households had average unsecured debts of £7,065.

The average balance on secured debts was reported as

£67,662 for around 40% of households. There were, at the

time, reported cases where individuals had over £100,000

of outstanding credit card debts set against annual income

levels of around £20,000 and examples of relatively low

income individuals who had large unsecured debts spread

across as many as 20 different credit card lines6

.

A survey by the National Consumer Council7

, in 2007,

concluded that the majority of households are managing to

service their debt commitments. They suggested that 57%

of households have no problems in meeting financial

commitments, that 31% ‘struggle’ from time to time, that

12% have difficulty managing their commitments and that

a subset of 1.6% of households are in serious difficulties.

Converting these figures into numbers of

households/individuals, 3 million are struggling to keep

payments up to date; 1.5 million are falling behind with

payments; and 0.5 million are in serious financial

difficulty, i.e. serious arrears. The trends were of concern.

The NCC suggested that mortgage arrears had increased

4%; repossessions had increased 32%; credit cards arrears

had increased 8.5% from an already high level; and contact



with advice agencies and debt management plans had

increased by 43% and 48% respectively. A survey in 2006

by the Citizen’s Advice Bureau, “In Too Deep” analysed

567 cases of debtors seeking advice. They suggest that

“debt is a continuing and often debilitating problem for an

increasing number of people, with its effects often felt

most strongly amongst the most vulnerable members of

society”. The CAB report an average increase in household

debt of 30% between 2003 and 2006 with the average

outstanding of over £13000, twice the figure reported by

the FSA. Debts were, on average, 17.5 times the average

monthly income. The majority of individuals in the survey

were young (25-44) and single.

The average household debt reported by Creditaction8

in

November 2007 was £8,681, which rises to £20,189 if only

households with some unsecured debt are included in the

denominator. The average outstanding mortgage was

reported as £98,571.

A recent report suggests the number of house repossessions

have increased 50% in the last year to around 45,0009

. As

borrowers reach the end of fixed interest deals taken out

when interest rates were low, the number of repossessions

could well increase further. New mortgage lending has

fallen rapidly along with activity in the housing market.

Most of the major lenders have reported increases in bad

debts in the period 2005-7. Calls to the National Debt line

have more than doubled since 2005 and stand at more that

300,000 per year. The CAB10

reported that 1.7 million

people sought debt counselling last year; 40% of whom

had credit card and unsecured debt problems. They

reported a 30% rise in cases of individuals struggling to

pay energy bills. There is considerable evidence of

households ‘juggling’ finances via balance transfer, the use

of loan consolidation products, making payments on

instalments of secured credit agreements with unsecured

credit (e.g. mortgage payments with credit card cheques).

Chart 2.3.1.1 – Debt Client Characteristics 2006

(source: Citizens Advice Bureau Survey 2006)



Attractive refinancing deals are currently harder to find as

lenders tighten credit policy and interest rates rise. The

Credit Reference Agency, Experian11

last month reported

that 8.2 million individuals are in serious debt; 2.1 million

are struggling with repayments; 2.5 million are concerned

about their ability to manage debt; and 2 million do not

know the extent of their debts.

2.3.2 Statistical Evidence

In the UK, the most recent statistics suggest that the value

of consumer credit outstanding on mortgage loans exceeds

£1150bn and around £215bn is outstanding on other forms

of consumer credit (Bank of England, 2007). The trend in

consumer credit (excluding mortgages) has shown a

substantial growth, particularly since 2000. Consumer

credit is defined as borrowing by consumers, i.e. the

household sector excluding sole proprietorships,

partnerships, and non-profit making bodies, to finance

current expenditure on goods and services. Figures from

the Central Statistical Office (on the value of consumer

credit outstanding) suggest over £215 billion outstanding

on forms of consumer credit. These figures exclude credit

where the balance has to be paid off at the end of each

period such as utility bills, but will include balances on

credit cards which are paid off on a monthly basis and

therefore do not, in the strictest sense, represent credit. The

services provided by the utilities, which are often on a

deferred payment basis, represent a sizeable proportion of

total consumer debt.

Chart 2.3.1.2 below shows the strong trend increase year

on year in consumer credit from 1994 to 2007. As the chart

illustrates, the 1980s saw a consumer credit boom; between

1979 and 1989 the volume of consumer credit outstanding

(excluding mortgages) more than doubled, and there was a

similar movement in the amount outstanding on mortgage

loans. Wilson and Summers (1998) suggested various

factors contributed to this, including:

• High inflation in the late 1970s and early 1980s. This

made buying on credit more attractive when compared

with saving for consumer goods, and also had a

negative effect on attitudes to saving which continued

even when inflation dropped;

• The de-regulation of financial markets and controls on

hire purchase;

• The 1986 Financial Services Act in the UK and

similar trends across Europe, which allowed building

societies to compete with banks, and changes in the

regulation of building societies allowing them to get a

higher percentage of funds from sources other than

their members;

• An increase in divorce rates across Europe which has

left more families needing credit to cope financially;

• Government policies encouraging home ownership.

Since 1994, however, the total amount of consumer credit

outstanding (excluding mortgages) has almost quadrupled.

Much of this increase has arisen in the credit and retail card

market. Competition has been fierce in the UK plastic card

market. It has been reported that there are over 1300

different credit cards in the UK (standard, gold, charity,

affinity, co-branded etc) with around 33 card issuers

including the major banks. Estimates suggest that there are

over 75 million credit and debit cards in circulation with

amounts outstanding around £67.25 billion12

. The credit

card market experienced unprecedented levels of

competition largely as a result of new entry by US issuers

that dramatically increased the choice of card rates and

benefits. The trend growth in consumer credit appears to

have slowed in 2007-7.



The growth in credit outstanding is clearly closely linked to

the level and growth in consumer spending over the time

period. The chart to the right demonstrates the continued

and strong growth in consumer spending in every period

since 1994 and a continued but slowing growth in 2007.

In the context of total consumer borrowing, credit card

debt forms only 4%, with mortgages and personal loans

having the major share.

The chart to the right shows the relative shares of lending

broken down as secured (mortgages) and unsecured (cards and

unsecured loans) over the recent period. Thus, the growth in

debt is associated predominantly with asset accumulation and

house price growth rather than consumer spending.

0

50

100

150

200

250

Consumer Credit Outstanding(excluding mortgages)

‐4%

‐2%

0%

2%

4%

6%

8%

10%

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Consum

er Sp

endin

g y‐on‐y

Consumer Spending Growth

Mortages

Credit Cards

Loans etc84%

12%4%

Total Personal Debt – £1.355 bn, July 2007

0

5 000

10 000

15 000

20 000

25 000

30 000

total

secured

consumer

Total Lending to Individuals Per MonthAugust 2005 –August 2007

Totals Outstanding £ 1364742 (100%)secured £ 1150247 ( 84%)consumer £ 214495 ( 16%)

Chart 2.3.1.2 – Consumer Credit Outstanding

(source: Bank of England)

Chart 2.3.1.3 – Consumer Spending Growth


Chart 2.3.1.4 – Total Personal Debt July 2007

(source: Calculated from Bank of England statistics)

Chart 2.3.1.5 – Total Lending to Individuals Per Month




A notable feature borrowing in recent periods, since around

1998, is the extent of mortgage equity withdrawal as a

source of borrowings. This primarily concerns releasing

funds tied up in property for expenditure outside of the

housing market (i.e. not used for house purchase of home

improvements). The considerable growth in property prices

since 2000 has created significant amounts of ‘equity’

relative to initial mortgage. The figures in Chart 2.3.1.6

below examine the total additional amounts borrowed

against properties and the percentage of disposable income

withdrawn against existing equity and reveals a marked

upward trend throughout the period and, after a sharp

decline in 2005, further growth in 2006/7. Clearly,

households have been able to finance consumption (and

unsecured debt re-payments) on the back of rising house

prices during this period.

As a percentage of disposable income Chart 2.3.1.7 shows

a sharp upward trend since 1998, reaching almost 9% by

the end of 2003. The previous high of 7.7% in 1988

coincides with the beginning of the last major UK

recession. The sharp decline in 2005 coincides with a

tightening of credit policy amongst the major lenders as a

result of record high levels of arrears on credit products at

the beginning of 2005. However, the growth in equity

release in relation to income continued to grow in 2006,

reaching 7% at the end of 2006, but has fallen again in

2007 to around 4.5%. This, however, is more likely to be a

supply constraint, as a result of the tightening of lending

terms, rather than a fall in demand.

‐5,000

0

5,000

10,000

15,000

20,000

1970 1988 1998 2003 2006

Mortgage Equity Withdrawal 1970‐2006 £m

‐2.0

0.0

2.0

4.0

6.0

8.0

10.0

Mortgage Equity Withdrawal as a % disposable income

1970 1988 1998 2003 2006

Chart 2.3.1.6 – Mortgage Equity Withdrawal 1970-2006 £M (source: Bank of England)

Chart 2.3.1.7 – Mortgage Equity Withdrawal as a % of Disposable Income (source: Bank of England/ONS)



2.4. A Summary of Lending Trends

In this section, we report the more recent trends in lending

on secured and unsecured products that are reported by the

Bank of England.

2.4.1. Secured Lending

The latest data showed that the number of total approvals

for secured lending decreased again toward the end of 2007

after recovering from a bottom in January 2007 once again.

However, both the bottom and the top peaks failed to reach

the levels of the recent years up to 2004. This may well be

explained by the increased interest rates in 2004. Number

of UK Resident Banks’ sterling approvals and that of both

Building Societies’ and Other Specialist Lenders’ sterling

approvals have all followed the same trend with the

exception of their growth rates. Further increases in interest

rates coupled with a tightening of lending policies have

taken some effect.

The 12 month growth rates of the number of the total

approvals and UK Resident Banks’ approvals followed

almost the same route as expected from the majority share

of the banks in secured lending. Despite UK resident

banks’ majority and a negative growth rate (-0.5%), in

August 2005, building societies’ and other specialist

lenders’ positive rates (both around 15%) were enough to

make the total rate positive (4%) as well. However, UK

resident banks’ 12 month growth rate is also positive (3%)

in September 2005, which shows an overall rising trend.

However, this stabilized and has shown a steady downward

trend up to July 2007.

050

100150200250300350400450

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

UK Resident Banks Building Societies Other Specialist Lenders

Chart 2.4.1.1 – Approvals for Secured Lending to

Individuals (thousands) (source: Bank of England 2007)

-1.00000

-0.50000

0.00000

0.50000

1.00000

1.50000

2.00000

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Total UK Resident BanksBuilding Societies Other Specialist Lenders

Chart 2.4.1.2 – 12 Month Growth Rate of Secured Lending

Approvals to Individuals (source: Bank of England 2007)



Similar trends could be observed on the values of

approvals for secured lending, with the other specialist

lenders’ increased share in recent years. Although the level

of numbers was relatively lower in 2005 than it was in

2003 and 2004, the level of values increased through 2006

and 2007 until the last quarter of 2007.

One of the main differences is that although the 12 month

growth rate of UK resident banks for number of approvals

was still negative in August 2005 (-0.5%).

This was the same rate of banks for value of approvals was

well positive even in July 2005 (2.5%) compared to the

negative July growth rates of building societies and other

specialist lenders (-15% and -0.8% respectively). The

growth of specialist lending shows a sharp peak in early

2006 compared to the other lenders since this peak all

trends show a steady decline with the Building Societies

being most pronounced.

0

5000

10000

15000

20000

25000

30000

35000

40000

Jan-

02

Jul-0

2

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06

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07

Jul-0

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UK Resident Banks Building Societies Other Specialist Lenders

Chart 2.4.1.3 – Monthly Value of Approvals for Secured


-1

-0.5

0

0.5

1

1.5

2

2.5

Jan-

03

Jul-0

3

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04

Jul-0

4

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06

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Jan-

07

Jul-0

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Total UK Resident BanksBuilding Societies Other Specialist Lenders

Chart 2.4.1.4 – 12 Month Growth Rate of Value of Approvals for




Types of Lending

Approvals for House Purchase, Remortgaging and Other

Secured Lending have followed similar trends in recent

years, all having almost equal shares in the pie regarding

the number of approvals (112,000, 112,000 and 83,000

number of approvals in August 2005) that have remained

quite static until the fall in 2007. All types of lending see

the bottom peak in January typically.

In terms of the growth rates, remortgaging and other

secured lending follow nearly the same path unlike the

house purchase one.

However, the growth rates of all three have started to show

alike trends since the middle of 2004. Although all the

three rates had negative values in late 2004 and early 2005,

remortgaging had a relatively higher level. The sharp

upward trend in house purchase in 2006 has been followed

by a decline into negative growth rates in 2007.

0

50

100

150

200

250

300

350

400

450

Jan-

02

Jul-0

2

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03

Jul-0

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Jan-

06

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Jan-

07

Jul-0

7

House Purchase Remortgaging Other Secured Lending

Chart 2.4.1.5 – Monthly Number of Approvals for Secured Lending to


-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

Jan-

03

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7


Chart 2.4.1.6 – 12 Month Growth Rate of Number of Approvals for




Unlike the similar shares for the number of approvals, a big

difference is apparent for the value of approvals. The share

of other secured lending was only around 8% in August

2005. House purchase and remortgaging had analogous

shares in August 2007, and after peaking in July 2007 a

sharp decline is evident.

Whereas the 12 month growth rates of House Purchase and

Other Secured Lending were negative from July 2004 (the

rate for Other Secured Lending was still negative in August

2005), the growth rate of remortgaging went up to a

positive by the end of 2005. It is also possible to notice

here that the rate of remortgaging did not see the negative

levels of house purchase and other secured lending in late

2004 up to mid 2007.

0

5000

10000

15000

20000

25000

30000

35000

40000

Jan-

02

Jul-0

2

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7




-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Jan-

03

Jul-0

3

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04

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5

Jan-

06

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07

Jul-0

7


Chart 2.4.1.8 – 12 Month Growth Rate of Value of Approvals for




Gross Lending

The amount of total sterling secured gross lending follows

the trend of value of approvals in a very similar way,

seeing the bottom in January and increasing towards the

summer. Overall, there has been a steady trend increase

since early 2005.

Repayments

In terms of repayments of secured lending, repayments on

redemption, regular repayments, and other lump sum

repayments had alike trends. Repayments on redemption

formed the majority of repayments of secured lending at

around 80% of the total repayments. The amounts have

increased 2 and a half times since 2002.

0

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Chart 2.4.1.9 – Monthly Amount of Total Sterling Secured Gross

Lending to Individuals and Housing Associations (in sterling millions)

(source: Bank of England 2007)

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Chart 2.4.1.10– Monthly Amount of Sterling Repayments of Secured

Lending by Individuals (in sterling millions)




2.4.2 Unsecured Lending

Unsecured gross lending trend is likely to move in a zigzag

manner, having the peaks in each December. Whilst credit

card lending has a top peak in December, other consumer

credit lending tends to have a bottom peak. Furthermore,

the level of the bottom peaks of other consumer lending

has an increasing trend unlike the top peaks of credit card

gross lending.

The trend of amounts outstanding of unsecured lending

shows little fluctuation over time. The amounts outstanding

of both credit cards and other consumer credit have

increased steadily except for a short decline in credit cards

in early 2003.

0

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Chart 2.4.2.1– Monthly Amount of Total Sterling Unsecured Gross Lending

to Individuals (in sterling millions) (source: Bank of England 2007)

Chart 2.4.2.2– Monthly Amounts Outstanding of Total Sterling Net

Unsecured Lending to Individuals (source: Bank of England 2007)



Despite the apparent zigzag shape, credit card repayments

have a rising trend over time with, however, a lower

growth rate recently.

Repayments-to-Amounts Outstanding ratio has started to

decrease since April 2004 and despite some sharp short ups

and downs it continues to remain quite static.

Both credit card and personal loan interest rates show

similar trends recently, especially in 2005. Both have a

decreasing trend very recently followed by a steady

increase from the start of 2004 to the second quarter of

2005. Regardless of the time, credit card interest rates have

had a slightly higher level than personal loan interest rates

in recent years up until July 2007 where they converged.

0

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12000

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Credit Card Personal Loans

Chart 2.4.2.3– Monthly Amount of UK Resident Banks’

(inc. Central Bank) Sterling Credit Card Repayments by

Individuals (in sterling millions)


Chart 2.4.2.4– Monthly Amount of UK Resident Banks’

(inc. Central Bank) Sterling Credit Card Repayments by

Individuals/Monthly Amounts Outstanding of Total

Sterling Net Credit Card Lending to Individuals


Chart 2.4.2.5 - End Month Weighted Average Interest Rate,

Bank & Building Societies (source: Bank of England 2007)



2.5. The Over-Indebtedness Debate

Once a borrower reaches the position that they are unable

to meet their debt obligations and scheduled repayments,

i.e. the borrower defaults or falls into ‘arrears’; then they

can be regarded as over-indebted. Most consumer lenders

define ‘default’ as three consecutive missed payments and

‘arrears’ as one or more missed payments on revolving or

fixed term credit accounts. Clearly many borrowers may

miss payments due to some temporary financial difficulty,

but are able to recover the situation and return accounts up

to date and therefore would not be defined as ‘over-

indebted’. On the other hand, some borrowers may be

currently up to date but realise that is not long-term

sustainable and therefore are at risk of being ‘over-

indebted’. Assessing the incidence and extent of over-

indebtedness amongst UK households is, therefore,

problematic.

Households that are ‘in arrears on a structural basis’

eventually default, the extent of which can be estimated by

the numbers of bankruptcies, IVA’s, and to some degree by

the number and values of CCJs and debt write-offs and/or

debts being placed with Debt Collection Agencies and

Debt Buyers. Estimating the number of households ‘at risk’

is far more difficult to determine in the current climate.

Those ‘at risk’ may be conflated with debtors in

‘temporary difficulties’ if we analyse the level of ‘arrears’.

However, the lending market now allows debtors ‘at risk’

to disguise any problems for much longer than in the past

by the ability to continually restructure debts by taking on

products from other lenders or rescheduling their debts

with existing lenders i.e. the balance transfer, ‘arrangement

to pay’ and consolidation loan environment.

Those with a rising property value have also had the option

to re-mortgage and/or ‘equity release’ as a means of

recovering in the short-term. Thus, even though changes in

arrears levels may be a useful proxy for potential over-

indebtedness, it could either seriously under-estimate or

seriously over-estimate the true extent of over-

indebtedness. In the past, the path to default was easier to

track, individuals in arrears soon ran out of refinancing

options. In the recent climate, an individual with serious

debt problems can manage to keep up to date on credit

accounts and show none of the obvious symptoms of

financial distress until the terminal stage. Recent accounts

of up to a million individuals covering mortgage payments

with credit card cheques is perhaps a compelling example

of this (Shelter, October 2007).

In order to assess the household sector’s ability to meet

debt obligations its is important to analyse debt service

ratios, i.e. the funds available to meet monthly interest

payments and debt to income/wealth ratios.

The ratio of household debt to income has risen by 50%

since 200013

and stands at 160% in the first quarter of

2007. The debt to income ratio has been rising steadily

since 1998 with an acceleration in growth rate post 2000.

The recent interest rate rises and the strong growth in debt

levels relative to earnings are likely to further increase the

debt to income ratio.



The ratio is now close to that in the US economy. A more

important concern, however, is how well the consumer can

service the debt out of current and future cash-flow. In order to

assess the financial fragility of households we need to have a

view of the consumers complete balance sheet position which

takes account of household assets. The latter is more difficult

to proxy.

An indicator of financial health is the share of income

devoted to servicing debt (income gearing). Mortgage debt

service measures have been quite stable since the interest

rate hikes of the late 80’s and have fluctuated around 8-

10% in the period up until 2004 including unsecured debts

the share of income has fluctuated around 20% until more

recent times.

The increase in mortgage debt levels coupled with recent

rises in interest rates has resulted in a sharp increase in the

share of income devoted to servicing debt. Gross interest

payments have increased by more than 2% as a share of

disposable income since 2004. This trend increase is

expected to continue as the impact of larger mortgages and

higher rates feeds through despite the obvious tightening of

credit policy by the lenders. Reported statistics on debt

servicing vary considerably and are, of course, sensitive to

the sample selected. Although the ‘average household’ is

spending around 12% of its disposable income on interest

payments, if we take only the ‘credit active’ population

then, in 2007, households are spending around 30% of their

income servicing debt, up from around 20% 10 years

ago14

.

Chart 2.5.1 – Debt to Income Ratio (source: ONS

and Bank of England 2007)

Chart 2.5.2 – Income Gearing (source: ONS and

Datastream 2007)

Chart 2.5.3 – Debt to Wealth Ratio (source: ONS and

Bank of England 2007)

0%

5%

10%

15%

20%

8 7 8 8 89 9 0 9 1 9 2 9 3 9 4 95 96 9 7 9 8 9 9 00 01 0 2 0 3 0 4 0 5 06 07Repayments as a % of Disposable Income

Incom e G earing

Inte res t o nl y In te re st and mo rta ge rep ayme nts

Source: ON S a nd Datastre am

0 %

2 0 %

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% of Annual Disposalable Income

D e b t to In c o m e R a t io

S o u rc e O N S a n d B a n k o f E n g la n d

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£ Billion

W e a lth D e b tSo u rce O NS and B ank o f Eng la nd



Some commentators point to the growth in ‘wealth’

relative to the growth in household debt. Wealth comprises

household assets such as pensions, shares, savings and

property values. The chart shows that the growth in wealth

has outpaced that of debt and the gap between wealth and

debt has increased. Of course, there are problems with such

analysis. Firstly, wealth is something of a ‘will o’ the wisp’

- property prices and share prices can ‘collapse’ and so

with them much of the reported balance sheet wealth.

Secondly, the distribution of debt and wealth across the

population are very different as is the gap between wealth

and debt across the rich-poor the spectrum. A recent study

by the Bank of England (Quarterly Bulletin, 2007 Q1)

reports that older households (55+) have experienced the

greatest net gains in wealth whilst the middle-aged

households (35-54 years) have increased their indebtedness

most over the same period. They suggest that “the

distribution of debt has become more skewed with fewer

households borrowing larger amounts” (p71).

Obviously the middle-age population have a longer

expected future income stream and using the flexibility in

the credit industry can take action to spread current

problems over an extended period and avoid short-term

financial distress. However, this is the same age group that

have the largest outstanding credit card balances and other

unsecured lending products.

2.5.1 Arrears

Arrears levels and trends in arrears are an important

indicator of debt problems and a gauge of the extent of the

shift from temporary difficulties to more structural

problems in debt servicing. Hard statistics on arrears across

the range of financial products are difficult to obtain. The

Council for Mortgage Lenders report that the number of

mortgages in short-term arrears rose to 125,100 in June

2007 which was slightly down on the previous year. The

Bank of England’s Financial Stability Report (2007,

October) attempts to measure the number of households

that are liable to default should economic conditions

worsen. They report a model of household distress that is

disaggregated by age and income. They conclude that

arrears will be concentrated in a small proportion of

households with low income/high debt and that “the

number of arrears spanning the majority of the income and

debt distribution is small” but with changes in interest rates

and growth in indebtedness “there is a growing tail of

vulnerable households” and that the “outlook for the UK

household sector appears to be more uncertain than for

some time”. Moreover, the Bank of England Quarterly

review (2007 Q1) warn that “larger shocks than seen

recently, particularly shocks impacting on interest rates,

income or employment, could cause adverse interactions

between debt, house prices and consumption” (p76).

2.5.2 Trends in Write-offs by Major Lenders

Whereas secured lending write-offs decreased from 2000

to 2004, unsecured lending write-offs, both credit cards

and other unsecured lending, have kept rising steadily since

2000 accelerating from 2003 up until summer 2007.

Together with a lower level of credit card repayments and

an increasing trend in amounts outstanding of unsecured

lending, the steady increase in unsecured lending write-offs

may be the sign of a lowered credit quality level in the

unsecured lending industry. The ratio of write offs-to-

amounts outstanding for credit cards is also increasing

steadily with a remarkable peak in the first quarter of 2002.

The secured lending write-offs show a considerable

increase in 2005 and 2006 with a peak similar to the end of

1999. They have started to decline in 2007.



Credit Card Lending…

Chart 2.5.4 – Credit Card Lending


Other Unsecured Lending…

Chart 2.5.5 – Other Unsecured Lending

(source: (source: Bank of England)

Secured Lending…

Chart 2.5.6 - SecuredLending

(source: (source: Bank of England)

The ratio of write-offs to credit card lending peaked in

January 2002 as a result of a considerable increase in

arrears in 2001. Since 2003 the trend has been sharply

upwards until summer 2007.

Ratio: (An Example)

Quarterly Amount of UK Resident Banks’ Sterling Write-offs of Credit Card

Lending to Individuals / Quarterly mounts Outstanding of Total Sterling Net

Credit Card Lending Individuals

Chart 2.5.7 – Ratio of Write offs to Credit Card

Lending (source: ???

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2.6 Personal Insolvency: Bankruptcy and Voluntary Arrangements

The levels of personal insolvency as gauged by the number

of bankruptcies and individual voluntary arrangements

show a quite spectacular increase since 2000. The

beginning of this upward trend pre-dates the changes in

bankruptcy law introduced in April 2004, although there is

a clear acceleration in the levels of declared insolvencies

post-2004. The Act appears to have encouraged individuals

on the path to bankruptcy to declare early.

The legislation changes allow individuals in serious

financial difficulty to be discharged from bankruptcy after

a maximum of one year as opposed to 3 years under the old

rules. Although the legal changes make the bankruptcy

option more attractive, the bankruptcy trend is more likely

symptomatic of a tremendous increase in the number of

individuals facing severe financial difficulty. The level of

personal insolvency appears to have peaked at the end of

2006 and was at a level almost 3 times higher than the

previous peak in the early 90’s recession.

Chart 2.5.8 – Major UK Banks Annual Write Off Rates

(source: Bank of England 2007

Chart 2.5.9 – Personal Bankruptcies and Individual

Voluntary Arrangements (source: DTI 2007)



What is particularly striking about the growth in

bankruptcy is that the trend increase occurs against a

background of generally good macro-economic and

monetary conditions, GDP growth, low interest rates, high

levels of employment and strong asset prices. The 90s’

peak occurred against a backdrop of economic decline and

nominal interest rates in the region of 13-14%.

Some commentators argue that the insolvency levels are

still relatively low in relation to the number of individuals

in debt and therefore are not indicative of a general

increase in household financial stress. The personal

bankruptcy ratio, bankruptcy filings per 10000 adults

(source: Insolvency Service and ONS), rose from 0.30 in

1970 to 3.86 in 2005 and is estimated to have reached 4 in

2006.

2.6.1. Bankruptcy Modelling – Key Drivers

The CMRC has produced a model of personal bankruptcy

rates in an attempt to determine the key drivers of

bankruptcy. The purpose is to model variations in personal

bankruptcy in relation to other macro-economic and credit

related statistics.

It is clear that personal bankruptcies, household

indebtedness, and consumer credit are highly interrelated.

Furthermore, it is suggested that the evolution of personal

bankruptcies and laws related to them have been

influenced considerably by the consumer credit expansion.

Although there are some conflicting arguments regarding

why bankruptcies have increased steadily and reached to

record levels, the main reasons are generally cited as the

increased credit availability, decreased credit quality in the

industry, decreased default costs (fall in “social stigma” or

in “legal costs”), changes in regulations and laws, and

macroeconomic shocks.

The data used in our study are described briefly below:

The personal bankruptcy ratio is calculated as the number

of individual insolvencies divided by the adult population.

The insolvency data is gathered from the Insolvency

Service as the number of individual insolvencies in

England and Wales on a seasonally unadjusted and

quarterly basis from 1960 to 2006. The quarterly

population data for the UK is collected from the Office for

National Statistics as the population aged over 16 (ONS

Chart 2.5.10 – Personal Bankruptcy Ratio (Source ???)



code: MGSL). The England and Wales quarterly adult

population is then calculated from the population estimates

gathered from the General Register Office for Scotland and

Northern Ireland Statistics and Research Agency.

Debt-to-income ratio, an indicator of the household

indebtedness level, is calculated as the total household

liabilities (ONS code: NNPP) divided by the real

households’ disposable income (ONS code: NRJR) with

the ONS data on a quarterly basis from 1987 to 2006.

Quarterly values of Real Households’ Disposable Income

are multiplied by 4 to match the nature of the liability

values. Capital Gearing, a factor that shows the level of

indebtedness relative to household wealth, is calculated as

the ratio of total household liabilities (ONS code: NNPP)

divided by total household financial assets (ONS code:

NNML).

Amounts Outstanding of Net Lending to Individuals, an

indicator of the trend in the consumer credit volume, is

reported both for each lender type and for each type of

lending. The Bank of England data contains information

about UK Resident Banks’, Building Societies’, other

specialist lenders’, retailers’, and other lenders’ lending as

well as secured and unsecured lending in total over time.

However, the data do not inform about the proportion of

secured or unsecured lending for each type of lender.

Write-off Ratio, an indicator of the default behaviour over

time, is calculated as the Amount of Write-offs of Lending

to Individuals divided by the Amounts Outstanding of Net

Lending to Individuals using Bank of England data on a

quarterly basis. The data includes only UK Resident

Banks’ write-off amounts for secured and unsecured

lending. However, amounts outstanding of UK Resident

Banks’ secured or unsecured lending is not available

separately. Therefore, although it is more desired to use the

unsecured lending write-off ratio, such an application is not

possible with the data available. Hence, the ratio calculated

here is the UK Residents’ Banks’ write-off ratio in total

including both secured and unsecured lending due to the

data limitation.

ILO Unemployment Rate for England (ONS code: YCZG)

is selected to represent Unemployment, a proxy of

economic discomfort and financial strain for households.

Since the ILO rate is calculated for the economically active

resident population, it may also be more representative for

the economic shocks for households.

Data for Interest Rates, which could be stated as the cost of

credit, is collected as Treasury Bill interest rates given that,

as widely argued, economic conditions as well as the

inflation may have an effect on Treasury Bill Interest

Rates. Data for Quarterly average rate of discount of 3

mount Treasury Bills is gathered from Bank of England on

a quarterly basis from 1975 to 2006.

Data for Household Savings, which would help to deal

with income shocks, is gathered from the ONS as the

Households’ Saving Ratio (ONS code: NRJS) on a

quarterly basis from 1963 to 2006. Self-employment is

calculated with a ratio as the number of self-employed

divided by the adult population. Data for the number of

self-employed is gathered from the ONS (ONS code:

MGRQ) for the UK and the UK adult population is used to

calculate the ratio accordingly.

Retail Prices Index (RPI), one of the main measures of

inflation, is used as an indicator of the changes in the cost



of living that may have an effect on households. The RPI

data is collected from the ONS as the RPIX (ONS code:

CHMK) which is the retail prices index excluding

mortgage interest payments to minimise the impact of the

interest rate changes.

Consumer Confidence, a factor that may affect bankruptcy

decisions as public’s confidence in the economy, is

represented with Retail Sales Index (RSI) in terms of

volume with constant prices for predominantly non-food

stores (ONS code: EAGX). Consumer spending, which is

one of the main economic drivers of the whole economy, is

generally cited to be affected by consumers’ confidence in

the economy. Another general view is that when consumer

confidence falls, it is more likely to see a drop in spending

on comfort or durable products than in spending on food.

Income Gearing, an indicator of the affordability of debt, is

considered as both mortgage and total income gearing.

Total Income Gearing, which is related to the total cost of

servicing household debt, is calculated as the ratio of

household interest payments (ONS code: QWMG) to real

households’ disposable income (ONS code: NRJR) on a

quarterly basis. Mortgage Income Gearing is calculated as

mortgage average interest rate (ONS code: AJNL)

multiplied by amounts outstanding of total secured net

lending (Bank of England data) and divided by real

households’ disposable income (ONS code: NRJR).

The series are modelled using a dynamic time-series

methodology which attempts to identify and model those

factors that form a long term relationship with personal

bankruptcy rates with those that affect bankruptcy rate in

terms of short-run dynamics. The debt-to-income ratio and

the indebtedness level of households, emerge as the key

long-term determinants of personal bankruptcies in the

sample period. The econometric model suggests that other

than the debt-to-income ratio, the growth rate of the write-

off ratio and consumer confidence have significant short-

run effects on personal bankruptcies. Although the study

does not find unemployment or inflation significant in the

equation, they still may have an impact on bankruptcies.

The reason of insignificance may be the relatively stable

nature and low levels of such factors in the sample period.

The results of this study need to be interpreted according to

the sample period. The write-off ratio only has a short-run

impact on personal bankruptcies in the sample period. The

ratio used in this research is a general ratio of all lending

types. However, unsecured lending write-off ratio may still

form a long term relationship with personal bankruptcies.

The research is unable to explain a relatively sharper

increase in personal bankruptcies between 2004 and 2006

other than suggesting that the new bankruptcy law is

largely responsible for this increase.

2.7. County Court Actions to Recover Debt

Previous research by CMRC (Debt Survey 2004) indicated

that the use of court action, by the major lenders and credit

card providers, to recover debt from consumers in default

had generally been in decline. In recent interviews with

lenders, however, it is clear that the use of various forms of

court action to secure and recover outstanding debt have

been increasing again. Indeed the Registry Trust recently

commented that, “lenders are increasingly using the court

route to deal with unsecured debts. A judgement opens the

way to further action such as a charging order “(RT Press

Release, October 2007).



The number of CCJ’s against consumers has grown rapidly

since 2004 and reached a ten year high by the end of 2006

with 843,853 judgment orders. The growth has continued in

2007 with almost 250,000 judgements in Q1 and therefore the

total could reach 1 million judgements by the end of the year

compared to just over half a million in 2004. Registry Trust

estimates that around 70% of judgements are ‘credit related’

the remaining 30% being for unpaid tax, utility bills and motor

tax. Interviews with major lenders found that county court

action in order to gain a ‘charge on the assets’ of a debtor were

becoming common practice.

2.8 Factors Affecting Indebtedness

This section provides some background on trends in consumer

indebtedness and the recent response of collections and

recovery departments. A key point is that consumer

indebtedness has increased substantially in the last 5 years and

households typically have debts spread across multiple

creditors. There are signs of an increasingly fragility in the

economy with a larger proportions of households on the

interface between ‘struggling’ with payments and being in

more serious ‘financial difficulty’.

Households in financial difficulty will typically have a

‘pecking order’ of creditors and are likely to pay those whose

service they value most, those who have most

sanctions/threats and/or those with the most sophisticated and

proactive collections activities.

There are a number of reasons put forward to explain why

accounts become delinquent i.e. the borrower defaults on

payments. Most have always been cited as factors

precipitating financial difficulty. For example, changes in

work circumstances and unemployment or problems with self-

employment; changes in family circumstances such as marital

break-up, separation and divorce or illness and bereavement;

suspicious circumstances such as suspected fraud. Clearly

some of the factors might be interrelated. For instance,

unemployment may place strain on marriages and precipitate

indebtedness. More recently, factors such as over-commitment

and spending sprees have been cited as reasons for advanced

arrears and indebtedness. The latter, in practice, may be

difficult to define. It may be treated as 'quasi-fraud' or

'malicious spending' rather than financial mismanagement.

Understanding the customer's psyche and the difference

between those who are 'free and easy' with spending and those

who are slightly over-committed but 'in control' is important

but not trivial. Understanding the reasons for over-committed

customers is a particularly important for those working at the

Chart 2.5.11 – Consumer County Court Judgements 2002-2007

(Source: Registry Trust)



sharp end, such as collections agencies that have to develop

collections strategies to deal with this type of customer. From

our interviews with lenders, we can draw the following

general conclusions regarding credit and indebtedness:

• Consumers have found it easier to get credit as

lenders competed for business; even when their

credit worthiness has been highlighted as a problem;

More recently credit policies across both secured

and unsecured lending has considerably tightened

(in the last 2 years) making credit access more

difficult for customers with high levels of debt and

‘restructuring opportunities’ less likely;

• Consumers are likely have more debt and more

unsecured debt as the average outstanding balance

of the credit active household has increased;

• Consumers are more likely to have multiple debts

spread across different lenders; the average value of

outstanding unsecured debt of households that are in

difficulties is estimated as between £20,000 to

£40,000 and spread across multiple creditors;

• Personal finance (e.g. loans; consolidation loans)

now tend to have longer repayment periods

compared to a few years ago and higher interest

rates;

• Lenders are more willing to restructure debt over

longer periods and ‘re-age’ current balances;

• There has been a significant increase in Home

Equity Finance as a means of consolidating

debt;

• There has been a significant increase in lending and

products aimed at the sub-prime market, particularly

sub-prime and buy-to-let mortgages;

• Lenders are beginning to use litigation via the

county court system to obtain ‘charges on assets’;

• Borrowers are increasingly using debt management

and IVAs as a route out of debt.

A common finding from our study of large volume collection

activities was that customers would often find themselves in

financial difficulty and arrears on consumer debt due to 'over-

commitment' i.e. too many debt repayments in relation to

current levels of income. Recent survey evidence suggests that

over-commitment continues to be cited as the major reason for

payment difficulties. Increasingly, however, the borrower

treats the matter with less concern, less urgency and feels less

‘stigma’ about the problem. Because a consumer's

indebtedness is a function of total consumer debt outstanding

it will span all types of credit across many possible lenders.

The practice of spreading debts across a wide range of

products and lenders obviously makes it very difficult for an

individual lender to assess the customer's 'ability to pay' and

the likelihood that they will service the debt.

Increasingly consumers in financial difficulties are applying

for finance without revealing their complete financial position.

The lender is only likely to discover the true position when

repayment difficulties become apparent. Thus information on

over-committed customers, often only comes to light once the

debtor is in an advanced state of arrears and in the collections

system. The Credit Reference Agency, Experian, has recently

launched a new product that attempts to assess the total level

of indebtedness of individual borrowers (Indebtedness Index).

The trend in consumer indebtedness has led to charges of

irresponsible lending on behalf of the lenders and has seen an

escalation in the use of debt consolidation services and 'advice'

organisations. These trends have implications for the debt

collection industry. The large volume lenders that were

recently interviewed expressed some concern that indebted

customers are more likely to use fee-paying advisors and

consolidation companies to manage their debts rather than

confront the situation themselves. Some general conclusions

were observed:



• Indebted customers are more likely to pay fee

paying advisors in order to avoid confronting the

problem with individual lenders;

• Indebted customers go earlier to advisors;

• They are likely to turn down or avoid free advice

from their creditor/lender;

• There is a trend increase in the number of consumers

using bankruptcy and Individual Voluntary

Arrangements (IVAs) in order to deal with creditors

(Trust Deeds in Scotland);

• The major lenders are beginning to resist IVAs.

Over-commitment may stem from a number of causes, clearly

changes in levels of income e.g. due to unemployment or

divorce may leave a customer unable to meet commitments

that were arranged on the basis of higher levels of expected

income. It may, however, be a function of the mismanagement

of personal finances or rash spending sprees. These latter two

are the most likely reasons for over-commitment i.e. general

indebtedness where the consumer takes on too much debt in

relation to income and spending sprees where injudicious

spending begins to cause mounting problems in servicing

current debts.

The government and regulators have taken an interest in

promoting both ‘responsible lending’ and ‘responsible

borrowing’ in order to mitigate potential debt problems. The

lender-borrower relationship has often been blighted by

problems of incomplete and ‘asymmetric information’. The

lenders require a complete picture of the borrowers income

and asset position in order to be able to assess risk and

appraise credit worthiness. The information provided by

Credit Reference Agencies has provided a incomplete picture

of the potential debtors profile since only recently have some

of the major banks (HSBC, NatWest) agreed to share

information via the CRAs. Recent work by the CRAs to build

‘indebtedness indices’ which profile the customers

debt/income position should be helpful for future lending

decisions but have not been available in the past. The sharing

of positive credit data is another welcome development for

lenders and collection departments.

Recent changes to the Consumer Credit Act and other

government interventions have attempted to improve the

information provided by lenders, particularly transparency on

quoted APR’s, bank and late payment charges and redemption

penalties. The Consumer Credit Bill aimed to create more

competition and protection for consumers. The growth in

payment protection products and other safety-nets should

reduce the impact of ‘changes in circumstance’ on vulnerable

groups.



2.9 Fraud

The Credit Industry Fraud Avoidance System (CIFAS) report

an escalation in fraudulent behaviour in the use of financial

products. Recent data released by CIFAS (October 2007)

suggests that fraud trends continue upwards. Application fraud

increased by 23% from 2006-7 with 57,321 detected cases

reported to CIFAS and identity fraud, although slightly down

had 57,302 reported cases.


CIFAS Case TypeJanuary to Sept

2006

January to Sept

2007

% Change

Asset Conversion relates to the sale of assets subject to a credit agreement where the lender retained ownership of the asset, for example a car or a lorry.

Misuse of Facility is where an account, policy or other facility is obtained for fraudulent purposes or the fraudulent misuse of a facility.

Identity Fraud cases include cases of false identity, identity theft, account takeover and other impersonation situations.

Application Fraud/False Insurance Claim relate to applications or claims which include lies or false supporting documentation where the name has not been identified as false.

Facility Takeover Fraud occurs where a person (the 'Facility Hijacker') unlawfully obtains access to details of an existing account holder or policy holder or an account or policy of a genuine customer or policy holder (the 'victim of takeover') and fraudulently operates the account or policy for his benefit or the benefit of another authorised person.

Misuse of Facility 16,774 16,841 0.40%

False Insurance Claim 281 306 8.90%

Facility Takeover Fraud 3,625 4,844 33.63%

Asset Conversion 285 352 23.51%

Identity fraud 58,050 57,302 -1.29%

Application Fraud 46,468 57,321 23.36%

CIFAS Category 1997 1998 1999 2000 2001 2002 2003 2004 2005

Category 1 - False Identity 2,231 1,902 2,189 12,310 27,270 42,029 57,669 69,512 80,894 Category 2 - Victim of Impersonation 17,847 16,810 18,075 22,539 26,266 32,737 43,094 50,455 56,200 Category 3 - Application Fraud Facility Granted 15,338 15,348 11,531 13,524 13,213 18,354 18,893 19,865 22,466 Category 4 - Application Fraud Facility Refused 54,284 60,710 66,006 86,077 123,606 146,431 152,070 162,911 153,290 Category 5 - Conversion* 1,180 1,238 775 751 800 662 832 875 1,140 Category 6 - First Party Fraud 13,343 13,014 17,608 21,867 30,507 36,453 36,526 41,588 41,313 Category 7 - Aiding & Abetting** 0 0 0 6 24 37 12 27 47 Category 8 - Insurance Claims Fraud** 0 0 0 10 144 993 960 802 488 Total 104,223 109,022 116,184 157,084 221,830 277,696 310,056 346,035 355,838

% Change over previous year - 4.60% 7.15% 35.20% 40.46% 25.18% 11.65% 11.60% 2.80%

% Change since 1997 - 4.60% 12.08% 51.53% 112.84% 166.44% 197.49% 232.01% 241.41%

*Sale of assets subject to a credit agreement where the lender retained title to the asset. **Category introduced in the year 2000




3. Commercial Lending and Trade Credit

All organisations that are involved in any form of lending

to the commercial sector, corporate and small businesses,

are a potential source of business for the commercial debt

collection, debt purchase and outsourced credit

management services industry. This lending includes all

manner of bank products from overdraft to loans, factoring

and asset-based finance and commercial mortgages all of

which may be subject to default/payment arrears. Indeed

since 1999, the net indebtedness of the corporate sector,

measured by gearing ratios, has shown a marked increase

and remains at an historically high level. Moreover, all

business and organisations involved in business to business

trade (supplying trade credit) on a deferred payment basis

(on invoice) in both product and services markets may

decide to make use of collection agents if debts fall into

arrears. Increasingly, the government sector, as a collector

of taxes or a contractor with the private sector, is becoming

a source of debt collection and recovery business. The

potential size of the commercial debt collection market is,

and will be, influenced by the total amount of corporate

lending activity and the propensity for borrowers to go into

'arrears'. The implementation of the Late Payment of

Commercial Debts (Interest) Act has increased the

propensity for businesses, of all size, to pass on trade debt

to commercial debt collectors. At the time of writing our

analysis forecasts an increase in corporate insolvencies

during 2008-09 and particular pressure on the SME sector

that that is most affected by the recent restrictions in bank

lending to business. The result is to try and substitute bank

credit for trade credit and take extended trade credit where

possible (resulting in late payment). Corporate payment

delays and bad debts are likely to increase along with

insolvencies.

3.1 Business Growth and Insolvency in the UK

The common definition of default, 90+ days late, applies

equally to the commercial and consumer sectors. Basel II

deliberations defined default as 90 days late and such a

definition is commonly used by the credit insurers as a

trigger for claims. Default and ‘arrears’ can be

distinguished. The Finance and Leasing Association (FLA)

regards a debt to be in arrears if it is more than two

payment instalments overdue and/or over 31 days overdue

- approx 3% of outstanding balances in direct and sales

finance were in 'arrears' in their analysis15

. Euler Hermes

estimated that businesses that use collection agents contact

their debtor an average of six times before passing on the

debt to the agency16

. Thus, commercial debt arising from

trade credit can be considerably older than 90 days prior to

being placed with a debt collector. Clearly the 'younger' the

debt is when it is placed with a collection agent, then the

better chance of recovery. The market for commercial debt

sale is, consequently, very small.

As in consumer credit the latter is affected by underlying

economic conditions, the quality of lending and risk-return

decisions and in-house credit management practice, i.e.

how well the debt is worked prior to being out-placed. The

Late payment of Commercial Debts (Interest) Act has had

an impact of the extent of outplacement to the DCA sector.

The fact that DCAs can impose an interest charge and

recover some collection costs has made out-placing debt

more cost effective for the commercial sector and

particularly SMEs. Increasingly DCAs are offering to

collect overdue debts ‘for free’ i.e. the DCA keep the

interest charge (8% + base rate) rather than charge

commission.



Clearly the volumes of commercial debt out-placed will be

a function of the number of businesses experiencing

financial difficulties and delaying payments to suppliers.

The pattern of corporate bankruptcies and liquidations will

be indicative of the degree of fragility and corporate

financial distress.

There has been a trend increase in the number of active

companies registered with Companies House. The stock of

active businesses approached 2.3 million in 2006.

According to Companies House the number of new

incorporations has been growing rapidly year on year, e.g.

43% 2003-6.

In total, unincorporated businesses and SMEs account for a

significant proportion of the business stock. This is

estimated to have grown by more than 1.4 million since

1980.

The stock of small businesses is estimated at 3.8 million.

SMEs account for 52% of aggregate business turnover and

56% of private sector employment, according to the SBS.

Barclay’s bank estimated that the number of business start-

ups has been growing at approximately 20% pa since 2002;

and in 2003 the number of new start-ups was 465,000.

Business closures, however, are also high. It is estimated

that over 50% of new starts go out of business within 3

years. Of course, not all of these leave unpaid debts behind.

The company birth rate, new registrations and a proportion

of the stock of active companies showed strong growth

from 2000 to 2004 with a levelling off up to 2006 (Q2) at

around 2%.

Number of Registered Companies

0

500000

1000000

1500000

2000000

2500000

2001

3

2001

4

2002

1

2002

2

2002

3

2002

4

2003

1

2003

2

2003

3

2003

4

2004

1

2004

2

2004

3

2004

4

2005

1

2005

2

2005

3

2005

4

2006

1

2006

2

Chart 3.1.1 – Register Size in Great Britain (1992-2006)

(Source: Companies House)



The number of company insolvencies (compulsory and

creditors’ voluntary liquidations) in the England and Wales

was 3,194 in the last quarter of 2006, nearly half of the

figure that was observed in the third quarter of 1992 with a

record number of 6,509.

Although the trend fluctuated around 3,500 insolvencies

per quarter between 1995 and 2007, the figures have been

much lower than the levels of the early 1990s’ recession.

The seasonally adjusted figures provided by the Insolvency

Service show 3,032 liquidations in the second quarter of

2007, representing a 4.2% decrease on one year ago.

COMPANY BIRTH RATE

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

2001

3

2001

4

2002

1

2002

2

2002

3

2002

4

2003

1

2003

2

2003

3

2003

4

2004

1

2004

2

2004

3

2004

4

2005

1

2005

2

2005

3

2005

4

2006

1

2006

2

Chart 3.1.2 – Company Birth Rate (2001-2006)

Source: Companies House

Chart 3.1.3 – Company Insolvencies (1975-2006)

(Source: Companies House)



Corporate failure may be the necessary by product of the

competitive process. One might argue that markets

basically keep efficient firms inside but throw out the

inefficient ones, as the natural process in aggregate

economic activity, in order to secure future growth and the

efficient use of resources. However, company failures

result in immediate social costs for families after possible

job losses or more seriously affect a whole region or a city

if the company is large enough to drive that area’s

economy. Indeed individual corporate failures have a

knock on effect via bad debts that puts pressure on the

cash-flow of otherwise healthy companies and impacts on

their ability to generate new future projects or investments,

and indeed, may push them into bankruptcy.

Company failure investigations can be highly useful for

banks, investors, and also trade credit specialists. On the

one hand, lenders need to know who to give credit safely

and profitably or creditors who to trade with or investors

who to invest in. On the other hand, they also want to

know how companies they have a business relationship

would react to aggregate economic fluctuations. For

instance, the Basel Capital Accord has provided the

impetus to lenders to research and develop adequate

default/failure prediction models for all of the business

sectors of their lending portfolios. Once implemented these

risk management systems have to be ‘stress-tested’ under

different economic scenarios which track the ‘prior

probabilities’ of failure.

Research by the Bank of England shows a clear

relationship between insolvencies and the write-off rate of

the banks.

Chart 3.1.4 – The Relationship between Insolvencies and the

Write-off Rates of Banks (Source: Bank of England)



3.2 Forecasting Corporate Insolvencies

In order to gain insights into the economic drivers of

business failures, we compile a macro-economic data-base

using aggregate UK data between 1995 and 2007. It is

worth noting that this data is from a period of relatively

stable economic conditions A sample, which is exclusive

of a recession, may offer results that can reveal what

aggregate factors are likely to affect company failures

under a relatively healthy economic environment. Such

results can be considered with an aim of understanding the

factors that keep the number of operating companies at a

maximum. Lower levels of company failures are likely to

lessen not only reverse social costs in the society (e.g. job

losses) but also administrative costs of bankruptcies, which

could be used more productively in the whole economy

instead of officially eliminating ineffective companies.

Having employed advanced econometric methods, it is

found that whereas company birth rate, income gearing,

and money stock form a long term relationship with

corporate insolvency levels, lending to corporate sector,

aggregate profitability, trade credit defaults (county court

actions) and business confidence have significant short-run

effects on corporate insolvencies.

Data sources are generally from publicly available sources

and are as follows:

• The Number of Active Registered Companies

(Companies House);

• Business Confidence Indicator (OECD);

• All Others (Office for National Statistics),the

ONS code of the data set is also provided where

applicable);

• County Court Judgement Information .

Corporate insolvencies are represented with the corporate

insolvency ratio that involves both compulsory liquidations

and creditors’ voluntary liquidations. Members’ voluntary

liquidations are not included because such liquidations do

not necessarily represent insolvency. The corporate

insolvency ratio is calculated by dividing the number of

compulsory and creditors’ voluntary liquidations (ONS

code: AIHQ) by the number of active registered companies

in that period. The liquidation data and registered

companies data are gathered from the Office for National

Statistics and the Companies House respectively.

It is widely argued that corporate insolvency rates may be

related to the “business cycle”. Besides, it is also stated

that business cycles may largely affect company

profitability and, hence, failure rates (e.g. Turner et al,

1992). Therefore, the growth in GDP index at market

prices with chained volume indices1

(ONS code: YBEZ) is

used to control such a relationship. Furthermore, it is also

aimed to control the level of “business investments”, which

is proxied by “Gross Fixed Capital Formation: Business

Investment” in chained volume measures (ONS code:

NPEL).

1 Chained volume measures are used by ONS to represent “constant prices” where the base year is updated regularly.



Despite some opposing arguments and differing empirical

findings regarding other factors, there is a consensus that

profitability is vastly important for companies.

“Profitability” is controlled with four different variables.

The first one is a straightforward profits variable: Real

Gross Operating Surplus of Private Non-financial

Companies (deflated by GDP deflator) (ONS code:

LRWL). The second one is Gross Rate of Return of Private

Non-financial Companies (ONS code: LRWV). The

remaining two variables considered here are generally cited

as the drivers of profitability. They are: Real Unit Wage

Costs (deflated by GDP deflator) (ONS code: LNNK) and

Real Input Prices (materials and fuel purchased) (ONS

code: RNNK) (deflated by output prices (manufactured

outputs) (ONS code: PLLU) deflator). “Productivity” is

also controlled with proxies of output per filled job (ONS

code: LNNN) and output per worker (ONS code: A4YM)

indices.

Interest rates are commonly mentioned as drivers of

company fragility and failures. It is claimed that real

interest rates can be highly influential for company health.

On the other hand, it is also put forward that inflation

and/or nominal interest rates can be the main cause of

company insolvencies depending on the circumstances. It

is aimed to control both types of interest rates, as well as

inflation, in this study. Nominal interest rates are proxied

by London Clearing Banks’ Base Rate (ONS code: AMIH)

and real interest rates are calculated by using GDP deflator.

Inflation is calculated by using GDP (expenditure) deflator

at market prices (ONS code: YBGB).

The availability of money and/or credit is regarded as an

important factor for the aggregate economic activity. It is

controlled by Real Money Stock (M4) (deflated by GDP

deflator) (ONS code: AUYN) and Real Banks’ and

Building Societies Lending to Non-financial corporations

(deflated by GDP deflator) (ONS code: VQSG).

“Over-indebtedness” and high capital gearing are cited as

possible causes of high levels of corporate failures. It is

argued that tax advantage of debt finance should be

managed carefully not to increase the probability of failure.

Indebtedness is controlled with a proxy of Debt-to-GDP

ratio. Debt is calculated by subtracting liquid assets of

Private Non-financial Companies from their total liabilities

at current prices (ONS code: NLBB-(NKJZ+NKXQ)) and

divided by GDP at current prices to obtain the Debt-to-

GDP ratio.

Income Gearing is used to represent the effects of interest

rates, indebtedness, and how debt is managed in the same

measure. It is calculated by dividing Interest paid by

Private Non-financial Companies at current prices (ONS

code: ROCG) by their Gross Operating Surplus at current

prices (ONS code: CAER).

Tax payments relative to profits are also controlled by

calculating the ratio of current tax payments of Private

Non-financial Companies (ONS code: RPLA) to their

Gross Operating Surplus at current prices (ONS code:

CAER).

Exchange rates are also cited as a possible determinant of

company failure. Sterling Effective Exchange Rate Index

(ONS code: BK67) is used to control such an effect.

Labour conditions are cited as being related to closures and

controlled by a proxy of employment rate (%, age 16-

59/64) in this study (ONS code: MGSU).



It is also suggested that property prices may influence

insolvency rates since properties are mainly used for

collateral. Besides, the changes in such prices may also

affect the liquidation value of a company. Hence, property

prices are also controlled in the model with a proxy of real

house price index (deflated by GDP deflator) (ONS code:

WMPQ).

Share values are also controlled since they may show a

company’s worth and affect the liquidation value of a

company. The proxy used is Price Index of FTSE industry

sector, non-financials (ONS code: HSER).

It is widely suggested that new companies are more likely

to fail than the old mature ones. Such an effect is

controlled by company birth rate, which is represented by

the growth in active registered companies (Source:

Companies House).

Business confidence is also controlled as it may affect both

borrowers’ and creditors’ decisions. The data is gathered

from OECD as Business Confidence Indicator:

Manufacturing for the UK.

The factors affecting the business failure rate in the long-

term and in terms of short-term dynamics were modelled

using the final data selection tabled opposite.

Table 3.2 – Variables used to Forecast Insolvencies

(Source: CMRC)

The results of the analysis were as expected. That is, in the

long term insolvency rate increases when income gearing

or real CCJ values increase, and when the employment rate

or real money stock decrease.

The Growth in Real Short Term Loans and Business

Confidence are the short-run dynamics of the insolvency

rate. That is, whereas short term increases in the growth in

real short term loans are likely to create short term

increases in the insolvency rate, short term increases in

business confidence are likely to create short term

decreases in the insolvency rate.

VARIABLE DESCRIPTION 1-Insolvency Rate No.of Insolvencies/

No.of registered Companies

2-Company Birth Rate Growth rate of the number of registered

companies

3-Growth in Short Term Loans

4-Growth in Short Term Bank

Loans

5-Capital Gearing Total Debt/Total Assets

6-Income Gearing Interest Payments/

Operating Profit

7-Growth in Operating Profit

8-Inflation Calculated from

GDP Deflator

9-GDP Growth Quarterly

10-Exchange Rate Index Sterling Effective Exchange Rate index

11-Nominal Interest Rate London Clearing Banks’ Base Rate

12-Real Interest Rate Deflated by GDP deflator

13-Real House Price Index Deflated by GDP deflator

14-Employment Rate Between age 16-59/64

15-Business Confidence

Indicator

Manufacturing

16-Real Money Stock (M4) Deflated by GDP deflator

17-Real CCJ Value (total) Deflated by GDP deflator

18-CCJ Count Number of CCJs

in a quarter

19-Real CCJ Value/CCJ Count Ratio



The relatively high levels of indebtedness in the corporate

sector coupled with recent interest rate increases and a

decline in business confidence suggest that corporate

insolvencies are set to increase in the next 2 years.

3.3. Commercial Lending

Since 1996, the total lending to the non-financial sector, in

the form of loans by the banks and building societies, has

increased by over 75%. The figures include all lending to

PLC's, limited companies and partnerships.

There was some slow down in this form of lending towards

the end of 2000 and early 2001 but the total lending has

increased 23% in the last 5 years.

Lending to non-financial companies rose by £13.3 billion

in the last year to 2005(Q4) with real estate taking a large

share of this total.

Statistics provided by the Bank of England (January 2006)

show a sharp increase in lending growth since 2004(Q2)

compared to deposits from non-financial corporations (see

charts below).

1996 1997 1998 1999 2000 2005 Outstanding Lending at year end (£m) 160,744 178,928 189,260 201,797 228,686 281,606 % change - 11.3% 5.8% 6.6% 13.3% 23.1%

Table 3.3.1 – Bank and Building Society Lending to Industrial and

Commercial Companies 1996-2006 (Source: Bank of England)

Chart 3.3.1 – Contributions to Annual Growth Rate from Non Financial

Corporations (Source: Bank of England)



Asset finance in the form of HP and Leasing remains an

important source of funding and particularly for SME’s.

Data from the Finance and Leasing Association shows that

total new finance to fund capital investment totalled over

£2.3 billion by June 2005 and that growth in the financing

of investment goods outperformed motor vehicle leasing.

There has been some growth in HP and Leasing to the

SME sector, predominantly to firms in the £1-5 million

turnover.

Recent theories of corporate finance have emphasised the

importance attached to internally generated finance and

managerial preferences for internal over external sources of

finance in certain situations, particularly when managers or

owner-managers are better informed about the firm's future

prospects than can be 'costlessly' conveyed to external

lenders (i.e. the problem of 'asymmetric information'). The

'pecking order hypothesis' (POH) of financial structure, for

instance, suggests that firms will finance projects by first

using internal resources, then debt finance and, as a final

resort, equity. This theory has been empirically verified for

large firms. For smaller and growing firms, the POH may

be particularly relevant when informational asymmetries

are likely to be more acute and potential debt providers

may seek premium interest rates and high levels of

collateral on loans.

The POH theory predicts that smaller firms are likely to

rely to a greater extent on trade credit and short-term bank

finance to support their operations and have a preference

for 'asset-based' finance over external debt and equity.

Chart 3.3.2 – New Leasing and HP Business Finance

by Client Size and Business Investment

(Source: FLA and ONS)

Recent surveys (e.g. Bank of England Surveys of 'Finance

for Smaller Firms') have suggested that 'asset-based'

finance accounts for an increasing proportion of external

finance for the smaller company sector. Leasing and hire

purchase, factoring trade debt, invoice discounting and

pledging trade debtors as collateral for bank finance are all

growing forms of asset-based finance.

The Bank of England study ‘Finance for Small Firms –

Eleventh Report’ suggests that external bank finance for

SMEs is important but not dominant. Leasing and HP has

grown in importance. Operating leases and hire purchase

are common forms of asset-based finance utilised by the

smaller company sector - an important means of spreading

the purchase costs of an asset over the asset's lifespan.

Research has estimated that hire purchase and leasing

account for over 30% of all external finance utilised by

small firms. Factoring and invoice discounting has grown

quite considerably over recent years, albeit from a small

base as discussed below.



The chart below shows the proportions of overdraft relative

to fixed term lending in the SME sector.

The Bank of England and BAA in their analysis of lending

and deposits to and from the SME sector recently tightened

up their definition of a small firm.

Consequently, data prior to 2002 (Q4) is calculated on a

slightly different basis to more recent figures. Nonetheless

the data shown below reveals that the structure of bank

lending to SMEs has shifted markedly away from overdraft

to more fixed term lending.

Chart 3.3.3 – Small Business Borrowing and Deposits at Year End (£ Billions)

(Source: BBA and Bank of England)

Chart 3.3.4 – Changes in Sources of External Finance for SME’s

(Source: ESRC Centre of Business Research)



The ESRC Centre for Business Research produce surveys

which illustrate the decline in the proportion of finance

accounted for by traditional bank borrowing and the

growth of the use of leasing and factoring.

Thus in recent years, fixed term loans have replaced

overdrafts as the main source of bank lending for small

businesses. There appears to have been a shift away from

an over-reliance on overdraft and short- term finance to a

more structured approach in addressing capital

requirements. This should have an impact on the late

payment of commercial debt that is often precipitated by

firms juggling short-term finance when they are

undercapitalised.

A recent study by the Bank of England2

shows a sharp,

and to some extent inexplicable rise in the level of capital

gearing in the UK (large) corporate sector. Capital gearing

remains at a historically high level which, some

commentators believe, is a symptom of a fragile economy.

The measures of capital gearing are indebtedness to market

value and indebtedness to capital stock replacement costs

ratios.

The chart below shows the trend increase in these ratios,

particularly since the late 1980s.

2 The determinants of UK Corporate Capital Structure (2005)





More recent data derived from an analysis of UK Company

accounts suggests that the ratio of total debts to total assets

has risen quite sharply since 2004.

When we also analyse rations reflecting the ability of firms

to cover their debt interest repayments, we observe a

similar rise since 2004. This suggests that there are a large

number of companies that are not generating sufficient

profit to cover their interest payments. The considerable

growth in private equity backed leveraged buyouts has

increased the role of debt in capital structures. It is

estimated that value of investments LBOs in 2007 was

around £22 bn.

Chart 3.3.6 –Capital Gearing/Total Debt/Total Assets


Chart 3.3.7 –Income Gearing/Operating Profit


Capital Gearing(Total Debt/Total Assets)

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3.4 Trade Credit

Trade credit involves supplying goods and services on a

deferred payment basis that is, giving the customer time to

pay. The vast bulk of inter-firm sales are made on credit

terms. Trade credit is a particularly important source of

funding for smaller companies; the stocks and flows of

trade credit are typically twice the size of those for bank

credit. In the UK corporate sector it is estimated that more

than 80% of daily business-to-business transactions are on

credit terms. This form of financing, trade credit, is the

most important and largest form of short-term financing for

the corporate sector. The amount of credit extended by a

business to its customers (and not yet recovered) appears as

a current asset ('trade debtors') on the balance sheet and is

therefore a component of net working capital. The amount

of credit received by a business from its suppliers (and not

yet paid back) appears as a current liability (trade creditors)

on the balance sheet.

These two components represent a substantial market for

debt collection services. Indeed, trade debtors are one of

the main assets on most corporate balance sheets,

representing up to 30-35% of total assets, on average, for

all companies.

The chart compiled from a sample of 100,000

manufacturing companies over 2 decades illustrates the

relative importance of trade debtors as an asset on the

balance sheet. The share of total assets, on average, is in

the region of 30-35% of total assets over the time period.

This contrasts with stocks (inventories) which over time

have fallen as a proportion of total and current assets as

firms have become more efficient in the management of

inventories.

All UK Manufacturing 1977-2004N=100,000 approx.

0

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20

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50

60

70

1977

1979

1981

1983

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1987

1989

1991

1993

1995

1997

1999

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2003

Time Period

Per

cent

age

Trade Debtors/Total Assets Trade Debtors/Current AssetsStocks/Total Assets Stocks/Current Assets

Chart 3.3.8 – The Importance of Trade Debtors to the Balance Sheet




An important aspect of trade credit, however, is the two-

way nature of the transaction. Many companies,

particularly those at intermediate points in the value chain,

both use trade credit as customers and provide it as

suppliers. The debtor (DSO) and creditor days figures

(DPO) were calculated over the same time period as above.

The DSO figures which can be seen in the chart to the right

are in the region of 60-70 days for manufacturing firms and

DPO are in the region of 50-60 days. These aggregates,

however, disguise some wide variations when analysed by

sector and company size. Moreover, for individual firms

the net trade credit position is of more importance.

Managing the net trade credit position is critical. The

CMRC Quarterly survey of businesses tracks the net trade

credit position of respondents. The average net trade credit

position of companies can be seen to the right throughout

the life of the survey. A positive value indicates that firms

are extending more credit than is being received whereas

negative figures suggest the company is receiving more

credit than it is extending. Essentially, the Net Credit Days

figure is the difference between Debtor Days (DSO) and

Creditor Days. There was a significant rise in the Net

Credit Days figure during 2005. A survey in the UK (FPB,

1994) estimated that there was £10 billion (ECU 14.8 bn)

net late trade credit owed to small businesses.

Trade credit can involve a 'one-off' sale on invoice to a

customer to be paid say, in thirty days from receipt of the

goods. In the case of repeat purchasers however, the

supplier may open and manage a customers 'credit

account', whereby the buyer may order goods up to an

agreed limit (the credit limit) and pay funds into the

account according to agreed payment terms.

Companies engaged in exporting their goods or services

across national boundaries may supply them on a deferred

payment basis (i.e. trade credit) but make extra provisions

to finance export trade and/or take additional steps to

'secure' future payments (i.e. 'export-credit').

All UK Manufacturing 1982-2004

0

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Time Period

Perc

enta

ge

Debtor Days Creditor Days

Chart 3.3.9 – DSO and Creditor Days Trends (1982-2004)


Chart 3.3.10 – Net Trade Credit Trends




For small firms, supplying trade credit can be an important

strategic or competitive tool that plays a role in capturing

new business, in building supplier-customer relationships,

in signalling product quality, 'reputation' and financial

health and in price competition and price discrimination.

Yet, for many firms supplying and financing trade credit,

and managing trade debt, can cause cash-flow/financing

difficulties. Trade credit contracts are by their nature

incomplete and often established between supplier and

buyers with asymmetric bargaining positions. Indeed,

enforcing credit terms can be a problem, particularly for

smaller firms. The late payment of commercial debt has

often been cited as a factor that precipitates financial

distress and/or constrains growth amongst smaller firms.

Small firms can be particularly vulnerable to bad debts,

because they tend to have a smaller customer base than

their larger counterparts.

Trade credit as a form of short-term financing is not

costless. The cost of trade credit however, as compared to

other forms of financing (i.e. bank credit, factoring, etc) are

quite difficult to ascertain. The duration and implicit costs

of trade credit loans vary across firms and industries.

Moreover, as we will show later, customers often violate

the stated terms in practice. This obviously creates a debt

collection problem.

3.4.1. Credit Terms and Credit Management Practice

Credit terms refer to the written or stated policies given to

a customer with regard to: the timing of payments;

discounts for early settlements; the methods of payment;

ownership of goods prior to payment (e.g. retention of title

to the goods or other types of security); and (if applicable)

interest or penalties for late payment. The terms of

payment on business-to-business sales can take many

forms and a wide variety of possible payment terms can be

offered. Cash on or before delivery (COD, CBD) obviously

does not involve trade credit. Progress or 'stage payment'

terms usually involve an up-front deposit or down payment

with the outstanding invoice value being spread in

payments over a set period or at specific points in the

fulfilment of a supply contract. The majority of trade credit

sales however, are offered on a net period or a net period

with cash discount for early settlement.

Net terms involve the setting of a period after which

payment should be made in full. This is usually defined

either as a number of days after the invoice date or a

number of days after the end of the month in which the

invoice is issued (e.g. 30 days EOM, meaning thirty days

from the next month end). The use of EOM terms

obviously has a substantial impact on the actual credit

period; if sales are evenly spread through the month 30

days EOM will lead to an average credit period of

approximately 45 days. With two-part terms the supplier

specifies a net period, as with net terms, but also specifies a

shorter period (the discount period) during which payment

will attract a discount. Terms of 2/10 Net 30, for example,

mean a buyer can obtain a 2% discount by paying in 10

days or less, otherwise payment of the undiscounted price

is required in 30 days. Although the percentage discount

offered might often seem small, it is equivalent to a high

annual rate of interest being charged for the additional

extension of credit to net terms. Variations on this concept

also exist, for example, the payment of a rebate to

customers who pay in full by the discount date. This latter

variation protects the seller from the buyer taking unearned

discounts opportunistically.



Predominantly, the payment period specified, in the UK, is

30 days (net 30 or 30 EOM) but can vary from less than 7

days (near cash) to over 120 days. Typically, credit periods

offered on export contracts are slightly longer than those

for domestic sales, but this varies according to the

destination country, the industry sector, the characteristics

of the buyer and the nature of the product/service involved.

Credit terms and payment behaviour varies within the EU

Member States. In general, Northern/Scandinavian

countries trade on shorter credit periods and pay promptly,

whilst some Southern European countries have long

periods and long delays. Intrum Justitia’s Business Survey

suggests that Portugal, Spain and Italy have the longest

payment periods and Finland, Denmark, Sweden, Austria

and Germany have the shortest. The European Commission

have estimated, based on the FPB estimates, that the total

amount of net (late) trade credit owing to EU businesses

could be in the region of ECU 90 billion at any point in

time. The sectors which are frequently cited as being 'bad

payers' are construction, transport, retail and wholesale,

primary industries and the public sector.

3.4.2. Motives for the Supply of and

Demand for Trade Credit

It is clear, however, from CMRC survey evidence that the

motives individual firms have for extending trade credit to

customers (supply-side) are complex and manifold.

The market for debt collection services is to some extent a

function of the supply of and demand for trade credit and

the factors that affect the level and flows of trade credit in

the corporate sector. This section provides a brief review of

the motivations for extending trade credit (supply-side) and

the factors determining the usage of trade credit (demand-

side) and the implications for the credit management

process.

Trade Credit Extension and Credit Terms: The Supply-Side

Motivation

This section provides a brief overview of the main motives

that (non-financial) firms have for extending credit. In

particular, we examine the motivations for extending credit

from a 'strategic' or 'competitive' perspective.

Firms add value by creating and sustaining competitive

advantages. The seminal work by Michael Porter suggested

that competitive advantages emanate from strategies of

either cost-leadership or differentiation that may or may

not be focused on a well-defined market segment. Others

develop more complex models which suggest that

competitive advantages are established through innovating

products and processes (including information systems);

building and reinforcing relationships with customers and

suppliers (external and internal to the firm); establishing

and maintaining a reputation; and by having 'strategic

assets,' i.e. market dominance or position. One could argue

that the extension of trade credit is an increasingly

important element of corporate strategy and a potential

source of competitive advantage. Offering and managing

credit can be a key element in developing a strategy which

can both create and sustain competitive advantage. In the

context of the Porter model it can clearly play a subtle or

overt role in price competition and can be an engine for

driving differentiation strategies.



Of course, firms will vary in the extent to which they use

credit pro-actively in this way. Some organisations credit

policy is closely aligned to the sales and marketing

function, whereas in some it is seen as a subsidiary

function to the finance department. In still, others it is seen

forming a vitally important loop between the two. For

instance, suppliers may use trade credit as a means of

competing in markets and generating sales and customer

loyalty. Trade credit as a competitive tool is many faceted

and can be used to respond to customers' sensitivities to

total effective price (goods plus finance); their needs or

demand for short-term finance; their focus on product

quality and after-sales service; and their requirements for

continuity and reliability in the timing and quality of

supplies. The table summarises the way in which trade

credit can provide an important component of business

strategy. None of which, of course, are mutually exclusive

and some of which will depend on the extent of the firm's

market power or 'strategic assets'. The nature and way in

which credit can be used as a tool for gaining competitive

advantages and reducing demand uncertainties will depend

on the competitive structure of the markets facing the

supplier and the customer, their relative bargaining

strengths and the conditions affecting the supply of

alternative sources of corporate finance.

Trade credit extension could be viewed as an important

means of managing 'relationships' with customers, e.g.

generating repeat purchase behaviour, establishing

reputation and building stable and long-term relationships

with customers (i.e. good-will and a future income stream,

and of generating market or customer information). As

discussed above, potential buyers of a product may require

an 'inspection period' in order to ascertain product quality.

In the same way sellers may wish to differentiate their

offering to the market by extending credit as a signal or

'pledge' of product quality.

Table 3.4.2.1 – Motivations for Trade Credit

Extension (Source: CMRC)

Strategy Impact

Market Signalling

and Differentiation

Credit acts as an implicit guarantee of

product quality. Available credit terms

provide a ‘quality signal’ to potential buyers.

Offering credit may be a key factor that

differentiates one supplier among

competing suppliers.

Customer Loyalty

& Information

Trade credit can be used to ‘tie-in’

customers and encourage repeat purchase

i.e. ‘building relationships’. Extending credit

generates potentially useful information on

customers.

Price

Discrimination &

Price Competition

Offering credit terms provides more

opportunities for varying effective price to

buyers with different elasticities of demand

or different credit risk. Credit terms can be

an important element of price competition

and the ‘marketing-mix’ in competitive

markets.

Cost Leadership

Offering a package of both product and

finance that is cheaper than a buyer

negotiating with two parties (supplier &

financier) may generate profitable sales. The

supplier may generate profit from both

activities - profit margin on the product;

(premium) interest on the finance.

Managing

Uncertainties

Using and extending trade credit can be

used to reduce the uncertainties in trading

relationships and minimise ‘transactions

costs’. It can therefore help the firm develop

an environment conducive to innovation.



Manipulation of standard credit terms through informal

deals is one way in which the extension of trade credit can

be used for marketing purposes and for price

discrimination between customers (e.g. to compensate for

different risks). The presence of such deals to any

significant extent in a market means that the actual price of

trade credit in a particular circumstance can be difficult or

impossible for a third party to determine (or for a potential

customer to determine prior to negotiation). The CMRC

found, for example, that over 30% of firms said they were

likely to vary credit terms to attract new large customers or

promote slow moving products and over 20% were likely

to do so to retain existing customers. Such deals may even

include effectively allowing a customer to pay late or

allowing a customer to obtain discount without paying

early. The willingness of companies to vary terms suggests

that a standard assumption that credit terms are standard in

an industry and perhaps over time must now be

reconsidered in such an environment. Evidence suggesting

that firms are using trade credit terms more pro-actively

and flexibly has implications for the debt collection

industry, which, in the past, has had a poor image in terms

of managing 'customer relationships'.

Extending credit to customers who themselves face highly

competitive product markets can be a useful means of

winning business. Such firms are likely to attach a greater

weight to the availability of credit when choosing amongst

competing suppliers. Indeed these are likely to be the firms

that have difficulty raising institutional credit and/or are

credit rationed by the banking sector. This, however, is

clearly not without risk since credit rationed firms are also

more likely to default or pay late.

The supplier may well be able to offer products with trade

credit and pass on the cost of credit to the buyer. Some

firms will add a premium onto product price in order to

cover the costs of extending credit or to discriminate

between different classes of risk in the customer base.

Others may offer credit at a loss to illiquid buyers but

offset this against a surplus from cash buyers. There may

be other situations where the firm will wish to trade-off the

short-term profitability of individual customers with the

increased volume of sales or market share and, of course,

the potential for generating repeat purchase behaviour and

market or customer information.

Trade credit extension may be used to smooth the pattern

of customer demand over the business cycle or seasonally.

For instance, trade creditors may relax credit terms in order

to stimulate demand in lean periods and recover the costs

of this policy in more buoyant times. Thus, although trade

credit is short-term finance for the recipient, as far as the

supplier is concerned it may be used as part of a long-term

strategy of managing the customer-base. Consequently, the

supplier may be prepared to extend trade credit at a short-

term loss (or cross-subsidised by cash payers) for the

benefits of a long-term relationship and future income

stream. Whereas the seller may regard the bundling of

products and finance from a marketing/relationship point

of view, the buyer may value the financing element.

Finally, in the context of financial markets suppliers may

have cost-savings vis-à-vis institutional lenders both in

assessing credit worthiness initially, and in monitoring it

on-going basis. Some of these cost savings arise from

industry knowledge and others from the contact of the

selling process and potentially from the trade credit

transaction itself. A supplier may also get more collateral

value, in the event of default, from goods sold on credit

than would a third party (e.g. a bank). Offering products

and finance (trade credit) can thus be part of a strategy of



cost leadership. In such cases, the cost of obtaining both

merchandise and credit from a single firm can be lower

than purchasing them through separate transactions. The

provider may be able to generate profit from both the sale

of the product and from the provision of finance.

3.4.3 Credit Management: The Impact on Corporate Performance

Companies extending and managing trade credit should

establish a credit policy which provides the framework for

making consistent and well-informed credit decisions

which are compatible with the company's strategic

objectives and the goals of the credit function. The credit

policy is a document that specifies the course of action for

granting credit and for recurring credit activities.

Obviously, the credit policy has to be understood by and

communicated to all relevant parties, particularly credit

staff, sales staff and customers.

Credit policies need to be reviewed and monitored on a

regular basis. A carefully documented credit policy is a

fundamental requirement of sound credit management

practice, and should serve at least the following purpose:

• To define the objectives of credit extension in the

context of corporate strategy and organisation

structure;

• To define the authority and responsibilities for

credit granting, establishing and varying terms

and the timing of collection actions;

• To provide documented procedures in relation to

the above that can be communicated to all staff;

• To specify training policy for credit staff;

• To specify performance targets and monitoring

activities for credit staff.

Most large companies will have a documented credit

policy, but many medium-sized and smaller companies

lamentably neglect this aspect of their business. A CMRC

survey in 1995 revealed that only 35% of manufacturing

companies and less than 20% of small companies had a

written credit policy. Over 30% of firms extending credit

did not agree credit terms in writing prior to the sale. More

recent research by CMRC, suggests that credit

management practice, SME financing and banking

relationships and perceptions of the late payment problem

have all improved significantly in the period 1995-2000.

The credit policy of a company should be developed in

accord with the strategic, marketing, financial and

organisational context of the business and be designed to

contribute to the achievement of corporate objectives. The

corporate strategy can include trade credit management,

not just in terms of its contribution to collection and cash

flow, but as a means of generating sales and profits, and of

investing in customers by building relationships.

The management of trade credit can help build stable and

long term relationships with customers, generate

information about the customer and their requirements and

facilitate different customer strategies in terms of credit

granting, credit terms and customer service. The objective

is to generate growing, but profitable sales. Managing

collections lowers cash-flow risks and helps to ensure that

cash is available for investment opportunities. The

objective is to collect in accordance with credit terms,

minimise collection costs and reduce the need for finance

whilst responding quickly to customer queries and/or



disputes. Managing the total investment in debtors and

‘money at risk’ has a direct impact on profitability and the

ability of firms to raise external funds. Measuring,

monitoring and minimising credit risk is an important

activity for credit management. Minimising bad debt in the

context of the risk-return decision has a direct impact on

profitability.

The decision of the extent to which the firm uses the

services of external agents such as credit reference agents,

credit insurance, factoring, invoice discounting and debt

collection/recovery services is a strategic issue and will

have a bearing on overall performance. The use of credit

insurance can impact on credit management practice and,

in turn, on corporate performance in a number of ways.

Firstly, credit insurance protects cash-flow against

protracted default and protects profits from the risk of bad

debt. Credit insurance, however, imposes a discipline on

the credit management activities of the firm. Thus, sales on

credit have to be agreed formally between the two parties

along with payment dates.

The credit grantor has to monitor payment times in order to

inform the insurer of any overdue and comply with the

terms of the policy. In effect this improves the collection

time on all trade debt and impacts on cash-flow as well as

allowing the firm to analyse individual customer payment

histories. The credit insurer will credit vet all the firm’s

customers, provide the firm with advice on credit limits

and provide early warnings of customers in financial

difficulty. This information may be useful for marketing

decisions and customer relationship management as well as

with credit decisions. Having trade debtors insured may

facilitate the raising of finance from the banking sector and

foster better banking relationships. In turn, a credit insured

company is a better risk from the perspective of current

and potential suppliers since they will be protected against

the ‘knock-on’ effects of bad debt.

In previous research by CMRC, it was possible to

demonstrate that relatively simple credit management

practice could have significant effects and certainly give

the firm an edge over its competitors. For instance, in the

sample as a whole only 20% of companies had a written

credit policy and over 50% did not agree credit terms in

writing prior to a sale. Few used credit reference

information or credit insurance - a substantial number were

extending credit to bad risks. However, those companies

that were devoting more time to ‘front-end’ credit

management (i.e. checking creditworthiness of

customers; negotiating and agreeing terms in writing and

monitoring credit limits) had: a greater proportion of

accounts paid on time, lower levels of bad debts, lower

average debtor days (controlling for credit periods), and

perceived less of a late payment problem.

Of course, firms will vary in the extent to which they use

credit pro-actively in this way. Some organisation’s credit

policy is closely aligned to the sales and marketing

function, whereas, in some it is seen as a subsidiary

function to the finance department. In still others, it is seen

a forming a vitally important loop between the two. For

instance, suppliers may use trade credit as a means of

competing in markets and generating sales and customer

loyalty. Trade credit as a competitive tool is multi-faceted

and can be used to respond to customers’ sensitivities to

total effective price (goods plus finance); their needs or

demand for short-term finance; their focus on product

quality and after-sales service; and their requirements for

continuity and reliability in the timing and quality of

supplies. The nature and way in which credit can be used



as a tool for gaining competitive advantages and reducing

demand uncertainties will depend on the competitive

structure of the markets facing the supplier and the

customer, their relative bargaining strengths and the

conditions affecting the supply of alternative sources of

corporate finance.

The strategy map below summarises the routes by which

good credit management practice can impact on a

companies overall performance, i.e. profitability, growth,

shareholder value.

3.4.4 The Use of Trade Credit and Payment Behaviour: The Demand Side Motivation

Understanding how customers, 'buyers', might behave in

respect on their usage of trade credit (their demand for

trade credit), their payment behaviours and the likelihood

of protracted default and/or insolvency is an important

aspect of the credit manager's role and may, in turn, affect

their decision to insure the risks of trade debt. This section

focuses on the factors affecting the demand for trade credit.

CREATESHAREHOLDER VALUE

Financial Perspective

CORPORATE STRATEGY

FINANCIAL STRATEGY MARKETING STRATEGY

CREDIT STRATEGY

OPTIMISECASH CONVERSION

GROW REVENUEMAXIMISE CUSTOMER VALUE

MAXIMISE INVESTMENTIN CUSTOMERS/ MINIMISE

‘MONEY AT RISK’

RISK-RETURN

OPERATIONAL

ORGANISATION

Customer Perspective

CREDIT MANAGEMENT

CREDIT GRANTING RISK MANAGEMENT CREDIT CONTROL

- CUSTOMER PRODUCT DEMAND- CUSTOMER CREDIT DEMAND-TAILORED PRODUCT/CREDIT PACKAGE - MAXIMISE CUSTOMER PROFITABILITY- SERVICE QUALITY/FLEXIBLE TERMS- GENERATE NEW/REPEAT BUSINESS- PRODUCT LIFE-CYCLE MANAGEMENT- CUSTOMER LIFE-CYCLE MANAGEMENT

INFORMATION GENERATIONCUSTOMER AND MARKET KNOWLEDGE

IN-HOUSE ACTIVITIESOUT-SOURCED ACTIVITIES

Collection Strategy

Collection Periods/CostsNet Trade Credit

Customer Relationship ManagementCustomer Portfolio Management

OBJECTIVE

- SALES/CREDIT COORDINATION - MONITOR CREDIT LIMITS - INVOICE EFFICIENCY/PAYMENT OPTIONS- DISPUTE RESOLUTION- PRO-ACTIVE COLLECTION/CRM- MINIMISE OVERDUES/CREDIT NOTES- MAXIMISE CUSTOMER SATISFACTION

- CREDIT INFORMATION- RISK MEASUREMENT- DEFAULT PROBABILTIY- COLLATERAL/GUARANTEES- ‘MONEY AT RISK’/ FINANCING- RISK TRANSFER (BUYER)- RISK TRANSFER (INSURER)

Minimise DelinquencyMinimise Bad Debt Losses

-New customers-Customer Retention

- Customer Profitability

Cost Effective Credit Management- CREDIT REFERENCE DATA/RISK SCORES- DEBT RECOVERY/LITIGATION- CREDIT INSURANCE- FACTORING/INVOICE DISCOUNTING

- CUSTOMER KNOWLEDGE- CREDIT GRANTING/POLICY/CRM- SALES ADMINISTRATION- COLLECTIONS- FINANCING/ RISK PROVISIONS

COST-BENEFIT

SHORT-LONGTERM

Chart 3.4.4.1 – The Use of Trade Credit and Payment Behaviour – A Strategy Map

(Source: CMRC)



It was suggested above that a buyer may wish to purchase

on trade credit in order to protect against forms of seller

non-compliance e.g. delivering goods of poor quality or

not fully complying with the terms of sale. Moreover a

firm may have no real preference for trade credit over other

forms of finance but accept trade credit as but one element

of the supplier's total 'marketing bundle' (of goods + credit

+ after-sales service etc.). The most likely motivation for

using trade credit is however, to satisfy a financing demand

(financing theory) and/or to minimise transactions costs

(transactions cost theory).

As we have discussed above trade credit, to the recipient, is

primarily a form of short-term financing. If we consider

trade credit as one of several options for financing

purchases, then the attractions of trade credit will depend

on the relative costs and availability of other options. If

credit market imperfections cause some buyers to have

unsatisfied demand for finance, i.e. to experience credit

rationing, then they will be willing to use trade credit even

at a premium cost. Academic studies of trade credit

demand provide some support for this notion. If, on the

other hand, firms are cash rich then trade credit must be

compared with the opportunity cost of other uses of the

money. Possibilities for credit rationing arise where lenders

are not able to set an appropriate rate for each loan

applicant based on the riskiness of the loan. This situation

may arise because of imperfect information; where a lender

is unwilling, due perhaps to economic viability, or unable

to obtain sufficient information on the borrowers

creditworthiness or the risk-return profile of the project for

which the loan is being raised. If a lender is asymmetrically

informed compared to the borrower, they are exposed to

the problems of adverse selection and moral hazard.

Alternatively, the ability of the lender to set an appropriate

rate may be restrained by usuary laws, the way such action

is viewed by the customer base, or the potential impact on

public perceptions of the lender.

If credit rationing exists in a market (e.g. amongst small

growing businesses) then trade credit can be an attractive

way of obtaining finance even if the costs are high due to

foregone discounts or late payment penalties.

This motivation for trade credit demand would imply that

firms who are higher credit risks would have a higher

demand for trade credit, including that at premium cost,

and would be more likely to display behaviours such as

late payment, which are effectively breaches of the terms

of sale. Suppliers may be willing to finance such customers

because the firms have more in common than the financial

transaction; the supplier benefits in the longer term by

helping a customer in temporary difficulty to stay in

business and therefore making future sales. The supplier is

also in a potentially better position to ascertain the

probability of default, than an institutional lender if the

relationship is long term or the selling process facilitates

the collection of credit information. In the event of default

the supplier may be able to obtain greater value from the

goods if they are repossessed than would a third party. The

supplier's credit management department may also be in a

better position to monitor customers on an ongoing basis.

Moreover, suppliers can also use two part terms to obtain

ongoing information on credit worthiness; buyers who fail

to take early payment discount may be signalling financial

difficulty. Finally, the differences between the market

borrowing and market lending rates of interest provide a

financial incentive for suppliers to engage in arbitrage,

using surplus funds to finance customer purchases, rather

than earning interest on the market.



Even if a firm is not subject to credit rationing, trade credit

may be an economic option compared to other finance

because suppliers are in a position to save on information

costs in assessing a buyer's creditworthiness and in

collection and monitoring costs, particularly with regular

customers. The relative price of trade credit may therefore

be favourable. We might then expect that firms who have

long-term relationships with suppliers might use more

trade credit, and might obtain more favourable terms.

The lack of the fixed costs associated with arranging a loan

or line of credit and the administrative costs to the

borrower may also make trade credit more attractive.

Another factor which may make trade credit a more

attractive option financially is the motivation of the

supplier in extending it; although making a profit from the

credit side of the transaction is a potential motivation, it is

not necessarily the major determining factor - the suppliers

main business is usually the goods being sold. Alternatives

to the profit motive for credit extension are unlikely for

financial institutions, where the credit transaction is

primary business. The CMRC surveys support this notion,

suppliers indicated that they offered credit as a necessary

part of marketing their products and did not think of trade

credit as a potential substitute for bank credit when credit

terms are requested by a customer.

Transactions costs theory emphasises trade credit's

intermediary role in removing a requirement for

simultaneous action by both parties in a trade transaction,

(i.e. simultaneous exchange of money for goods and

services). Trade credit can be seen as a way of reducing the

transaction costs involved in trade exchange. A main issue

is the cost of making money available. To do this, firms

have to convert liquid assets into cash; there are costs to

doing this that may be greater if conversion is frequent

and/or for small amounts, consequently firms have a

demand for precautionary cash balances. Trade credit

reduces the need for this, particularly where there is

uncertainty in the trade exchange. For example, supplier

relationships are important; a firm facing variable and

uncertain delivery schedules with no trade credit available

has to take the risk of a delivery arriving when it does not

have available cash (and therefore incurs implicit or

explicit penalties). This risk level will, of course, influence

the size of the firms precautionary cash balance. Trade

credit gives a buyer notice of when cash is needed for

payments and thus allows them to keep reduced

precautionary balances and to plan movements from liquid

assets to cash in the most cost effective manner; this is

therefore a motive for buyers to use trade credit and we

might expect that uncertain delivery schedules would be

associated with more use of trade credit.

The above argument in fact gives rise to two motives; the

buyer can plan the management of cash versus liquid assets

more effectively optimising returns on assets (the cash

management motive), but the buyer will also potentially

reduce the number of transactions on their current bank

account (because one cheque may be able to pay many

invoices) thereby reducing banking costs (as most banks

charge businesses on a per transaction basis); we refer to

this as the transaction volume motive. The ability to group

invoices for payment at predicted dates in the future may

also make it easier for firms to organise payment by credit

transfer, which would again reduce bank charges as such

transactions usually have a lower fee compared with, for

example, cheques.

The businesses purchasing and delivery schedule would

affect the benefit they could potentially gain from the

transaction volume motive. If a firm requires frequent



deliveries, particularly from a large number of suppliers

then they have the most potential for gain. Obviously a

business' purchasing and delivery schedule may in turn be

influenced by the availability or otherwise of credit terms;

if a firm has a transaction charge on each individual

purchase they might seek to have fewer, larger purchases

(if their business allows), the trade off being the additional

costs of holding extra stock. We might therefore expect a

positive relationship between use of trade credit and

frequency of orders as those who require frequent orders

have most motivation to use credit.

3.5 Late Payment and Bad Debt

The relative importance of trade creditors and debtors as an

asset and liability has increased in recent years, as shown

earlier. Trade debt, however, is a risky asset as a

component of the seller’s balance sheet. Trade debtors may

generate a future cash flow but need to be financed while

waiting for this cash to be paid. The financing costs of late

payment, additional and unanticipated collection costs

and/or bad debts all impact adversely on the profitability of

credit sales and working capital requirement. Thus,

management decisions regarding credit such as assessing

credit risk, extending credit and setting limits, and

managing/monitoring the credit cycle, are of central

importance.

3.6 Late Payment Trends

However, late payment as a phenomenon is enduring. The

CMRC Quarterly Review monitors payment behaviour

across a sample of 2000 enterprises. As can be seen to the

right, sales accounts which pay at or near the due date are

currently reported at 54%. This leaves 46% of all sales

accounts being reported as overdue by our panel of

respondents.

In terms of customer accounts, the proportion of customers

paying at or near the due date is slightly lower. 46% of our

survey panel state that customers at an account level pay

on time. This equates to 54% of all customer accounts

currently being paid late.

In the CMRC survey3

, when asked about late payment,

89% of firms responding to the survey admited that they

have sometimes faced late payment from customers.

Upon further analysis, we find that one-third of firms in the

sample receive more than 80% of payments at the due date,

while only one-third of firms receive less than 60% and

11% receive less than 20% of accounts at the due date.

These findings are similar, if we consider the accounts as

percentage of customers as opposed to sales invoices.

3 Credit Strategy and Corporate Performance, CMRC 2005

All

Chart 3.6.1 – % of Accounts Paying beyond the

Due Date (Source: CMRC)

(S C C)



Smaller firms tend to have highest percentage of accounts

paid on time and the figure decrease in opposite direction

with firm size.

Firms in agriculture, hunting and forestry and hotels and

recreations tend to have higher percentage of accounts paid

on time, while firms in construction and business and

financial services have lower percentage of invoices paid

on due date.

In the manufacturing sub sector, textiles and upholstery

and transport equipment have the higher-than-average

percentage of invoices paid on time, while machinery

equipment, metal products and paper, publishing and

printing sector tend to be paid late.

Chart 3.6.2 – % of Companies Paying on Time

(Source: CMRC)

Chart 3.6.3 – % of Invoices Paid on Time – Sector

Analysis (Source: CMRC)

Chart 3.6.4 – % of Invoices Paid on Time – Sub

Sector Analysis for the Manufacturing Sector

(Source: CMRC)

0%

20%

40%

60%

80%

100%

Under 10 10 to 49 50-249 Over 250

Accounts as % of sales Accounts as % of customers

MEAN PERCENTAGE OF PAYING ON TIME - FIRM SIZE ANALYSIS

Employee size bands

Perc

enta

ge o

f firm

s

0% 20% 40% 60% 80% 100%

All sectors

Agriculture, hunting & forestry

Business and financial services

Construction

Hotels/ Recreation

Manufacturing

Retail distribution

Transport/ Communication

Wholesale distribution

Accounts as % of sales Accounts as % of customersPercentage of

responses

PERCENTAGE OF INVOICES PAID ON TIME - SECTOR ANALYSIS

0% 20% 40% 60% 80% 100%

Manufacturing

Food, beverage & tobaco

Textile & uphoistery

Paper, publishing & printing

Chemical, plastic & petroleum

Non-metalic products

Metal products

Machinery & equipment

Electrical & optical equipment

Transport equipment

Accounts as % of sales Accounts as % of customersPercentage of

responses

PERCENTAGE OF INVOICES PAID ON TIME - SUB-SECTOR ANALYSIS FOR THE MANUFACTURING SECTOR



Debtor days and payment beyond the due date show the

picture of the extent to which payments are made after or

before the due date. The following figures analyse these

indicators to reveal more about the payment behaviour of

firms in the sample. 87% of firms in the sample cite a

debtor day figure of 30-89 and the average value of the

whole sample is 45 days.

Around two-third of firms receive payment from 0 to 30

days beyond the due date

Average debtor days figure is highest in medium firms (50-

249 employees). Large firms (over 250 employees) have

lowest debtor days as well as lowest number of days of

payment beyond the due date

Firms with a turnover from £10-19.9 million have the

highest payment beyond the due date figure, but at the

same time, have the highest debtor days. Firms with a

turnover from over £50 million have lower payment

beyond the due date, and firms with turnover from £20-

49.9 million have the lowest debtor days.

Chart 3.6.5 – Average Debtor Days

#

Chart 3.6.6 – Payment Beyond Due Date

Chart 3.6.7 – Payment Beyond the Due Date

Chart 3.6.7 – Debtor Days - Size Analysis

Chart 3.6.8 – Debtor Days - Turnover Analysis

Percentage of responses

0%

20%

40%

60%

80%

100%

0 to 29 days 30 to 59 days 60 to 89 days 90+ days

AVERAGE DEBTOR DAYS

Average debtor days

Perc

enta

ge o

f firm

s


0%

20%

40%

60%

80%

100%

0 to 14 days 15 to 29 days 30 to 59 days 60+ days

PAYMENT BEYOND THE DUE DATE

Payment beyond the due date

Perc

enta

ge o

f firm

s

0

10

20

30

40

50

60

Under 10 10 to 49 50-249 Over 250

Average debtor days Average payment beyond the due date

AVERAGE DEBTOR DAYS AND AVERAGE PAYMENT BEYOND THE DUE DATE - FIRM SIZE ANALYSIS (NO. OF EMPLOYEES)

Employees size bands

Num

ber o

f day

s

0

10

20

30

40

50

60

<1 1-2.4 2.5-4.9 5-9.9 10-19.9 20-49.9 >50 £ Millions

Average debtor days Average payment beyond the due date

AVERAGE DEBTOR DAYS AND AVERAGE PAYMENT BEYOND THE DUE DATE - TURNOVER ANALYSIS

Turnover size bands

Num

ber o

f day

s



The average debtor days figure is high within firms in

transport and communication, followed by retail

distribution and some sub-manufacturing sector as paper,

publishing and printing, metal product, textile and

upholstery. To the contrary, ‘debtor days’ indicator is low

within firms in agriculture, hunting and forestry, business

and financial services, hotels with recreation and food,

beverage and tobacco sector.

The average payment beyond the due date figure is high in

transport, communication, wholesale distribution,

chemical, plastic and petroleum sector, and is low in

agriculture, hunting and forestry, retail distribution, non-

metal products, electrical and optical equipment sectors.

71% of responses indicate that their credit terms allow

them to charge interest on overdue accounts. There is

evidence for the positive correlation between the incidence

of firms having such a credit policy and firm size, implying

that large firms are more likely to have conditions of sale

that allow them to charge interest on overdue accounts.

58% of firms use the interest rate from 2% to 5%. 31%

charge a 6% to 10% interest rate on overdue accounts.

Interestingly, 12% of firms in the sample are willing to

execute this condition when it is needed (i.e. actually

charge interest on overdue accounts). However, 76% of

firms never or rarely to do so.

Around one third of firms in the sample see late payment a

serious or very serious problem for their businesses.

Chart 3.6.9 –Debtor Days – Sector Analysis

Chart 3.6.10 – Debtor Days – Sub Sector Analysis

Chart 3.6.11 –Interest Charged on Overdue Accounts

Chart 3.6.12 – % Firms Affected by Late Payment

0 10 20 30 40 50 60 70 80

All sectors



Construction

Hotels/ Recreation

Manufacturing

Retail distribution

Transport/ Communication


Debtor days Payment beyond the due date

AVERAGE DEBTOR DAYS AND AVERAGE PAYMENT BEYOND THE DUE DATE - SECTOR ANALYSIS

Number of days

0 10 20 30 40 50 60 70 80

Manufacturing

Food, beverage & tobacco

Textile & upholstery

Paper, publishing & printing



Metal products



Transport equipment

Debtor days Payment beyond the due date

AVERAGE DEBTOR DAYS AND AVERAGE PAYMENT BEYOND THE DUE DATE - SUB MANUFACTURING SECTOR ANALYSIS

Number of days

0%

20%

40%

60%

80%

100%

0-1% 2% to 5% 6% to 10% 10% +

RATE OF INTEREST CHARGED ON OVERDUE ACCOUNTS

Perc

enta

ge o

f firm

s

0%

10%

20%

30%

40%

50%

Not at allimportant

Very important

Domestic customers Overseas customers

IS LATE PAYMENT A SERIOUS PROBLEM FOR YOUR BUSINESS?

Perc

enta

ge o

f firm

s



22% of firms seriously rate the threat of bad debt from

domestic customers on their operation. Firms in the sample

obtain an average receivables volume of £1.62 million

beyond 30 days and £0.35 million beyond 90 days.

The business and financial services and transport

equipment sector have the higher than average volume of

receivables beyond 30 days, while retail/wholesale

distribution, hotels, recreation, and construction.

Most of sub-sectors in the manufacturing industry average

below 30 days. Over 90% of firms have receivables

beyond 90 days while this figure for receivables beyond 30

days is 65%.

Chart 3.6.13– Receivables Beyond 30/90 Days

Chart 3.6.14 – Accounts Beyond 30/90 Days - Sector

Chart 3.6.15 – Accounts Beyond 30/90 Days

0%

20%

40%

60%

80%

100%

0 to 100k 100k to 500k 500k to 1m 1m to 5m 5m+

30 days 90 days

RECEIVABLES BEYOND 30/ 90 DAYS

Receivables

Perc

enta

ge o

f firm

s

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

All sectors



Construction

Hotels/ Recreation

Manufacturing

Retail distribution


£m30 days 90 days

AVERAGE RECEIVABLES BEYOND 30/ 90 DAYS - SECTOR ANALYSIS

Receivables

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

Manufacturing

Food, beverage & tobacco

Textile & upholstery



Metal products



Transport equipment

£m30 days 90 days

AVERAGE RECEIVABLES BEYOND 30/ 90 DAYS - SUB MANUFACTURING SECTOR ANALYSIS

Receivables



Bad debt as percentage of turnover for the last year of

trading is recorded at 0.47% on average for the whole

sample. This level of bad debts represents £4,700 lost for

every £1 million of turnover. There are clear variations in

the amounts written off as bad debts in the sample.

Large businesses, the NHS and central government are

claimed by more than 40% of firms in the sample as slow

payers. These are followed by local government (37%);

individuals (37%), small businesses (34%) and European

commission (26%). Medium businesses appear to be the

most prompt payers, with only 24% of respondents

indicating them as slow.

Nearly half of firms (45%) conduct a formal analysis of the

reasons for late payment. Of these, 96% of record an aged

debt profile; 53% categorize customers into different risk

classe;, and 21% mark these customers on aged debt

reports.

We find that larger firms tend to have higher level of bad

debt written off. The following table presents the profile of

firms with a high level of bad debts. However, some levels

of bad debt are inevitable, but good credit management

practice involves growing profitable sales and minimising

bad debts.

Profile of firms with high level of bad debts - Large firms - Products are standardized and similar to those of other competitors - Operate in highly concentrated industries - Have higher frequency of daily order from customers - Use credit terms rather than price to promote sales

Firms with high level of bad debts appear to - Focus more on the importance of credit management to corporate

performance, especially on profit before tax - More likely to cope with corporate fraud by a documented fraud

response plan - Resort more to debt collection agents for receivables/ debt collection - More likely to use Alternative Dispute Resolution

0% 20% 40% 60% 80% 100%

Small businesses (less than 50 employees)

Medium businesses (50 to 99 employees)

Large businesses (200 to 499 employees)

Individuals

Central government

Local government

European Commission

NHS

Never Always

WHICH TYPES OF CUSTOMERS ARE SLOW PAYERS?


Table 3.6.1 – Profile of firms suffering from Bad Debt

Chart 3.6.16– Types of Customer who are Slow Payers



3.7. Impact of the Late Payment Legislation

In the UK and EU, the crux of the recent debate on the late

payment of commercial debt, and its impact on small firms,

revolved around whether legislation, or simply improved

credit management practice, was required to alleviate the

problems. Various lobbying groups put forward cases for

and against the right to statutory interest and other policy

interventions. Others stressed the need for a greater

awareness of, and training in, 'best practice' credit

management. For example, the Institute of Directors (IOD,

1993) argued that the majority of overdue debtors can be

reduced by improved credit management. However, the

Forum for Private Business (FPB), a representative of

small UK businesses, was amongst the most vociferous

advocates of government intervention to mitigate the

effects of late payment on the smaller firm sector.

The policy prescription favoured by the FPB was the

statutory imposition of interest on late payment by debtors.

It was argued that such a provision would simultaneously

bind all firms into paying promptly, create a level playing

field in payment behaviour and ease the cash flow

problems of small firms, who will be compensated for any

overdue payments (HMSO, 1998). The 'causes' of late

payment behaviour are complex and summarised in the

diagram. Dominant customers are often able to leverage

cash-flow and profits if they have a good bargaining

position vis-à-vis their suppliers or very competitive supply

chains.

dominant customersdominant customersexploit competitiveexploit competitivesupplier marketssupplier markets

poor credit andpoor credit andfinancial financial

management;management;product/serviceproduct/service

qualityquality

undercapitalised firmsundercapitalised firmscredit rationing/credit rationing/

inappropriate financeinappropriate finance

Assertions About Late PaymentAssertions About Late Payment

financial distressfinancial distressand insolvencyand insolvency

financial difficultyfinancial difficulty

inefficienciesinefficienciesimperfect competitionimperfect competition

macro/financial environmentmacro/financial environment

Chart 3.6.17– Assertions about Late Payment



Late payment is often a function of poor credit

management practices of the supplier or poor quality and

after-sales service. Firms in financial difficulty often

stretch their creditors in order to alleviate cash-flow

problems. These may be firms on the path to failure or

small and growing firms that have difficulty raising

institutional finance. The different and complex causes of

late payment behaviour suggests that policy measures

aimed at tackling late payment would have to attack the

problem in a number of ways and led to a vigorous debate.

A range of possible measures might have an impact.

Measures to tackle dominant bargaining positions of

customers; education and training in credit and financial

management and improvements in the flow of finance to

SMEs would all help as would macro-economic policies

that avoid boom and bust and consequent high levels of

business failure and financial distress.

Arguments against the statutory imposition of interest for

late payment were formulated in terms of 'contractual

freedom'; in that trade credit is often used as a competitive

tool and as a means of building trading relationships.

Suppliers may wish to retain the flexibility to vary

(informally) credit terms for specific customers, and

customers may value the freedom to negotiate payment

periods with their suppliers as financial circumstances

dictate. A further powerful argument against legislative

intervention contended that the imposition of statutory

interest might in fact, dwindle a key source of short-term

finance for the small firm sector. Small firms have been

shown to value trade credit as a source of finance for its

flexibility and freedom from formal restrictions. It is also

posited that trade credit is used widely by small firms who

are unable to obtain sufficient finance from other sources,

such as financial institutions.

competition policy – MMC, Office of Fair Tradingcodes of practice and improved information

Asymmetric Bargaining Power

Management Practice/inefficiency

education and awareness - credit and financial managementSME support services - out-placed and out-sourcedprogress - information and technological advances

Financial Markets/Banking RelationshipsFinancial Markets/Banking Relationshipsfunctioning of financial markets - financing SME’s

- growth and export financebanking relationships & efficiency

- informed decisions- specialist products

macro-economic management - smoothing the cycle- rescue culture

Possible Policy Measures ?

Chart 3.6.18– Possible Policy Measures



CMRC in an empirical study of the demand for trade credit

by small UK firms, found strong evidence of a financing

demand for trade credit. They surmised that small firms,

which pay trade credit liabilities late, appear to do so when

they reach their limit on short-term bank finance. These

'credit rationed' firms were typically growing and export

oriented. In consequence, if the imposition of statutory

interest significantly reduces the trade credit offered to

smaller firms, this may lead to severe liquidity problems

and increased failure rates unless alternative finance is

readily available.

A number of other solutions to the problem of late payment

have been put forward. For example, it has been argued

that credit management is a neglected function in many

organisations with a focus on collection rather than the

front-end activities of negotiating, risk screening, using

credit information and establishing clear credit policies.

The CMRC identified poor credit management practices as

one of the underlying causes of late payment. In addition to

poor credit management practices, causes were considered

to include over reliance on trade credit and short term

finance and consequently an increased sensitivity to late

payments. The Bank of England report on finance for

small firms (BOE, 1996) observed a similar occurrence of

ad hoc credit management that was viewed as being

inefficient. They concluded that this was due to the

inherent lack of administrative resources in the small firm

sector.

It is argued that policies that emphasise the provision of

financial and credit management training for smaller

businesses would have a beneficial impact. This may also

raise awareness of the services and potential benefits of

credit insurance and factoring and the returns to

investments in information technology. Other measures

that have been proposed or implemented include voluntary

codes of practice; a British standard for payments; the

establishment of the 'Better Payment Practice Group'; the

compulsory disclosure of payment policies in company

accounts and the streamlining of legal procedures for the

recovery of debt. In response to the above debate, and

following a period of consultation, the current government

introduced legislation (the Late Payment of Commercial

Debts (Interest) Act 1998) entitling firms to claim a

statutory right to interest on late payment of trade debts, to

be phased in over four years.

The first stage, introduced in November 1998, allows only

the smallest companies to claim interest from larger

companies and the public sector in recognition of their

vulnerability to dominant customers. Small firms had a

statutory right to interest from each other two years later,

and large firms will be able to claim interest from 2002.

In 1998, the Credit Management Research Centre was

commissioned by the Department of Trade and Industry to

monitor the proposed introduction of the Late Payment of

Commercial Debts (Interest) Act.

Referred to as the Government’s Late Payment

Observatory by Barbara Roche (Hansard 1997), the CMRC

was able to construct a panel of 1100 Credit Professionals.

It was agreed that the Observatory would also identify best

practice in credit management so that small businesses can

benchmark their own performance. The CMRC then

developed a quarterly trend database to assess the impact

of measures introduced to combat late payment and

provide an indication of changes in credit management

culture in the UK. 82% of businesses were aware of the

Late Payment Legislation in 2002.



The number of firms using the legislation has consistently

been low with figures showing it to be 5% of those eligible

(CMRC Quarterly Review, 1999, 2000, 2001, 2002).

CMRC have argued for some time that actual use of the

Legislation is not necessarily a measure of the overall

effectiveness. Relations between the payment behaviour

and patterns of payment are far more complex and this

report attempts to examine firms’ attitudes to the statutory

right to charge interest on late payments and highlights

other key indicators of late payment to provide a

comprehensive review of large and small firms in terms of

late payment in 2002. A large number of firms in the

sample (79%) are aware of the UK first phase (November

1998) and second phase (November 2000) of the late

payment legislation. But only 38% of firms actually make

their customers aware of their rights under the late payment

legislation when negotiating terms and conditions for

granting trade credit. 36% of these firms admit that being

charged interest makes them pay a debt more quickly than

otherwise would have been the case.

It seems that firms in the sample have not placed high

expectations on the effect of the Legislation on the UK

payment culture. 69% of sample firms have a neutral

opinion about this.

21% of firms see it is advantageous and around 10% show

a negative feedback: ‘the legislation/ Directive will

generate detrimental impacts on the UK payment culture in

the long term’. We find that those firms that have high

expectations about the effectiveness of the Legislation are

those that view bad debt and late payment as a serious

problem for their businesses. They tend to conduct formal

analysis of the reasons for late payment and are more likely

to apply the third phase of the legislation in charging

interest on late payments.

However, for the whole sample, firms show some

hesitation when being asked whether they would use the

third phase of the legislation to charge interest on late

payment. 57% of sample firms confirm that they would not

do it for any customer. 35% of firms do so to some

customers and only 3% apply for all customers. Not many

firms quote a specific reason for this, but a great part of the

obtained responses (20%) rely on the fact that the

relationship with customers will be damaged if they do so.

Nonetheless, if the situation worsens, 78% of sample firms

are willing to pursue late payments through the courts and

97% of them are willing to consider claiming interest for

late payment. As expected, firms that specify their rights

under the late payment legislation when negotiating terms

and condition of credit grants are more likely to pursue late

payments through the court.

Do you pursue late payment through the courts (1)

Sub-group of firms that

specify their rights

Sub-group of firms that do not specify their rights

Significant

0.87 0.73 0.011* * Significant at 5% level, (1): ‘0’ for ‘no’ and ‘1’ for ‘yes’

Table 3.6.2– % of Companies Pursuing Late Payments through the Courts



62% of firms are not willing to receive more information

about the legislation. This is reasonable as most of these

firms are aware of the UK first and second phase of the late

payment legislation.

3.8. Use of Third Parties in Credit Management

Once a firm has decided to offer trade credit, an important

decision relates to the way in which the firm chooses to

organise its credit management process.

Statistical evidence shows that firms that are not aware of

the late payment legislation are requesting more

information about how to implement it.

There is a scale of strategies from full integration of the

credit function within the organisation (i.e. vertical

integration) through to externally run credit management

(i.e. contracted out to agents).

The need for further

information of the legislation (1)

Sub-group of firms are

aware of the legislation

Sub-group of firms that are not aware of

the legislation

Significant

0.31 0.67 0.000** ** Significant at 1% level, Value for (1): ‘0’ for ‘no’ and ‘1’ for ‘yes’

CUSTOMERS

SUPPLIERS

CREDIT MANAGEMENT

AGENTS IN HOUSE

Services provided by Agents

Credit References Debt Collection

Credit Insurance Invoice Discounting

Factoring

Credit Management Functions

Credit Risk Assessment Credit Granting Decision

Sales Ledger Administration Collection of Monies Owing

Financing Accounts Receivable Bearing Credit Risk

Table 3.6.3– Awareness of the Late Payment Legislation

Chart 3 6 19 Awareness of the Late Payment Legislation



Thus, organisations may choose to manage the entire credit

administration process 'in-house'. In contrast, however,

some or all of these activities can be 'out-sourced' to

specialised institutions that perform the various credit

administration functions. There are, of course, various

institutions or agents that will provide services for credit

management: factoring companies who will take over a

company's sales ledger and collect outstanding balances on

behalf of the company (finance, collection and, in some

cases, risk-bearing); credit insurers who will insure trade

credit against bad debt risks (credit risk assessment and

risk bearing); credit reference agencies who provide

information about companies or individuals with which

people may wish to trade and, by providing credit ratings

or credit scores, advise on the risks of dealing with certain

customers (credit risk assessment); and debt recovery

agents who will recover monies owed, directly or via the

legal system (collection and recovery).

The services provided by these organisations have, in the

past, overlapped to some extent but nonetheless remained

quite distinct. However, this situation is changing quite

rapidly. Almost all organisations in credit services have at

their 'core' a large I-T investment in the collation and

management of corporate databases and 'data warehouses'

that support their various credit service activities.

Consequently, as information technology progresses, the

boundaries between companies engaged in credit

insurance, credit reference provision, factoring and debt

management and collection activities are becoming

increasingly blurred as each can develop new products

which cut across these various inter-related services. For

instance credit insurers can feasibly offer credit reference

information, market intelligence, debt collection services

and general credit management advice. Credit insurers can

also work with banks and other finance providers to offer

finance packages collateralised by insured trade debt.

Developments in information technology facilitate the

development of credit management and credit insurance

packages targeted to specific corporate sectors (e.g. small

and growing firms). The rapid growth in the number of

debt collection and related services on the internet offering

'on-line' collections will clearly have an impact on the

structure and economics of the commercial debt collection

industry.

Information and communication technologies have

improved the interface between the service provider and

the customer via 'on-line' links and have considerably

speeded up response times for, say, chasing debtors. The

move is now to a greater degree of 'customer focus' and

market segmentation within the credit services industry.

Moreover, technological developments are changing the

economics of the costs and benefits of 'in-house' versus

'out-sourcing' decisions at the level of the firm. Whereas

scale economies and economies of information may have

made contracting out elements of the credit management

function more cost-effective in the past, developments in

information provision and the lower costs of data

warehousing and analysis may have shifted the balance in

favour of in-house credit management for some larger

organisations. For the smaller and medium-sized

organisations, on the other hand, that now find themselves

trading at greater geographical distance, utilising the

services of large-scale and global credit service providers

may prove an attractive and cost-effective solution.



Developments in electronic trading and payment systems

may impact upon the demand for credit insurance and other

credit services. Corporate credit cards, debit cards and

payment cards (a corporate charge card which logs

purchase order and VAT information about transactions)

can be considered as substitutes for certain of these

services should they become widespread in the future,

although they may not be options for all firms (those with

high value goods for example). All these systems offer the

seller guaranteed money within a few days. Effectively

from an administrative point of view all transactions are

like cash (or perhaps cheque) sales; there is no need to

support a sales ledger and there is no need to assess and

take on credit risk. The possibility that a significant amount

of trade credit risk may shift to the financial services

provider (e.g. purchase card provider) has obvious

implications for the out-placed collection industry since it

implies collection activity moving in-house to the large

volume lenders.

3.8.1 Factoring and Invoice Discounting

Factoring is an important source of finance for businesses

with growing sales but low asset bases. The global market

for domestic factoring is nearly £800 billion with Europe

accounting for around 70% of the total global market.

Cross border factoring generates £68 billion17

.The UK

has a well established market for factoring services. By

July 2006, total advances by FDA members to business

was around £4.5 billion. Growth in the demand for has

been relatively low during the last 3 years in contrast to the

value of Invoice Discounting which has exhibited strong

growth since 2000 and stands at around £ 30 billion in

2005.

Domestic Factoring £M

0500

100015002000250030003500400045005000

Mar-95

Mar-96

Mar-97

Mar-98

Mar-99

Mar-00

Mar-01

Mar-02

Mar-03

Mar-04

Mar-05

Domestic Fcatoring

Domestic Invoice Discounting

0

5000

10000

15000

20000

25000

30000

35000

Mar

-95

Mar

-96

Mar

-97

Mar

-98

Mar

-99

Mar

-00

Mar

-01

Mar

-02

Mar

-03

Mar

-04

Mar

-05

Domestic Invoice Discounting

Chart 3.6.20 – Domestic Factoring Trends (Source: FDA)

Chart 3.6.21 – Domestic Invoice Discounting Trends (Source: FDA)



Export factoring and export invoice discounting advances

were in the region of £250m and 1.1billion respectively.

Again invoice discounting advances show the strongest

growth.

The Bank of England4

point out, however, that for firms

with a turnover of less than £1million factoring provided

just less than £1billion in finance compared to the £9

billion that bank overdrafts provide as a source of finance.

The data to the right demonstrates that most of the growth

in the demand for factoring came from firms with

turnovers in the region of £1-10million. Table shows the

average amounts advanced by size of firm. The amounts

involved are considerably larger than the average overdraft

(approx. £10k).

4 Bank of England 11th Report on Financing of Small Firms

0

200

400

600

800

1000

1200

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41

Export FactoringExport Invoice Discounting

Chart 3.6.22 – Export Factoring and Invoice Discounting (Source: FDA)

Chart 3.6.23 – Firms using Invoice Finance (Source: Bank of England)

Chart 3.6.24 - Growth in Demand for Factoring (Source: FDA)



3.8.2. Credit Insurance and Related Services

Credit insurance is traditionally used by companies to

protect their business against bad debts, payment delays

and protracted default which can seriously erode

profitability and liquidity. The size of the trade credit

insurance market, measured by global premiums, is in the

region of £3.75 billion. The market is dominated by

increasing global trade and the development of new

markets in China, Asia and Eastern Europe has stimulated

the growth of credit insurance particularly in the latter

regions. Growth in the US has been slow and Western

Europe has experienced only moderate growth in recent

years but still accounts for almost 75% of the total global

market. Penetration rates in the major European markets

and the US have generally increased over the past 15 years

although France and Italy have experienced a downturn in

the share of GDP in the new millennium. The penetration

rate in the US is very small but rising.

The market structure for credit insurance provision can be

characterized as oligopolistic, concentrated yet

competitive. Recent years have witnessed consolidation via

merger activity. The 4 largest players, Atradius, Euler

Hermes, Coface and Credito y Caucion have a combined

market share of over 80%. Credit Insurance is an industry

where there are considerable economies of scale and scope,

particularly in information, I-T and networks brought about

by the necessity of having a global coverage. Credit

insurance is a very cyclical business in terms of premium

generation, claims and profit/loss. Claims/losses vary with

the business cycle and particularly the aggregate

insolvency rate of businesses in the economy.

Clearly the growth in internet and information technology

has helped reduced the cost base of credit insurers as they

increasingly integrate their information systems with those

of their clients. Increased connectivity has to some extent

facilitated the growth in direct selling as apposed to

broking or, at least, extended the broker-base by enabling

smaller players to enter the market. Alliances with banks

and factoring companies has help to extend the reach of

credit insurance.

0.00%

0.01%

0.02%

0.03%

0.04%

0.05%

0.06%

1990

1992

1994

1996

1998

2000

2002

2004

USA Germany FranceItaly Austria Switzerland

World Market 2004 ICISA members (credit insurance)Total Market appr. EUR 4,56 bn

Credito y Caucion8,6%

CESCE2,4%

Coface17,8%

Mapfre2,5%

QBE1,7%

AIG2,4%

Others11,5%

Atradius21,1%

Euler Hermes34,4%

Chart 3.6.25 – Credit Insurance Growth (Source: ICISA)

Chart 3.6.26 – World Market for Credit Insurance (Source: ICISA)



The penetration of credit insurance in the SME market has,

over the past decade, been poor but is seen as the market

segment that has the most to benefit form credit insurance

products and the most potential for growing premiums and

cross selling other credit management services in the

future. In particular credit insurers have increasingly

marketed bundled services that attempt to offer a ‘credit

management solution’ rather than just insurance cover and

have necessarily diversified into receivables management,

credit and market information services, collection services

along with risk coverage.

A recent survey undertaken by the CMRC5

suggested that

the penetration of credit insurance amongst SMEs was less

than 2% compared to around 30% in the largest company

sector. Given that SMEs are the predominant form of

business across Europe and the globe then the potential

market for credit insurance and credit management services

is huge. In a recent survey of UK businesses undertaken by

CMRC6

firms were asked why they do not use credit

insurance.

5

Nicholas Wilson and Don Leahy (1998): “Credit insurance in

the UK and Europe”, The Stationery Office.

6

Corporate Strategy and Growth, CMRC, January 2005

The main reasons cited were that credit insurance was

perceived to be too expensive (68% of firms). The second

highest reason was that firms believed that credit insurers

provided inappropriate cover (51.2%). 39% do not use it

because they believe that it requires too much

administration and reporting. 21% thought credit insurance

had a poor image and 25% used other credit services. The

results of this part of the survey are summarized in the

chart below.

05

101520253035

Small enterprises (<10 Mn. €)Medium-sized entities (between 10 and 150 Mn. €) Large companies (>150 Mn. € turnover)

Not at all Very much

1 2 3 4 5 Poor insurance image 20.9 11.6 46.5 7.0 14.0 Too expensive 0.0 2.0 30.0 22.0 46.0 Inappropriate cover 7.0 7.0 34.9 23.3 27.9 Involve too much admin/ reporting 7.3 19.5 34.1 12.2 26.8

Use other credit services 25.0 10.7 39.3 14.3 10.7 Table : Why do you NOT use credit insurance – percentage of responses

Chart 3.6.27 – Use of Credit Insurance by SME’s (Source: ICISA)

Table 3.6.4 – Reasons for not using Credit Insurance (Source: CMRC)



Credit insurance can be made more attractive to the SME

market through increased automation to both reduce the

cost base of the service and reduce the administration and

reporting burden by developing better software interfaces

with the client and simplifying the reporting/claims

process.

Further ground could be made in this market by extending

the range of services offered and marketing the ‘product’

by emphasizing the impact that good credit management

practice can have on the overall business performance, i.e.

that the credit insurer is offering a credit management

solution that has a wider impact than merely protecting

cash-flow. Such re-branding could involve developing the

range of services offered, improving and modifying

existing services and/or changing the ‘image’ of existing

services via marketing activities.

The obvious benefits of using credit insurance are that it

transfers credit risk to insurers; it protects the insured

company’s balance sheet and reduces uncertainties in

earnings; it provides a variety of related services:

continuous monitoring of the creditworthiness of the

insured’s customers, maintaining account receivables,

suggesting payment and delivery conditions and supporting

debt collection; it can improve access to financing in that

firms with credit insurance can get better credit terms from

banks since the debtors book is collaterised. Finally, it can

help to generate sales and repeat business through agreed

credit limits.

In the survey cited above, when credit insured businesses

were asked why they use credit insurance, 85.9% of firms

in the sample respond that the do so for peace of mind. The

second highest reason is to protect cash flow (74%). Only

16% and 21.8% of firms use credit insurance to raise

finance and to enter new markets.

Not at all Very much

1 2 3 4 5 Previous bad debt experience 12.3 16.8 23.5 22.9 24.6 To grow the business 17.1 17.6 24.1 27.6 13.5 To protect cash flow 4.4 6.1 15.5 40.9 33.1 Helps raise finance 29.6 32.0 22.5 8.3 7.7 Help enter new markets 25.9 30.0 22.4 15.9 5.9 To improve knowledge of customers 13.1 16.6 26.9 28.6 14.9

Peace of mind 3.1 0.6 10.4 35.6 50.3

Table 3.6.5 – Reasons why companies use Credit Insurance (Source: CMRC)



A recent CMRC survey showed that those companies with

credit insurance were more likely to indicate that they

received preferential credit terms from their own suppliers

thus improving the overall cash and working capital cycle.

Credit insured firms are more likely to gain the confidence

of the supply chain because their own cash-in position is

more certain and therefore they are less likely to pay

suppliers late.

Moreover, 43% of businesses suggested that credit

insurance is useful for generating customer knowledge.

The users of credit insurance showed that they have to

spend less time resolving disputes and chasing late payers,

they have better control over cash flow and understanding

of the customer portfolio and they are more likely to have

software packages that improve the management of the

customer and sales ledger. It is clear, therefore, that credit

insurance has a wider impact on the overall customer

relationship management and the overall performance of

the business. Emphasis on these wider impacts may attract

new customers for all markets and particularly SMEs.

The chart below outlines the traditional view of the

benefits of credit insurance as a means of helping to protect

and manage cash-flow and customer risk. The technology

and information used in managing a credit insurance policy

however confers other benefits. A secured trade debtor

book can be useful in obtaining other sources of finance

from the banking sector and may help to reduce the firms

cost of capital and access to finance. Credit insurance can

indirectly help to improve supplier relationships. A credit

insured business is probably in a better position to pay its

own suppliers promptly and therefore may get preferential

credit terms form suppliers and enjoy a more stable

supplier base. Credit insurance can facilitate improved

customer relationship management by generating more

customer ‘knowledge’, having the systems in place to

better manage and resolve invoice disputes and confers

advantages form being able to offer customers both credit

and products/services. Finally, the information base of

credit insurers can be utilized to identify new market and

customer opportunities and facilitates speedy decision-

making in respect of new requests of credit accounts and

limits.

Cash-flow and Debt

management

Banking Relationship,

Cost of Capital

and Financing

Supplier

Relationship

Management

Customer

Relationship

Management

Traditional area of focusTraditional area of focus

- intelligence- technology

Table 3.6.28 – Traditional Benefits of Credit Insurance (Source: CMRC)



4. Large Volume Debt Management – Actual Case Studies

4.1. Introduction and Objectives In this section, we report a synthesis of interviews with

organisations involved in large volume debt management.

The aim is to provide a framework from which an

organisation can begin to assess whether they are

employing good practice in relation to the collection of due

and overdue debt in terms of: (1) taking enough action to

prevent debt from occurring; (2) pursuing debts quickly by

using appropriate methods to obtain payment cost

effectively; and, (3) investing in debt management systems

and more sophisticated recovery activity in order to collect

cost effectively within the ‘regulatory constraints’.

We examine trends and developments in debt management,

debt collection and recovery and look at the processes and

practices of large volume lenders in the consumer credit

industry and utlilties. The study looks at current practices

in collections and recovery amongst large volume lenders

and looks at the forces recent driving change in the credit

and collections departments. The report highlights new

approaches to collections and customer-base management

including new technologies and innovations and attempts

to assess the performance impact of these new investments.

We review recent trends in the collections strategies and

the general approaches taken towards customer

indebtedness, collection and recovery. The analysis

examines the path through which debts are processed, the

timing of various collection/recovery actions (i.e. the ‘debt

path’) and the effectiveness of actions at each stage. The

focus of this part of the study is to identify ‘best practice’

in collection and recovery departments and ascertain the

processes, procedures and technologies that help to

minimise the level of ‘un-collectable’ and ‘bad debt’ from

the domestic (household) market.

Organisations providing financial services have a different

context and regulatory environment than organisations

providing gas, electricity, water and telecoms. Financial

services are in effect competing for debt and customers but

have to maximise collections performance and minimise

bad debt losses within a relatively short time horizon on

individual accounts. Water suppliers have limited sanctions

against late and non-payers in that they cannot disconnect

supply and have no choice over their customers. Gas and

Electricity suppliers have some choice over their customers

and can take action to secure payments from riskier

customers (pre-payment meters, deposits, credit

references). They have, of course, the sanction of

disconnection to non-payers. Gas and Electricity

companies, however, have to compete for customers and

the industry has been subject to considerable restructuring

(mergers, acquisitions, outsourcing customer service and

collections). We draw upon evidence of ‘good practice’ in

this sector from a series of structured interviews and a

forum that has been devoted to benchmarking credit and

collections performance and credit/debt management

practices. We are able to identify the good performers in

then UK utilities from the Utilities Benchmarking Forum

data-base and analyse the specific factors that appear to

impact on debt levels in this sector. From this we are able

to draw up a check-list of perceived ‘good practice’ in the

sector.

The section is organised as follows. First we provide a

generic overview of the credit account life-cycle. We then

examine current good/best practice in debtor management

and collections as synthesised from the various case



studies. We then provide a summary of the findings from

the surveys undertaken since our first study in 1998 in

order to trace major trends. We then report on the case

studies and updates.

4.2. Background to the Credit Account Life-cycle

4.2.1. Customer Life-Cycle

This section provides some background to the typical

processes and stages in the management of a credit

account. In financial services lenders are typically starting

to move towards a ‘customer-level’ view of individuals not

only across different products but over the possible life-

time of the customer. Although this section focuses on the

management of individual accounts it is worth noting that

financial services may take a life time view of the

profitability of a customer and manage individual accounts

with cross-selling opportunities in mind and long term

profitability as an objective.

Chart 4.2.1 – Customer Life-Time Management

4.2.2. Account Life-Cycles

Although the operational processes and strategies will

differ between lenders there are some basic, common

elements. Credit accounts will generally go through a

series of stages, illustrated below. The consumer credit

sector is characterised by lenders that typically deal with

large volumes of accounts and consequently manage

millions of relatively low value transactions on a day-to-

day basis.

The stages in the process of account management equally

apply to the trade credit, business to business context. In

the latter case the lender will typically have a much smaller

customer-base and higher average invoice/order value. An

examination of the credit account life-cycle provides a

useful background from which we can examine the main

trends and forces driving change in debt collection as

gleaned from the series of interviews undertaken over the

past 10 years.

Chart 4.2.2 – The Customer Account Life-Cycle

Marketing/Recruitment

ApplicationProcessing

AccountIn Use

Authorisations andAccount Management

Collectionsand Recovery

Set UpAccount

New Prospects



The usual way of classifying consumer credit products is as

either 'revolving credit' or 'fixed term credit'. Revolving

credit allows the customer to make purchases up to an

agreed credit limit, regular (monthly) payments by the

customer release available credit and allow further

purchases to be made. There has, of course, been a recent

proliferation of segmented Credit Card products and many

variations under the revolving account heading. The other

main type of credit account, fixed term credit, involves the

customer paying for a single purchase or paying off a loan

by instalments.

The number of instalments and the payment regime are

usually fixed at the start of the credit agreement. Recent

trends have seen a general increase in the repayment terms

of personal loans (from 3 years a few years ago to 5-10

years now). Of course customers that have experienced

payment difficulties on credit card or loan products may

have put in place an ‘arrangement to pay’, i.e. a fixed

monthly payment plan aimed at recovering debt over a

longer time period.

The application process for a new financial product is an

important means of establishing the customer's credit

worthiness and risk profile. Information is generally

gathered via account/product application forms which can

vary from simple coupons in magazines asking for only

name address and telephone number, (as in the case of

some mail order catalogues), to forms covering several

pages and requesting detailed financial information such as

salary and balances outstanding on current credit

agreements. Of course there are often informational

asymmetries between lender and borrower at this stage.

The lender may not have a complete picture of the

borrowers assets, liabilities and future prospects.

It is important for lenders to ascertain a profile of the

potential borrowers past behaviour (e.g. payment pattern

on previous loans), current behaviour (e.g. how is the loan

applicant handling their credit cards or current account)

and total credit commitments. The latter is particularly

important, as borrowers will now typically spread their

outstanding credit across multiple products and multiple

lenders. Most credit grantors in the UK contribute to closed

user groups, such as CAIS or Insight, which provide

information on the accounts the applicant has currently, or

has had, with other credit grantors, i.e. total credit

exposure. Credit reports can be obtained from Credit

Reference Agencies, which provide details of, for example,

the Electoral Roll at the applicant's address (to check

residency), county court judgements against the applicant,

or recent credit searches done by other credit grantors. The

CRA data-bases have recently been considerably enhanced

by the major lenders HSBC and Natwest agreeing to share

account level information and the development of

indebtedness indices that evaluate an individuals debts in

relation to disposable income. Some lenders will now score

applicants according to risk and their forecasted ability to

service outstanding debts.

17

Credit Application

Cre

dit

App

licat

ion

Data Input

Cre

dit

App

licat

ion

Data Input

DECLINEDECLINE

Decision Engine

ACCEPT REFER

Manual ReviewProofs

DECLINEDECLINE

Decision Engine

ACCEPT REFER

Manual ReviewProofs

DECLINE

Decision Engine

ACCEPT REFER

Manual ReviewProofs

DECLINE

Decision Engine

ACCEPT REFER

Manual ReviewProofs

Other Data Gathering

Internal Files

CRA Bureau

Data

Other Data Gathering

Internal Files

CRA Bureau

Data



The Basel II initiative has drawn attention to lender risk assessment systems but more work can be done in this area. Risk assessment at the point that the customer applies for credit has, historically, utilised credit scores that rely on information regarding the applicants past performance on credit accounts. New scoring systems, that are more forward looking, and factor in a more complete picture of the customers’ indebtedness in relation to current and potential income flows along with features reflecting the impact of interest rate changes and the economic cycle will undoubtedly lead to a reclassification of portfolio risks”.

Thus an integral part of the process is application scoring,

based on the consumer's characteristics, and automated

(accept/reject) or manual (review) decision processing. For

instance, the credit granting decision process may involve a

mixture of credit scoring, applying the company's policy

rules, and human judgement. There may also be checks

against the company's in-house information; for example

checks for duplicate applications, checks for fraud and

checks on the applicant's performance on other credit

accounts held with that company.

Usually a decision process will have three outcomes;

accept, reject and refer (referred applications could be

those with scores around the borderline, for example, or the

company may have policy rules to refer certain types of

application). Referred applications will usually be

processed by more senior staff, with queues of applications

to be reviewed being maintained by the system.

The Application Processing system may also make

decisions in areas such as the setting of credit limits.

Consumers that have several credit accounts with the same

credit grantor, (several store cards can be run by one

finance company for example), may be set a credit limit on

their new account based on their exposure on existing

accounts. Alternatively, the lender might set an overall

credit limit for the customer. This total limit may be

distributed across accounts and products. Application

scores may allocate new accounts into certain life-style

clusters or segments which are then used in account

management and or for cross-selling. In mobile phone life-

time value, risk and fraud are key dimensions that are often

assessed at the account set up stage since recovering the

initial investment in the customer (handset and network);

managing fraud in a fast moving market and managing

payment risk are key to a profitable relationship. In the

utilities, assessing risk in order to match the appropriate

payment method and plan; securing deposits where

necessary and clustering customers according to

consumption patterns and life-style indicators can be

valuable in managing collections and overall customer

profitability.

Account management involves a variety of activities that

take place either on a regular basis or in response to

specific circumstances or behaviour. One objective is to

keep the customer in account management and prevent

progression into delinquency and recoveries. Some lenders

put effort into identifying payment risk pre-delinquency by

monitoring transactions and potential over-commitment.

The figure overleaf taken from Wilson and Summers (1998

p45) summarises the regular activities that a typical

account management system would support.



The key activity is processing payments and allocating the

funds to the appropriate accounts. A variety of payment

methods/options are usually offered (cash, cheque,

standing order, direct debit, switch, bank transfer etc)

although individual lenders may encourage particular types

of payment method.

Direct debits are usually processed within the BACS

system. BACS distribute payment requests to the banks

concerned. Direct debits can be used to make variable

payments, for example paying either a full amount

outstanding or a minimum payment on an option account,

such as a credit card. Direct debit is regarded as an

attractive payment method for fixed term loans and is

increasingly encouraged for revolving credit as a risk

management device. The latter was not the case a few

years ago since most credit card profit/income comes from

interest on the balance outstanding.

Account management systems have to be able to cope with

payments that cannot be matched to accounts. These can

arise from, for example, incorrectly stated account numbers

on a standing order or when a cheque and payment slip

become separated.

Unmatched payments are normally posted to a suspense

account and both automatic and manual efforts will be

made to match them to an account, perhaps using the name

on the cheque or an expected payment value to search for

potential matching accounts. The payments in suspense can

be interrogated if a customer queries an un-posted

payment.

In addition to payments, for revolving credit accounts there

will also be transactions representing purchases made with

the account and potentially credit notes if, for example,

goods are returned. Many transactions are now recorded

electronically although paper vouchers are still in use,

particularly in smaller outlets taking credit cards. Details of

transactions may come to the lender direct or through

intermediaries, as is the case with credit cards. Some

transactions may also be generated automatically, for

example, the annual fee on a credit card or insurance

charges for things like payment protection.

Account Management Functions

Regular As Required

Transactions Authorisations Payments Credit lim it changes Calculate interest Address changes Statements Settlement Account renewals Correspondence Merchant support Lost cards Diary/Account history Missed payments Insurance Over limit processes Behavioural scoring Strategy management Fraud detection

Table 4.2.1 – Account Management Functions (Source: CMRC)



Scoring models are increasingly used at all stages of the

account life-cycle. Increasingly profitability or debt

servicing ability may be ascertained at the point of

application. Scores to detect early signs of problems and

the likely debt path from ‘self-cure’ to arrears may aid the

collection process by either taking no action in the case of

‘self-cure’ individuals or fast tracking cases through the

collection sequences. Litigation scores may be used to

assess the likely success of legal action and scores may

help in pricing debt for sale.

These scores under the generic heading of behavioural

scoring are used at various stages of the accounts life. The

production of behavioural scores (see later for an overview

of Behavioural Scoring) which provide an indication of

the way an account is being conducted and the level of risk

it represents, may be produced by the Account

Management system itself or by a separate system

interfacing with it. If an account goes into arrears the

Account Management system may either manage the

collections process itself or pass the account's details to a

separate collections system. If the lender uses behavioural

scoring then systems need to be in place to regularly

update the behavioural scores. These may be part of the

account management software or may be provided by a

link to a separate system.

Alongside behavioural scoring there may also be strategy

management processing; for each account a strategy may

be assigned for anticipated circumstances, such as a request

for an increased credit limit or missing a payment, based

on the behavioural score and/or other factors.

Increasingly, account management systems will keep a

record of the history of each account, showing all the

transactions applied to it, and a diary of contact with the

account holder on any actions in progress, such as

following up queries about statements. These will be of use

to the customer services department when contact is made

with the account holder, as well as, the historic information

Account Management Early Delinquency Recoveries

Collections Environment Recovery/ SaleDebt Prevention

‐Application scores‐ Limit Scores‐ Affordability scores‐ Revenue/Risk Score

‐ ‘Self‐Cure’ Score‐ Roll Rate Score ‐ Behaviour Score‐ Collection Score

‐ Recovery Score‐ Litigation Score ‐ Debt Price

Chart 4.2.3 – Scoring in Account Management



being potentially a useful input to behavioural scorecard

development. Information collected from contact with a

customer in arrears may be used to modify collections

strategies that are being determined automatically. An

obvious case is where an otherwise prompt paying

customer has got into arrears because of a unexpected

event such as loss of income, accident or illness.

Account management systems have to be able to deal with

authorisations. On revolving credit accounts there can be a

requirement for sales over a certain value to be authorised

before they go ahead. This can be done by a phone call or

automatically when the card is swiped through an EFTPOS

terminal. Checks done at authorisation stage might include

calculating whether the transaction will take the account

over its credit limit and an assessment of the likelihood of

fraud on a large transaction. As indicated earlier plastic

card fraud is a major and escalating problem. Fraud is one

area where non-statistical models such as expert systems

and neural networks are most often used rather than

statistical models. These techniques can cope with the

rapidly changing nature of fraud, and identify new patterns

of fraudulent behaviour. The identification of a potential

fraud can result in customer services contacting the

account holder and checking on the transaction.

Account management software will need to check credit

limits as transactions are posted. When an account goes

over the limit a decision is needed on the action to be

taken, and some evaluation made of whether the problem is

likely to be a result of fraud. This might be based on the

amount by which the limit is exceeded and the customer's

previous behaviour. Usually, systems maintain a shadow

credit limit (an amount of credit above the known limit that

the company would be happy to give the customer based

on their perception of risk). The shadow limit allows the

call centre to respond promptly to customer requests for an

increased limit if the request is within the shadow limit

bounds. Responses to over limit situations include a

message on the statement, a letter or a phone call. The

account management system might have a strategy

allocated to the customer to deal with this eventuality.

Customers may also contact the lender with other requests

and enquiries, for example a change of address, a statement

query, a lost card or a request to pay off a fixed term loan

early. Customers who wish to pay off a loan early can

request a statement from the company of the amount

required to pay off the loan by a certain date. This will

require new interest payment calculations and there may

also be early settlement penalties and administration fees to

calculate.

The account management systems generate different levels

of management information that is used to produce reports

to support operational and strategic decisions. This might

include volumes of business, volumes of payments and

aged debt reports, split by variables such as product and

source of business. Having real time information on

delinquency levels is seen as important for modifying

collection and recovery stratgeies and/or realigning risk

and behavioural scores.



When an account shows signs of going into arrears, the

lender needs to ascertain what the appropriate action might

be to remedy the situation. Arrears may be a sign of

financial difficulty and a deteriorating profile or simply

represent a situation where a person regularly pays their

monthly bill a few days late, perhaps coinciding with when

they receive wages/salaries. Collections systems primarily

provide a diary function, so that a record is kept of contacts

with the accountholder and actions taken, and a queuing

system that enables the processing of accounts to be

controlled. Accounts entering collections will be allocated

to a particular queue initiating a particular action, such as

telephone contact with the customer or the sending of a

letter.

Clearly a strategy needs to be adopted that minimises

contact/collection costs but effectively remedies arrears.

There may be several collections strategies, perhaps based

on collection scoring, involving phone calls, reminder

letters or passing the accounts to an external debt collection

company.

The lender needs to identify the best route to take for a

particular account as promptly as possible. At this stage, a

decision may be made to pass the debt to an internal or

external collection agent. Collection agents will often use a

collection score to determine the most cost effective

actions to recover the debt.

Application App lication Processing S ystemP rocessing S ystem

Account Account M anagem entM anagem entS ystemS ystem

BehaviouralB ehaviouralScoring / S trateg yScoring / S trategyS ystemS ystem

C ollectionsCo llectionsM anagem ent M anagem ent S ystemS ystem

Debt Management & Collection TrendsDebt Management & Collection Trends

telephone contact (power diallers)more personal telephone / letter contact

debt collection agencies(internal and/or external) litigation

phone letter doorstep

Chart 4.2.4 – Applications to Collections

Chart 4.2.5 – Debt Management and Collection Trends



The timing of further actions is usually driven by a review

date that can be set by the collector or by the computer

system after an automatic action such as the sending of a

standard reminder letter. Accounts within a queue can be

prioritised by criteria such as value of debt, time in arrears,

or some combination of criteria.

Wilson and Summers (1998) identified differing collection

strategies for different types of financial services.

They write, "as a simple example Company A, who run an

in-house store-card system, would attempt to transfer

customers onto direct debit for payment of the card

wherever possible. This simplifies and speeds collection.

The objective here is to clear account balances in order to

facilitate further spending in the store. Company B, a

credit card provider, operate a very similar collection

system but have made a policy decision not to encourage

direct debit as this would reduce the profitability of the

customer base. The objective here is to allow profitable

debt to build but at the same time minimise the risk of

default and costly collection activities".

Letter & telephoneDoor step collection

Litigation

No ActionWrite-off

Receive Bad Debt

Scoring/Decision Tree (classifies debt)

StrategyStrategyAllocationAllocation

Chart 4.2.6 – Scoring to Determine Collection Strategies



In the later stages of arrears accounts may be passed to

debt collection agencies, sold or go to litigation. The

collections system now usually provide for monitoring/

review of accounts passed to an external agent or litigation.

Some systems include litigation functions but separate

litigation packages are also available. In the case of debt

sale, information has to be provided so that the buyer can

undertake due diligence.

The large volume lenders have relatively sophisticated

management information systems that facilitate the

tracking of customer risk and the progression of delinquent

debt. Such information is essential for making provisions

for bad debt write-off. Clearly the actual amounts

outstanding will be converted fully into cash because a

proportion of borrowers will default on some or all

repayments. Management information systems have

improved substantially in recent years and allow various

profiles and ‘drill downs’ of the current portfolios.

Lenders attempt to model debt progression from current to

delinquent in order to determine provisions and set targets

for collections and recovery operations. Common methods

for projecting bad debt levels are ‘roll-rate’ models and

variants, such as Markov Chains. The former tracks the age

of debt and predicts the proportion of debt say in the 1- 30

days overdue category that will progress into the next

category of arrears 30-60 days overdue. By analysing

recent history the proportion that will roll forward can be

estimated. In practice roll rates will often be calculated on

a daily basis, i.e. how much of the 1 day overdue rolls onto

2 days overdue.

The Collection departments may look at the profile of

delinquency at each collection cycle or collection action in

order to estimate the returns in relation to actions.

Collection departments will be interested in analysing ‘cure

rates’, that is the proportion of accounts that are currently

overdue that are fully or partially returned to order.

4.3. Elements of ‘Best Practice in Collections’ and Implications

This section is based on an analysis of a series of case

studies of the collection systems and structures of some

organisation that have large volumes of consumer debt to

manage, collect and recover which we refer to as ‘large-

volume lenders’. The lenders cover: (a) Financial Services:

Credit Card, Current Accounts, Personal Loans, Charge

Cards, Insurance Products, mortgage lenders; (b) Utilities:

Gas, Water and Electricity; (c) Telecommunications:

Mobile and Fixed Line (d) Home Shopping: major Mail

Order Companies. Interviews have been conducted within

a selection of organisation in the categories above at

various intervals since the initial survey in 1998. This

report summarises the interview responses from the

original survey in 1998 (see 'Debt Collection in the UK and

Europe', by Wilson and Summers 1998 for more detail).

and the updates provided in 2001, 2003 and 2007. Thus,

major trends in the collection systems and strategies can be

gauged with a particular emphasis on the back-end of the

collection and recovery cycle and the usage of 'out-placed'

collection agents by large volume consumer lenders and

the more recent trend to use debt sales as an alternative to

placing for collection on commission. The trends in 'in-

house' collections systems and procedures have obvious

implications for the 'external' debt collection industry.



This purpose of this section is to draw some general

conclusions from tracking developments within

organisations engaged in high volume consumer lending

and debt management. The focus was an examination of

recent trends and strategies in collections. Interviews

allowed us to gain insights into the 'state of the art' in

information provision, risk analysis and decision support

and debt progression software, with a view to identifying

common and 'best' practice whilst focusing on the forces

driving change in the credit and collections departments of

these organisations. The analysis provides a benchmark for

organisations interested in appraising their current practice.

Clearly any investment 'in-house' in new debt management

philosophies and technologies should affect internal

collections performance and efficiency and will have an

impact on the type, age, quality and volume of debt that is

made available to external debt collectors and debt buyers.

An attempt was made to focus on organisations held as

examples of 'best practice' within the industry, or

organisations that had recently re-organised their credit-

debt management activities and/or invested in new

information-technology and collection systems. A synthesis

of the main trends affecting high volume collection

concludes the section.

Marketing


AccountIn Use

Account Management


Set UpAccount

New Prospects

DCA’s ?Sale ?

Marketing


AccountIn Use

Account Management


Set UpAccount

New Prospects

DCA’s ?Sale ?

Marketing


AccountIn Use

Account Management


Set UpAccount

New Prospects

DCA’s ?Sale ?

Credit Card Bank Loan Current Account

Marketing


AccountIn Use

Account Management


Set UpAccount

New Prospects

DCA’s ?Sale ?

Product Level View

Customer Level View

CRA’s

Chart 4.3.1 – New Debt Management Approaches



4.3.1. Credit Information and Scoring Technologies

Profiling and understanding the ‘customer’ is at the heart

of best practice account management debt prevention and

collections/recovery. Organisations in financial services

have and continue to invest in data-base systems that

facilitate the generation of a view of the customer

(customer-level) rather than behaviour in respect of a

specific product (account-level).

This has involved matching all internal product use with

particular customers (e.g. bank account, credit card,

mortgage) and gaining an insight into the customers

behaviour and level of indebtedness with the credit

accounts of other lenders via the credit reference agencies.

The latter has been aided by major lenders, such as HSBC

and Natwest sharing their data and the development of

‘indebtedness’ indices by the CRAs (e.g. Experian,

Callcredit). Prior to these initiatives, the lender had a very

partial view of an individual’s debt commitments and

ability to service debt (creditworthiness).

The compilation and management of 'data warehouses'

including credit reference data, lifestyle and geo-

demographic data, and 'closed user group' data has been

facilitated by sophistication in computer technology and

software. Thus there has been a move towards profiling the

'customer' across all credit products, rather than a 'product

focus' and gaining a view of total indebtedness.

Organisations have been re-organising data and

information systems to be able to 'manage the customer not

the debt'. Decisions are informed by scoring systems and

propensity modelling, but there has been considerable

resources devoted to the capturing of ‘up to date’ and

‘event’ data from telephone and letter contact with the

customer. For instance, a customer may currently have a

good risk score but telephone contact reveals that the

household has recently lost income through job changes.

The profile of the customer can then be changed

accordingly by combining both the quantitative

information from scoring systems with ‘qualitative’

information from customer contact. Profiling customers

will usually involve 'segmenting' the customer base into

groupings with similar characteristics and behaviours

and/or in relation to appropriate collection activity.

15

coping with high volumes with low value in a competitive environment

pricing risk – segmentation

managing and understanding customers (relationships) andmaximising profits

Credit Scoring

Propensity(probability)Modelling

‘If’ ‘when’

timing

Chart 4.3.2 – Motives for Credit Scoring in Consumer Credit



Organisations use statistical models and 'scorecards' to

support credit decisions at all stages of the credit lifecycle

from credit applications to account management via

'behavioural scoring'. The term ‘credit scoring’ was coined

in relation to application scoring used for reject/accept

decisions in high volume low value credit granting

environments. The technique has evolved to model many

‘propensities’ as well as risk. For instance, there is an

increased use of models to predict/understand customer

'churn'; payment behaviour; collection scores; life-time

value and profitability etc. Different techniques are often

combined, e.g. statistical methods for scorecard building;

neural networks for account monitoring (behaviour, fraud

etc); expert systems for implementing 'policy rules'.

Organisations are placing more emphasis on monitoring

scorecard performance after implementation and

monitoring different strategies towards customer segments.

More recently, emphasis has been placed on modelling the

‘timing’ of behaviours to determine the optimal ‘timing’ of

actions. Scoring models are essential for the accurate

‘pricing’ of debts and debt portfolios should a debt sale

opportunity arise.

Best practice systems incorporate many of the elements

charted below. Data combinations that are able to profile

account or service usage; the customer life-style;

indebtedness and income. Data is updated at every

opportunity. This information feeds into propensity models

that help to segment customer behaviours and determine

strategies to be employed in responding to customer

behaviours. This facilitates the efficient deployment of

resources and skills in managing customers. MIS systems,

strategy testing and benchmarking aids continuous

improvement and adaptation to change.

DATACustomer LevelAccount Level

CustomerBehaviour

ContactUpdates

Credit ReferenceData

PROPENSITYMODELS

InformedProcesses andStrategies

‐ Customer segmentation

‐ Tailored Collectionand Recovery Processes

‐Focussed resources and skills

‐ Champion‐ Challengertesting

‐ Cost‐benefit Analysis

‐ Sophisticated MIS

Chart 4.3.3 – Modelling for Collections Strategies



Collections or behavioural scores are one variant on

propensity scores that may be used to accept/reject an

application for finance. Risk scores rank the customer in

terms of the probability that they might become delinquent.

Collection scores are compiled based on risk and recent

behaviour. They are designed to determine the probability

of collection and/or the percentage of debt that should be

collected. Collection and recovery scores help the collector

prioritise actions and the debt path for each delinquent

customer. Thus, the score provides empirically an

assessment of ‘collectibility’ and therefore determine an

appropriate collection strategy. As outlined above

delinquent accounts flow through a collections life-cycle or

debt path and require different techniques to solve the

problem. The overdue payment will initially be dealt with

in the ‘account management’ system and then flow through

to ‘collections’, internal and external ‘DCAs’, 1st

, 2nd

and

perhaps 3rd

placements with DCAs and then through to

write-off, ‘debt surveillance’ or ‘debt sale’. The collection

score can be utilised the path and the timing of actions.

Such score can also be utilised to help determine a ‘price’

for debt sale.

The need for monitoring activities versus returns and

decision software tools has grown with the use of scoring

models. Champion-Challenger (see below) is commonly

used to test different strategies on different customer

segments (based on scores). The collection process/strategy

is therefore adaptive and varied at regular intervals. Thus,

the key features of such a system are: (1) Segmentation -

the collection department must be able to identify customer

sub-groups with similar characteristics/behaviour; (2)

Score calculation and implementation - the system must be

able to warehouse customer data from various sources,

calculate and update scores and incorporate them into the

decision process; (3) Adopt a champion-challenger

environment for continual testing and strategy

improvement; (4) Undertake ‘what if’ scenarios for future

strategy implementation; (5) Report detailed management

information on collections activities and returns and

provision for bad debt.

In order to build and utilise behavioural scores as a means

of making more effective and automated decisions the user

has to have a sophisticated customer data base and a high

frequency of behavioural information. Typically, the user

will have a high number of accounts, high volumes of

usage and historic performance, comprehensive and robust

periodic dates, a highly automated and integrated account

processing system and automated delivery mechanisms.

Samples of data can then be downloaded and analysed in

relation to a particular outcome.

The principle is as follows and summarised in the diagram

overleaf. An outcome (i.e. 3 payments down) may be used

to build the behavioural score. Data is taken at the

observation point for a sample of good/bad accounts.

Account characteristics and behaviour in the previous 12

months is analysed and related to the particular good/bad

outcome and behavioural scoring model is built and used to

classify the probability that current good accounts will

become bad at the outcome point.

Behaviour Scoring: Principles

ObservationPoint

OutcomePoint

24 months ago 12 months ago Today

Behaviour

Window

Chart 4.3.4– Behaviour Scoring: Principles



The chart to the right provides information on the types of

variables that might be collected in the ‘behaviour

window’

A statistical process is employed to derive points or

weights for each behaviour variable. These are summated

for each account to derive an overall behavioural score. An

example is provided in the Chart opposite.

The behavioural scores might be used to make decisions

about an account at the various stages in the life cycle.

Additional data and behaviour can be added to create

‘collection scores’ and ‘recovery scores’ as highlighted in

the Chart opposite.

Behaviour Scoring: historic performance characteristics

- How the account has been operating historically, e.g.

- Number of times over the limit in last 3 months- Average balance over the last 6 months- Average payments/Average balance over the last 6 months- Average outstanding balance over the last 3 months/ averageoutstanding balance last 6 months

- Decision point details

- Current balance- Current balance/limit %- Age of account- Current facilities

Example Behaviour Score Card

Balance / limit%

Ave payment / Balance%(last 6 months)

Cash advances/total debits %(last 3 months)

Age of account (months)

Worst arrears stage(last 6 months)

0 - 30 31 - 80 81- 100 101+

0 - 5 6 - 20 21 - 50 51 - 100

0 - 5 6 - 50 51 - 80 81 +

0 - 6 7 - 12 13 - 24 25 +

0 - 1 2 3+

+50 0, -30 -100

-60 0, +20 +35

-10 -30, -20 -150

-10 0 +10 +30

0 -35 -120

valuepoints score

Application Early Behaviour Behaviour/Delinquency Recovery

Pre-acceptance 1st bill- 6 months 6th months- final bill Final Bill Write-off

Customer provideddata to assess futurerisks and credit limits,billing and paymentplans and security Application risk score

and early behavioursuch as early transactionsand payment

Analyse actual customerbehaviour such as payments,overdues, balances .. Toassess risk and set collectionor treatment priorities

Behavioural Scoring and the Account Life-cycle

Liklihood of this account leaving anunpaid balance,arrangement vs action

Strategy asdetermined byrecovery score;Litigation ?DCA?Sale?Write-off ?

Chart 4.3.5 – Behaviour Scoring

Chart 4.3.6 – Example Behaviour Score Card

Chart 4.3.7 – Behavioural Scoring and the Account Life-cycle



4.3.2. Customer contact and Customer Retention and Collection

In Financial Services, one of the impacts of Basel II rules

and the default definition (90 days) has been to focus the

attention of lenders on the time path of debts. An emphasis

is now placed on detecting indebtedness problems and

potential payment difficulties at an early stage and if

possible to solicit some payments that enable the debt to be

reclassified. This may involve the use of scoring or

behaviour triggers to alert account management to relevant

changes. Customers may be contacted for counselling or

‘money management’ and pre-emptive action to relieve

financial pressure via the restructuring of finances or debt

being re-aged. Emphasis is on customer retention and

rehabilitation in order to prevent future delinquencies.

Customer retention emphasises early contact with

individuals and their education regarding payment habits

and indebtedness and referrals for 'debt counselling' in

some circumstances. Supported by 'on-line' and timely

information on the individual's account history and

payment scores.

Call centre staff have increased flexibility and discretion in

the approach to indebted customers with an emphasis on

resolving the problem and negotiating solutions to the

problem, e.g. restructuring payments. It is recognised that

financial difficulties can be transitory (due to changing life-

styles and income streams) and customers in arrears can be

rehabilitated. Significant resource is put into keeping

account information up to date particularly contact

information, employment status, income and assets. This

information is used to modify the treatments that may be

automatically determined by the scoring systems.

Customers in early stage delinquency are contacted

immediately and repeatedly in order to resolve any

problems quickly. Again, restructuring debts and

implementing a program to recover outstanding balances is

the priority. Collection staff must be multi-skilled to deal

with multiple products on multiple systems. Recalcitrant

customers will be passed on to a 'collections' environment

when the early stage collection has not been successful, i.e.

broken promises, arrangements not kept up.

Customers are segmented by risk and outstanding balances

and much champion-challenger testing in relation to

strategies and the timing of actions is undertaken. Scores

focus on ranking customers by ‘propensity to pay’. The

cycle from arrears to recovery action and write-off has

become much shorter but accounts and debts are worked

much harder or more aggressively in the early stages.

Delinquent accounts are passed into the ‘external

environment’ via debt sale or to a DCA much sooner where

the emphasis is on recovering arrears through repayment

plans.

The Champion-Challenger environment is commonplace in

collections. Champion/challenger systems can be used to

develop strategies over time. The basic approach is

illustrated in the chart below. In collections, a particular

collection sequence will be in operation for certain types of

accounts. The approach/sequence is then slightly varied for

a sub-set of accounts (challenger strategy) and the

outcomes are monitored and tested against the champion

strategy statistically. If the challenger outperforms the

champion it becomes the new champion that in turn is

tested against new challengers.



By adopting different collection sequences with different

timings across a segmented collections portfolio

collections performance can be continually improved. The

effect of changing the collections sequence provides an

uplift to collections performance simply by removing the

predictability of the collections sequence from the

perspective of the debtor. A debtor that can predict the

sequence of actions to recover payment will rationally wait

until the end stage before paying or until collection efforts

‘get serious’. If the collections sequence is constantly

changed, then this can stimulate the debtor into better

payment habits. Champion-challenger can increase

effectiveness by targeting actions that solicit the best

response from customer segments and removing collection

stages that have been shown to add little value in the

collection process. The process of continual improvement

may involve creating ‘specialist’ collection teams that

focus on particular debt stages or particular customer

segments.

Organisations have implemented systems that are able to

identify quickly if an account is going into arrears and

decide an appropriate collection strategy. Various

information support systems are now available to help the

organisation make timely and suitable decisions.

Collection support systems have the following features:

• A diary function which records contacts with an

account holder and the actions taken;

• Queuing systems to control the processing and

progression of overdue accounts: different queues

initiate different actions; different queues for

different account types; choice of queue can be

determined by risk scores; timing of next action

can be automatically set and implemented;

prioritisation within a queue by value, age, risk of

Champion 80% accounts Challenger 20% accounts

£’s OutstandingRisk ScoreLow Medium High

Low

Medium

High

£’s OutstandingRisk ScoreLow Medium High

Low

Medium

High

CollectionStrategy

Time

Letter

Phone

DCA

Letter

Phone

DCA

LetterPhonePhone

Legal

DCA

LetterPhonePhoneDoorstep

DCASale

Chart 4.3.2.1 – Champion vs Challenger Strategies in Collection



default etc.; automatic sending of reminder

letters;

• SMS messaging is used to invite inbound calls.

Inbound calls are deemed a very successful

strategy for resolving payment problems;

• Collection staff will be monitored on cash

collected, promises kept, ATPs arranged, call time

etc. Collection staff now works in a competitive

environment and will often receive bonuses based

on performance.

4.3.3. Collection department practices

Leading edge collection departments tend to have the

following characteristics:

• Centralisation of the collection function

especially in the early stages and specialisation as

the debt progresses;

• Use of 'champion/challenger' approach to ensure

that collection strategies are constantly updated

and effective; statistical analysis of C/C

strategies;

• Customer tailored collections paths are more

likely; different strategies for different ages of

debt using different collection approaches;

emphasis on rehabilitation of customers and cash

recovery;

• Use of on-line customer information systems and

credit reference agencies to provide payment

histories;

• Use of automated collection systems using

decision support information to prioritise debts

and determine the appropriate collection strategy;

• Management information for documenting and

monitoring actions taken and responses by

debtors; collectors' performances; early detection

of non-compliance incorporating the use of

scorecards to identify individuals most likely to

default and the probability that they will repay.

The ‘timing’ of actions is deemed to be very

important and lenders are researching the impact

of varying delinquency cycles;

• There is recognition that ‘debt resting’ may be an

appropriate strategy for certain accounts. If a low

risk customer has been affected by an unexpected

‘event’, such as divorce or employment change

then it may be more cost effective to allow the

customer to recover his/her financial position

before collection action is taken;

• There is more use of ‘behavioural’ and ‘collection

scoring’ to segment customer-bases and

determine the escalation process for each debt,

i.e. debts may not all pass through the same

sequence of actions. In order to be effective, these

collection strategies have to be monitored and

tested continually in a champion-challenger

environment. New strategies based on customer

risk profiles and ‘propensity to pay’ scores are

implemented and monitored to establish possible

sources of cost saving and efficiency in

collections activities;

• Implementation of activity-based costing to

monitor cost effectiveness of actions versus

recovery;



• 0nce non-compliance established early contact

with debtors via the telephone; use of

power/predictive dialling telephone technology;

investment in new contact modes that encourage

the debtor to make inbound calls. For instance,

SMS messaging and or Interactive Voice

Response (IVR) calls;

• Early categorisation of debtors who 'can't pay'

from those who 'won't pay';

• Early establishment of a realistic payment plan;

• Negotiation with debt management organisations

and IVAs.

Debt sale is on the increase and all the lenders that were

interviewed were actively participating in the debt sale and

purchase market. The market for debt sale is increasing

since the time horizon of the lender and the DCA is

different and facilitates the customer shifting from a short-

term payment plan (credit card) to a longer term

arrangement (DCA arrangement to pay).

In interviews, Debt Sale was usually undertaken post-

write-off. Usually debt would be written-off after being

out-placed once or twice unsuccessfully. At this stage

portfolios of written off debt would be sold by tender to

organisations specialising in debt purchase.

One lender was offering portfolios of around £20million

plus for sale several times per year. The price of these

debts would range from 2% to 10% of face value.

Portfolios are often broken down into segmented ‘buckets’

and sold for differing prices, but many lenders expressed

the view that they had little confidence in the pricing

mechanisms for debt. Almost all of the lenders

interviewed expressed an interest in selling debts at an

earlier stage, i.e. pre-write-off. Most lenders that sell debt

take some steps to maintain their ‘brand image’. There is,

of course, some ‘reputation’ risk if debts are sold for

collection by more aggressive or ‘unscrupulous’ collectors.

The role of brokers was beginning to result in some price

uplift.

Debt Lifecycle

Debt Cleared

Bad Event, e.g. divorce

Arrears

Default

Write Off

Reached divorce settlement

Repayments re‐start

Loan Established

Time

Collections Litigation Activity

Chart 4.3.3.1 – Lender Time Horizons



4.3.4. Use of external debt collection agencies for telephone, letter and doorstep contact; litigation

There has been a significant rationalisation of the use of

collection agents and constant performance benchmarking

between agents and between agents and in-house collection

activities. Our previous studies reported that clients were

insisting on having closer contact with collection agents

via integrated information systems. Close monitoring of

the outcomes of placing with agents. More recently,

perhaps due to the pressures of Basel II systems, lenders

are keen to remove delinquent debt from their books via

debt sale (ownership transfer) rather than placing for

commission collection.

Where placement occurs, collectors use in-house and

external collection agents in more sophisticated ways.

Lenders will typically use a panel of around 6 DCAs and

possibly 2 trace and collect specialists for ‘absconders’.

The panel of DCAs will be monitored closely and their

collection success measured. Usually the lender will have

direct access to customer-level information as it is worked

within the DCA. This includes access to all computer

systems and diary records along with collection ‘outcome’.

Complaints against the DCA will also be monitored closely

and may be one criteria (along with recovery rate) by

which debt is allocated to the DCA in then future.

Benchmarking is undertaken to further assess the relative

performance of individual DCAs including the client’s

internal DCA. First placed debt (1st

placement) typically

has a recovery rate of 1-3% of face value. Debt may be

placed a second time if the first placed agency is

unsuccessful. Second placed debt has a recovery rate of 1%

or less. Of course the recovery rate is dependent on the age

of the debt when passed out.

4.3.5. Benchmarking

Benchmarking is now utilised widely in credit management

in order to gauge and monitor the relative performance of

the credit/debt management department. Benchmarking is a

continuous process which involves measuring activities

against other similar organisations in the industry sector,

comparing individual performance against the industry

leaders and comparing internal performance indicators

through time. This process allows the identification of

demonstrably better practice which will lead to measurable

improvements in performance. “Companies must be

flexible to respond rapidly to competitive and market

changes. They must benchmark continuously to achieve

‘best practice’ (Michael Porter, Harvard Business Review,

December 1996).

The quantitative side of benchmarking involves

establishing and defining Key Performance Indicators

(KPIs) that will be comparable through time and across

organisations in the sector. The KPIs measure the

performance of an organisation and/or a function within an

organisation. For debt management departments, for

instance, measures of account delinquency, bad debt levels,

roll rates or aged debt profiles, operating costs, collection

cost per customer or per activity, call centre absenteeism

etc. can be measured periodically tracked over time and

compared with the results of other organisations in the

benchmarking group. KPIs should be continually and

consistently measured across organisations and across

time. The KPIs help to establish internal goals that all

employees in the department can identify with e.g. reduce

bad debt by x% this year. Once the KPIs have been

measured and compared then the relative positions of each

participating organisation can be established. The

benchmarking group can then focus on the qualitative



attributes of the departments processes and practices to

determine what management practices, techniques,

technology employed etc, contribute to the performance of

the ‘best in class’. ‘Best practice’ information can then be

discussed and shared within the group. An important part

of benchmarking is recognising that the data (KPIs) is a

result of processes and practices and that these must be

modified and ‘tweaked’ according to ‘best practices’ in

order to improve performance continually.

“Benchmarking is needed for continuous improvement and

should be an on-going, dynamic process”

The steps involved in benchmarking are summarised

below:

• Decide what the measure (KPIs)/benchmark

making sure that the criteria aligns with the

department mission/goals;

• Measure and document your own performance

historically and going forward;

• Identify the ‘best’ in the industry (or at least an

organisation that is outperforming you in at least

one dimension);

• Analyse and compare results taking care to

establish that the KPIs are truly comparable

between companies;

• Study the practice and processes to establish why

they are a superior performer;

• Implement new practices to improve your own

performance;

• Monitor and measure your KPI’s and start the

process again.

4.4. Summary

The picture then, is of large organisations setting up

sophisticated customer focussed operations aimed at

'reforming' debtors, if possible, so that the relationship with

them can continue and generate future profits. This has

been partly a response to increased competition amongst

lenders, the emergence of 'consolidation companies' and

recognition that changing life-styles and patterns of work

have precipitated periods of 'over-commitment' by debtors

which need be managed longer-term. Collection cycles

have become much shorter in financial services but opened

opportunities for debt buyers. Basel II rules has resulted in

reclassification of debtor portfolios in financial services

with the development of new default probability models.

The centralisation of collections activity in organisations

may produce an environment in which more sophisticated

decision support systems including statistical and

propensity models, such as behavioural scores, can be used

to formulate the most effective collection strategies by

encapsulating the company's previous experience of what

works and creating variability in collection sequences.

The introduction of enterprise wide data sharing has arisen

because of the emphasis being placed on having a

'customer-level' view and detailed management

information systems. The expansion of closed user groups

in the UK means that firms have access to better

information on other lenders experience of a debtor, and

can include this in their decision making process. The

differences in information costs of in-house and out-placed

debt collection are thus reduced.



Sophisticated credit management in-house will inevitably

reduce the 'quality' or 'collectibility' of debt that is out-

placed. Many debts passed to debt collectors will already

have been through telephone and letter based collections

procedures, and may even effectively have already been to

one debt collector, if the company has a debt collection

subsidiary. It may be that such firms will only want to

make use of a sub-set of the debt collectors service which

they cannot provide for themselves, for example, door-step

collection.

As well as the obvious affect of making it more difficult to

make a profit with charges based on the value of debt

collected, this decrease in the 'quality' of debt may further

impact on the competitiveness and efficiency of the

'external' debt collection industry. The larger debt

collection operations that have traditionally taken the bulk

of their business from the banks and credit card industry

have in the past been able to develop scoring systems

based on their own history of recovery and bad debt write-

offs. The development of scoring models however, requires

that the data sample, based on a history of account

experience, have sufficient variation between 'good' and

'bad' accounts. The move towards more sophisticated

collection systems by the credit providers has meant that

the type of debt that is eventually passed on to debt

collectors is debt that has already been worked and is likely

to be skewed heavily towards the 'bad' end of the debt

spectrum. That is, there is insufficient variation in the

quality of debt coming through their books to permit a

meaningful statistical analysis and predictive modelling.

Effectively the client companies are reducing the

information content of the data by making use of it in their

own behavioural models prior to outsourcing.

A trend towards using fewer agents with closer contact and

integrated information systems suggests that there will be

fewer/larger and more sophisticated collection agents in the

future.

4.5. Short Case Interviews 2007

During the spring and summer of 2007, a series of

interviews were carried out with major lenders involved in

the banking, mortgage and credit card sector with a view of

updating our case studies on the trends in collections and

recoveries and soliciting opinion on the current position

and expectations. Interviewees were asked to comment on

the level of indebtedness in the UK and the risk factors.

4.5.1. Collections Department: A Medium Sized Bank

The collections department of the bank handle debt from 3

products: credit cards, personal loans and current accounts.

Mortgages and commercial lending are handled by a

separate unit.

The collections unit is undergoing some change in order to

develop a full ‘customer view’ since the data-bases are

currently organised by product. Collection is undertaken

via a call centre inclusive of 150 seats and an in-house debt

collection agency (operating with a different name to the

lender). A pre-delinquency team attempt to identify cases

showing signs of delinquency and contact via call centres

may be made in order to take preventive action or give

advice.



The reasons cited for non-payment are over-commitment

and a changing attitude towards debt. The appears to be

less stigma attached to debt and debtors are better informed

about their options and are aware of how long it will take

to ‘buy time’ Rate of interest rises are having an impact on

arrears and IVAs. As a result, accept rates are being

tightened as are credit limits.

Debt that arrives for collection is segmented (strategic

segmentation) according to risk (high, medium, low) and

outstanding balance and each case will be allocated with a

call and letter sequence. The segmentation is informed by

behavioural scores using CRA and in-house data. Around

50% of cases do not have a accurate telephone number.

Debt that is 100 days old is sent to the internal DCA.

Champion challenger is used and being developed

alongside activity based costing. There has been

investment in telephony and alternative contact methods,

e.g. SMS to generate inbound calls and Interactive Voice

Response (IVR) systems. Outbound IVR is also used to

verify transactions when fraud is suspected. Collectors do

not get cash bonuses.

The emphasis of early collections is to educate the

customer and achieve payment. Call centre collectors can

take payments by debit/credit card; direct debit, etc. If a

promise to pay is achieved then a follow-up will take place

within 7 days. The customer will be warned about late

payment charges where applicable. If there are 2 missed

payments (60 days) a default notice will be issued and

logged with the CRAs. Individuals that are identified as in

financial difficulty are referred to counselling and a ATP or

payment plan will be negotiated. An external partner is

used to manage any IVAs with more effort being placed on

maximising the returns and trying to get customers to

establish ATPs internally. After 100 days, the debt is

passed to the internal DCA and a more manual and skilled

process is initiated. Tracing may be used at this stage.

There is an internal litigation team and they are

experimenting with litigation scoring. Litigation is used to

recover debt and/or achieve charging orders. After 180

days the debt is written-off and placed with an external

DCA- a core of 4 DCAs are used. Commission is 10% on a

first placement and 20% on a second placement. The

internal DCA is benchmarked against external DCAs and

roll rates are monitored.

At the moment, only small volumes are sold and are

usually debts that are 360+ days old. The price is generally

around 2-4p in the £. The problem with debt sale is the

pricing issue for debt at different stages and the data

required for pricing

The main developments are using scorecards to determine

collection paths; analysing recovery rates against the costs

of activities; control over IVAs; increasingly automated

early collections with IVR technology; focussed and

segmented collections.

4.5.2. Commercial Credit Card

Corporate credit cards are split into merchants (card

acquiring) and card issue (company cards). Merchants

receive commission on credit card sales and charge backs

through purchasing. Company cards are used primarily for

expenses of key personnel in the company. The majority of

customers are referred to the credit card division via the

main bank (70%). Large accounts with credit limits in

excess of £300,000 are assigned an account manager.



The management of card accounts is highly automated.

The card portfolio is categorised by trade and risk with risk

scores generated using an external CRA. Security may be

requested against risky credit limits. In house behavioural

scores are used to monitor credit limits and pick up

fraudulent transactions. The behavioural scores use

external CRA data, the bank branch networks and ccj

information to update risk scores. Scores are used to

measure risk and detect fraud.Where possible, customers

are signed up to direct debit payments. The merchant side

of the business has a revolving debt book of around £10.1

million with around £2.6 million written off in 2006 and

£5million recovered.

An account that misses a payment or direct debit is

segmented into a category based on risk score and balance

outstanding along with analysis of the reason a DD was

returned. Contact with the customer is made within 3 days

with a phone/letter combination. Merchant card debt is not

always clean because of charge-backs and will involve

specialist knowledge from the collectors. The internal

collection team operate a small scale call centre with debts

of more than £200 being referred to in-house debt

collection if initial contact is unsuccessful. The merchant

side has an internal investigation agency that may use visits

in order to assess the appropriate actions. Legal action such

as charging orders and baliff services are used as recovery

strategies. If charges on assets and other legal enforcement

is unsuccessful then the debt is written off and passed to a

DCA. The merchant side has a problem with fraud with the

merchants often being the victims of fraud. The nature of

insolvency has changed with more cases of CVA’s being

encountered with rates of recovery versus costs worsening.

Company cards include credit cards, charge cards and

business cards. The interest rates are variable but more

work is being undertaken to price risk across the portfolio.

Fraud losses have been reduced through chip and pin

(although foreign ATM’s often don not use chip and

pin).Cloning and organised fraud is still a problem. The

company card operation utilises the services of DCA’s

early in the collection process. Three DCA’s are used in

competition. Debts of greater than £10,000 will be

investigated by an internal team. Debt sale is not common

but around £150,000 of corporate card debt was sold in

2006. Bad debt write-offs have been reduced as a result of

improvements in application scoring and risk scoring and

more sophisticated use of credit limits. The improvements

in and automation of collection systems has resulted in

lower bad debt provisions.

4.5.3. Consumer Credit Card

A step shift in the approach to collections occurred as a

result of large increase in delinquency, arrears, cases being

referred to debt management organisations and

bankruptcies during the period after January 2005. A task

force was set up in order to re-examine the quality of the

lending book and the collection strategy. There appeared to

be problems in every risk sector (bucket) of the portfolio.

New debt management software was commissioned around

this time at a cost of over £25 million. The problems with

the portfolio were linked to over-indebtedness of the

customer base and a mis-classification of customers into

risk buckets i.e. prime, near prime and sub-prime. This

resulted in the collections having no clear picture of

indebtedness and risk. Repayment plans and delinquency

continued to increase to March 2005.



A number of trends emerge. A scoring system has

reclassified customers and the collection process is moving

from being a ‘event-driven’ process to a ‘time-driven’

process with more sophisticated management information

being used to report daily on the level of delinquency.

Lenders are under more pressure to reduce the number and

value of debts over the 90 day range as a result of Basel II

rules. This in practice has led to re-aging of debt if the

customer can make some payments if not the full balance.

The operation has made considerable investment in the

collection process in terms of debt management software,

telephony and scoring systems. Attempts to generate a

data-base that gives a full ‘customer view’ have not been

completed but are in progress. This has had an impact on

the sophistication of scoring which, it is believed requires a

customer level view in order to benefit collections.

Collection strategies and champion-challenger techniques

are used throughout the collection stages. Collection staff

are motivated by incentives and bonuses based on £’s

collected, number of accounts processed. Bonuses are paid

to teams on the basis of performance against collection

forecasts and to individuals on the basis of relative

performance in the team. Collectors are organised by a

classification of debt types and stages in the process.

Collection staff have discretion to negotiate with the

customer on re-aging and ATP’s

Call centre activity has been moved overseas including

South Africa, the USA and India. DCA’s are used with a

core of 5 being selected (including a DCA in the USA).

Call centre work requires more sophistication in targeting

calls because there are diminishing returns to call centre

activity. The objective is to increase the penetration rate on

dialling and combined with activity based costing work out

optimum penetration rates. Scoring is becoming more

sophisticated with a move to develop recovery scores and

assess the NPV of ATP’s. Debt is allocated to in-house and

external DCA’s and to debt sale. Commission rates are in

the region of 10-12% and debt is old for around 1-2 p in

the £. The level of trust in the debt sale market is not high

due to pricing uncertainty. There has been more activity in

door step collection.

IVA’s and bankruptcies are on the increase and the

company are developing a strategy to deal with IVA’s that

balances increasing returns with keeping the IVA from

failure. In card default cases the company is now more

likely to seek a charging order on any assets of the

customer via the county court.

Fraud continues to be a problem with ‘card not present’

causing the biggest challenge. Application and other fraud

has been countered with chip and pin.

The challenges for the future are to increase revenue;

develop more accurate risk scores, collection scores, ‘self-

cure’ scores and debt pricing mechanisms and close

dormant accounts. The development of ‘self-cure’ scores,

roll rate scores, write-off and recovery scores are all being

investigated. It is recognised that scoring systems play an

important part in determining optimum collection

strategies and fast track accounts through different

collection paths. There is now a preference to keep as

much of the process in-house as possible. There is

recognition that external CRA data is of better quality and

more comprehensive.



4.5.6. Medium Sized Retail Bank

The bank has a full range of financial products 50% of

which are internal and 50% offered via third parties (e.g.

credit cards). Internally offered products are current

accounts, personal loans and mortgages. 65% of mortgage

business is generated by brokers and 50% of personal loans

via the internet. A large proportion of new customers do

not have an existing relationship with the bank.

Application scoring has evolved to include an

‘affordability’ model in order to minimise over-committed

customers. The model uses share data to estimate gross

income; living costs and total debt (CRA debt

information). The bank will decline applicants if the model

predicts a debt servicing problem. At the moment the bank

perceive that only a small number of households in their

portfolio are struggling but lending has been tightened,

particularly to younger age groups. The main reasons cited

for non-payment is financial mismanagement and over-

commitment. That is the debtor profile is an individual

with an income and possibly property but problems with

debt servicing. Arrears levels are now more sensitive to

economic conditions and interest rates, a sign of fragility.

The biggest perceived risk for the future is a house price

‘correction’ and a growth in the culture of bankruptcy and

IVA’s . Currently around a third of IVA’s fail and the

others generate a return only after 2-3 years. Fraud losses

are increasing, especially ‘soft fraud’ (fraud that is not

classified as such). Compromised credit and debit cards,

identity theft, card ‘not present’ fraud and cloned cards

used abroad (i.e. not chip and pin) are all areas of concern.

Mortgage fraud is high, particularly associated with inner

city new builds. This is likely to be organised fraud. The

buy to let market is an area subject to fraud. Incentive

payments to customers that are not divulged to the lender;

overvaluation of properties, off-plan properties sold but

never completed; re-mortgaging scams are all examples of

the latter frauds.

Payments on the loan portfolio are all paid by direct debit.

If a DD is unpaid the debtor will receive a letter-phone

combination of contact in order to get payments up to date.

If a loan remains unpaid for 90 days it is passed to an in-

house DCA who will spend 2 weeks trying to establish a

repayment pattern. The debt will then be passed to a broker

who sends it to DCA’s on a commission based collection

path. The broker receives 21% commission. Debts will be

written off after 6 months and sold to debt buyers via the

broker.

The collections operation has increased both in scale and

sophistication. Roll rates and arrears have been increasing.

A behaviour score and balance determines the collection

path of a debt. Champion challenger analysis informs

further segmentation. Collection staff have doubled in size

and the company has invested in debt manager software.

Debt is rescheduled on the unsecured portfolios where

possible



4.6. Large Volume Collections: Interview Survey 2003

During the period May to July 2003 interviews were

arranged with the major lenders that have contributed to

this study over the past 5 years along with some other

major financial institutions participating for the first time.

The expectation prior to the 2003 survey was that there

would be some changes in practices but these would be

incremental rather than radical. However it was soon

apparent that some quite radical shifts in the organisation

of collection and recovery functions had occurred and that

collection strategies and approaches to the customer had

also shifted quite noticeably. These changes are reflected in

the updated case studies and comment presented below.

The main shifts in collection strategies were as follows:

(1) There has been a movement towards early detection of

delinquency and earlier and repeated contacts with the

customer in order to establish any problems and

rehabilitate the account back into ‘order’. The cycle from

early arrears to write-off has become much shorter but

accounts and debts ware worked ‘harder or more

aggressively in the early stages. A typical example of

escalation of actions is presented in figure 2.15. The point

0 represents accounts that are up to date and in order.

Accounts in early arrears are contacted in 4 ‘delinquency

cycles’ both phone and letter combinations. The early

cycles are geared to identifying problems, gaining

customer level information, prompting for payment and

reaching ‘reasonable’ agreements with the customer. Such

arrangements will be geared to getting the customer to pay

the arrears in full or establish promises to clear arrears

within a relatively short period of time.

4.6.1. Delinquency Cycles

After delinquency cycle 4 (i.e. 3-4 missed payments) the

account may be passed into a collections/recovery

environment. This will also include customers who have

‘broken promises’ or failed to respond. This usually

involves a name change for the customer. The

correspondence will now come from an internal Debt

Collection Agent that goes under a different name from the

lender or from an internal solicitor. At this stage a default

notice will be issued. Thus debts are being escalated

quicker into a default and recovery situation. The emphasis

will now be on recovering arrears through repayment plans

which may be longer term and recover lower proportions

of the outstanding debts. Some lenders do NPV type

analyses to establish whether it is more beneficial to

negotiate a settlement involving a lump sum payment (a %

of the total outstanding) as opposed to low monthly

repayments over a longer period. This activity is clearly

more suited to the financial services sector than the

utilities. There is a considerable amount of debt

rescheduling taking place amongst the large lenders in

order to rehabilitate customers. The default rate on

arrangements to pay (ATP’s) is less than 12%. Again at

this stage considerable effort will be geared to establishing

contact via phone, free phone-in, text message etc and to

gaining information on the debtors’ employment,

circumstances, financial and ‘asset’ position. Establishing

whether the debtor has employment and assets is important

in determining decision regarding litigation.



After a number of delinquency cycles the debts will then

be passed on to external debt collection agents and may be

placed a second time if the first DCA is unsuccessful. At

this stage the debt may also be written-off and sold. The

whole process from early arrears to write-off will take less

than 9 months. One lender ‘charged-off’ debt at 90 days.

That is the debt is passed on to external collection after 90

days delinquency.

(2) There is more use of ‘behavioural’ and ‘collection

scoring’ to segment customer-bases and determine the

escalation process for each debt i.e. debts may not all pass

through the same sequence of actions. In order to be

effective these collection strategies have to be monitored

and tested continually in a champion-challenger

environment. New strategies based on customer risk

profiles and ‘propensity to pay’ scores are implemented

and monitored to establish possible sources of cost saving

and efficiency in collections activities. Activity-based

costing helps to establish the cost-return trade-off for each

collection activity. That is, monitor and measure the

‘success of actions’ against the ‘cost of actions’. The

emphasis is on ‘working smarter’.

Activity-based costing is an area where most lenders were

aiming to implement. As one collection manager

commented, “we need to know more specifically what

action generates what return and the cost of each action.

At the moment we know the cost of broad areas of actions

and can evaluate their cost effectiveness but we need to

drill down further whilst avoiding ‘paralysis by analysis’.

(3) The ‘timing’ of actions is deemed to be very important

and lenders are researching the impact of varying

delinquency cycles. There is recognition that ‘debt resting’

may be an appropriate strategy for certain accounts. If a

low risk customer has been affected by an unexpected

‘event’ such as divorce or employment change then it may

be more cost effective to allow the customer to recover

his/her financial position before collection action is taken.

(4) Increasingly lenders as well as working early

collections more intensively attempt to identify customers

that may be heading for financial problems. Certain types

of behaviour triggers may prompt a call to the customer to

try and pre-empt any problems. For instance a customer

with a change in the pattern of spending such as an

increases in payments going out of the account, new direct

debits or standing orders etc.

Account management Internal Debt Collection External DCA Write-off Debt Sale 0 1 2 3 4 5 6 7 8 210 Days Late Payment Penalties Imposed Account in order

Delinquency Cycle Recovery Cycle

Chart 4.6.1.1 – Delinquency Cycles



The customer may be contacted by the lenders ‘money

management service’ in order to help the customer evaluate

the level of indebtedness and take actions or restructure

finances in order to prevent future difficulties. Lenders are

thus being more proactive and attempting to assess the

customer’s ‘total indebtedness’ or broader financial

position before identifying a ‘solution’.

(5) An increased emphasis on generating customer-level

information in order to improve the contact rate with

customers i.e. phone and mobile numbers, email addresses

etc and information on any changes in customer

circumstances, employment, behaviour, indebtedness with

other lenders and products.

(6) Collection and account management staff work more

flexibly in terms of hours and activity. Collection staff are

less likely to be specialists are certain delinquency cycles

but work across all cycles. As one financial services

organisation commented, “we are now driving out

specialist teams, the collection process is the same no

matter which route the debt is coming in from. Collection

and recovery shouldn’t be a fragmented set up”. Collectors

will have the discretion to negotiate arrangements to pay

and promises. Collection staff will be monitored on their

performance, particularly the collection rate or £’s

collected per hour/month etc. Solutions negotiated and

promises kept may continue to be monitored but the

emphasis has shifted to cash targets. One lender produces

league tables of the collection rates of every individual

collector and pays bonuses on league table positions.

Another lender has a ‘balanced scorecard’ for measuring

and monitoring collection staff on an individual and team

basis. The formula includes measures such as income

recovered per hour, percentage of time on and off the

phone, ‘solutions’ impact. Some lenders award cash

bonuses based on collections performance others hold

competitions for best collections performances and award

non-cash prizes.

(7) Call Centre and Collection staff undergo a significant

period of training in negotiation, customer relationship

management and collection/recovery skills. Most enders

suggested the period of training lasted up to 6 months

before a collector had sufficient skill/knowledge to work

cases independently. Training was both formal class room

and on-the-job using a ‘buddying’ approach.

(8) The use of Debt Management services by customers

with debt problems has been increasing. Many customers

will seek the advice of the Citizen’s Advice Bureau,

national debt line etc and/or allow a fee charging Debt

Management organisation to negotiate payment

arrangements with all of the customers’ creditors. Another

approach would be to seek a ‘consolidation loan’ from one

of the many organisations that advertise these as a ‘way out

of debt’. One lender revealed that out of 300,000 live

‘collections/recovery cases they had over 20,000 customers

making repayments via a debt management organisation.

This represented an increase of 3000 debt management

cases in one year. Another lender indicated an increase in

debt management cases of 200% in a period of just over 2

years. Consolidation loans or arrangements to pay may

extend the period for re-payments up to 20 years. Most

lenders suggested that they were taking a ‘harder line’ with

debt management and negotiating on repayment plans. A

figure of 2% recovery per month from ATP agreements

was cited as the target.



(9) Most lenders will use external debt collection agents

(DCA’s) along side their internal DCA. Usually debt will

be out-placed to external agents after having been through

the entire process internally. Thus the debt will have gone

through the collection cycle, internal DCA/solicitor and

then be passed externally if there has been no success. Few

of the large lenders undertake any litigation internally

unless it is clear that the borrower has some worth i.e.

assets/regular income stream. Some lenders will often do

tests and litigate a sample of say 500 accounts in order to

evaluate the success rate and cost effectiveness. Recovery

rates are around 2-3% of balances from litigation.

Litigation, however, may be an option in the recovery

strategy for external agents. In practice few external

DCA’s litigate to recover debt but use letter/phone cycles

and ‘doorstep’ collections or visits. The latter can be useful

in gathering further information about the debtors’

financial position and assets. Most DCA’s will, however,

threaten litigation as a recovery strategy. Most large

lenders will have a ‘service level agreement’ with the DCA

that sets out they type of approaches that the DCA can use

to recover the client’s debt. All of the DCA’s processes will

be vetted. This is designed to protect ‘reputation/brand’.

DCA’s will usually receive a significant amount of

‘customer-level’ information and risk scores or ‘charge-off

reason code’ in order to inform their recovery strategy.

This, however, means that the lender has a ‘cost’ associated

with ‘servicing’ the DCA arrangement and may evaluate

this in future when making decisions about ‘out-placing’

versus ‘debt sale’. Some use a ‘scoring model’ to decide

whether to ‘place’ or ‘sell’.

Lenders will typically use a panel of around 6 DCA’s and

possibly 2 trace and collect specialists for ‘absconders’.

The panel of DCA’s will be monitored closely and their

collection success measured. Usually the lender will have

direct access to customer-level information as it is worked

within the DCA. This includes access to all computer

systems and diary records along with collection ‘outcome’.

Complaints against the DCA will also be monitored closely

and may be one criteria (along with recovery rate) by

which debt is allocated to the DCA in then future.

Benchmarking is undertaken to further assess the relative

performance of individual DCA’s including the client’s

internal DCA. First placed debt (1st

placement) typically

has a recovery rate of 1-3% of face value. Debt may be

placed a second time if the first placed agency is

unsuccessful. Second placed debt has a recovery rate of 1%

or less. Of course the recovery rate is dependent on the age

of the debt when passed out. One lender suggested that

their DCA’s often recovered up to 6%. Normally debt will

be 120 days overdue by the time it gets to an external agent

but this varied from 90-270 days in our interview sample.

Given that the lender works the debt intensively in-house

prior to out-placing it is surprising that DCA’s have any

success at all. One lender suggested that external DCA’s

still manage to collect because of (1) a further change of

name (2) a different approach to collection and more threat

of litigation (3) because of ‘timing’ i.e. by the time the debt

reaches the external DCA the customer may have had a

chance to recover their financial position. This is

particularly the case for individuals who have had a sudden

change of circumstance e.g. divorce, unemployment etc.

(10) Debt sale is on the increase and all the lenders that

were interviewed were actively participating in the debt

sale and purchase market. Debt sale was usually

undertaken post-write-off .Usually debt would be written-

off after being out-placed once or twice unsuccessfully. At

this stage portfolios of written off debt would be sold by

tender to organisations specialising in debt purchase. One

lender was offering portfolios of around £20million plus



for sale several times per year. The price of these debts

would range from 2% to 10% of face value. Portfolios are

often broken down into segmented ‘buckets’ and sold for

differing prices. Almost all of the lenders interviewed

expressed an interest in selling debts at an earlier stage i.e.

pre-write-off. Most lenders that sell debt take some steps to

maintain their ‘brand image’. There is, of course, some

‘reputation’ risk if debts are sold for collection by more

aggressive or ‘unscrupulous’ collectors.

4.7. Case Studies 2003: large volume collection activities

4.7.1. Case A: Debt Recovery Division of a Major Bank

As a result of the major re-structuring of the customer

service/collection operations a leading bank established a

Debt Recovery Division approximately 4 years ago. This

was seen as a continued trend towards centralisation in

collections to exploit economies of scale. The division acts

as collectors for all the sections of the bank and for all

financial products, predominantly unsecured debt. The

bank has introduced a counselling service to counteract the

flight of customers to money advisors and debt

consolidation businesses. This is promoted as a ‘money

management service’ and is designed to identify possible

problems and resolve them to prevent the customer being

passed into recovery i.e. it is pre-emptive. However if the

relationship with the customer breaks down the account

will be passed to DRD i.e. 3+ arrears, no contact, broken

promises.

The purpose of the DRD is to maximise recoveries at

minimum cost. The emphasis of this division is on

recovery not customer retention and therefore the approach

to the customer is firmer in collection actions and in

establishing whether the customer has assets and an

income stream. The debts are worked intensively, by the

relevant customer service/account management teams,

prior to being passed to the DRD. The focus of the DRD

team is 'the customer' rather than the product where the

debts occur.

Thus the Debt Recovery Division receives for collections

action unsecured debt that has been deemed by their

internal clients to be non-rehabilitable i.e. where the

customer relationship has irretrievably broken down

(missed 3-4 payments) and the sole objective is now to

collect the debt. Thus the recovery team receive debt from

fixed term loans, overdrafts, variable period/rate loans,

credit card debt, secured consumer loans, secured and

unsecured business loans and trade debt. Debt values can

range from £25 up to £1m+. The average values are in the

region of £1500 to £4000 and are between 90 and 150 days

old prior to being passed into recovery. The team currently

handles around 300,000 live cases with approximately

20,000 new cases per month. Total balances outstanding

are in excess of £700 million of which around £10m per

month is recovered.

The department comprises of over 130 staff including 80

recovery staff, 20 qualified legal staff and 30 support staff.

All staff are trained in collection techniques,

communication and negotiation skills. The objective is to

be the creditor that makes the 'best first contact' with the

debtor. A bespoke debt recovery IT system is used in

conjunction with a solicitors software package (an

automated time recording, billing and case management

system). Collection strategies are undertaken through

different trading styles i.e. the use of 'in-house' agents

trading under a different name to the bank and in-house



solicitor companies. This 'separateness' from the bank is

considered integral to the effectiveness of the debt recovery

operation. Up to 7 different names are used to approach the

customer.

The recovery staff attempts to recover debt through single

settlements or through an agreed instalment plan. The

collection strategies include the use of predictive diallers,

interactive voice response, and automated lettering (under

the different trading headings). An escalation process is

adopted to reflect the severity of the non-payment

situation. Where repayment is not effected via early contact

and it has been established that the debtor has assets, then

litigation may be pursued as the primary recovery route.

Any repayment plan that is negotiated has to take account

of the reality of the debtor's financial position and ability to

pay. Debts are segmented by type and debtor

characteristics and the appropriate collection/recovery

route is then ascertained. Debt characteristics might

include: source of debt, debt size, time since last payment

etc and debtor characteristics might include: age of debtor,

employment, homeowner, telephone, extent of

indebtedness etc. Credit reference information is available

on-line to support decision-making.

Champion challenger approaches are used to identify the

optimum recovery processes. Thus letter text and telephone

scripts, frequencies of letters/calls etc are varied to identify

the most effective process relative to the debt and debtor

type. Activity-based costing is used to monitor actions

against recoveries in order to optimise the cost/recovery

ratio. A document imaging system is being introduced in

order to track customer contacts on-line. It is envisaged

that the use of the internet in collections will take-off in the

future and fundamentally change the

economics/approaches to collection. Behavioural scoring is

used to guide strategies and segmentation. There is an

intention to make more use of 'debt surveillance' i.e. taking

no action until the debtors' financial circumstances change

and the use of debt sale to external agents. A problem for

collectors is the use of 'death' as an excuse for not paying.

This is a sensitive issue and collectors have to be careful

when verifying the death of a customer/debtor i.e. Death

Certificate as proof. The success of DRD has led them to

experiment with collecting debts on behalf of other

organisations rather than being an exclusive operation for

the bank i.e. to act like an external agent.

In-house tracing of debtors is undertaken although external

agencies are used on a trace and collect basis.

External agents are used increasingly on a trace and collect

basis when in-house processes have proved to be

unsuccessful. Up to 10% of all accounts that have been

referred to DRD are placed directly with external agents

without any recovery activity. This process allows the

DRD to monitor its own performance against the external

collection agents. The policy is to use only 'four of the

largest and most effective UK agents'. The performances

can then be used for benchmarking internal processes.

Agents have to sign a strict Service Level Agreement

aimed at protecting the bank's image.

New business is allocated to external agents on a

percentage split based on how they have performed over

the last 3-6 months, the better the agent performs the

bigger percentage they receive. Accounts are taken off

agents after 6 months if they have not received any

payments. However the accounts are then transferred to

other agents for a further 18 months making 24 months in

total. The agents are paid a commission on successful

cases. Most of the agents use a field force for doorstep

collection.



In summary, "each of the style and methods used within the

collection process are different and unique, and are very

deliberate in terms of attempting to convince the debtor

that due to their continued non-payment, their situation is

becoming more serious".

The Company does not sell debt and rarely uses litigation

as a recovery option. Litigation is used very selectively and

judgements are enforced by attachments of earnings,

charging orders and warrants of execution.

4.7.2. Case B: Credit Card Provider

Company B, a major financial services organisation which

has over 10 million and runs a centralised collections

facility which also handles accounts which have exceeded

their credit limits and looks at accounts in these areas for

signs of fraud. The department has its own 'in-house'

collection agent that trades under a different name from the

bank and uses external agents for collection. They have

recently rationalised their use of agents to 6 'best in class'

collection agents. At any point in time approximately 1.8

million accounts will be delinquent (overdue by at least 1

day).

The company has recently replaced their computer systems

with a new system jointly developed with a commercial

partner, this is a 'customer service' system rather than a

collection system. The Company has also implemented

Fair, Isaac's TRIAD. TRIAD is used predominantly as a

customer relations management tool rather than a

collections tool. They have introduced software for late

collections (’Debt Manager’). The Company develop,

research and implement scoring methodologies and are

constantly re-appraising scoring methodologies for account

applications, fraud and collections in the context of their

developing systems. Scoring is currently used for

application processing, authorisations, collection scoring,

behavioural scoring and recently a propensity to repay

score has been developed.

There has been an increased emphasis on the customer

assistance element of customer management. Customers

going into arrears are kept within the CRM system and

staff attempt to negotiate and manage 'solutions' with the

customer. This is aimed a rehabilitation and gradual

progression into good payment habits. The emphasis in

recent years has switched to a ‘US style’ of collection

where staff are incentivised to ‘collect cash’ and league

tables of collections performance are produced, monitored

and bonuses allocated on the basis of collections. Staff can

receive bonuses up to £9,000 per annum on the basis of

cash targets and ‘promises kept’. CRM staff are trained to

recognise that delinquency may only be temporary and that

customers should be retained in the CRM system if at all

possible. Passing the debtor to collections usually marks

the end of the customer relationship. Thus the focus of

CRM is to understand the reasons that an account is out of

order and implement a strategy to return the account to

order. Different strategies are adopted with the debtor

based on behavioural scores and age and size of debt.

CRM staff have a tool-box of solutions; defer payment, re-

age the account, establish a repayment programme, change

credit limits. The process could keep the account in the

CRM system for 6 months before collection activity is

implemented. Work is being undertaken to develop an

intelligent agent that automatically suggests the 'best'

solution for a customer. The company use segmentation

and champion challenger strategies in CRM management.



Major trends in the last 3 years have been (1) focus on

gaining contact early (2) increasing contact rate through

accurate phone number, mobiles (3) use of text messaging

to ask the customer to phone in (4) more resource put into

collection activity (i.e. staff). (5) an emphasis of evaluating

actions versus recovery and researching the optimum

‘timing’ of actions. (6) taking a harder stance with debt

management organisations in negotiating repayment terms.

The company currently uses a collections management

package to control the collection process, an in-house

system for the Recovery section and a litigation package

(Debt Manager). The litigation package will take care of

standard paperwork such as the issuing of warrants,

thereby leaving the collectors free to deal with exceptions.

The objective of collections is 'to collect out as much as

cheaply as possible'. There is almost no use of litigation

with a preference now for 'debt surveillance' the use of

agents and 'debt sale'.

A power dialler is used for outgoing calls and a telephone

management system is used for incoming calls. This

system provides on line statistics on productivity. Queues

are managed by scoring systems.

The company has made significant investments in the MIS

system i.e. 'we have invested heavily in measurement'. The

key to success is regarded as measurement, learning and

knowledge. Solutions versus outcomes are monitored and

reported on. Performance drivers are identified and

monitored The monitoring of champion challenger

strategies has become more sophisticated. The front end to

the reporting system is customised, offering department

specific options. Managers can view budgets, actual profit

& loss figures, productivity, staffing reports and exception

reports. Reports such as profit & loss accounts versus

budgets can be viewed at different levels (e.g. cost centre,

nominal account) allowing the user to go to the level of

detail they need on a particular query. The MIS department

has developed desktop macros to perform routine tasks.

This has led to a significant reduction in the number of

staff needed for routine work.

Collection is split into two main sections; customer

assistance (Credit) and late collections (internal debt

collection agency). Supporting the activity is a Business

Improvement team that provide management information,

implement and test new strategies. Problem accounts are

now detected much earlier that a few years ago and

solutions put in place. After 4 collection cycles the account

will be passed straight into the internal collection agents

processes.

The Power Dialling section usually makes the first

attempts to contact the customer in the early stages of

arrears, although it is also being used in mid range arrears,

tracing gone-aways and providing "welcome calls" to new

account holders. Operators work part time on 4 hour shifts

with break time allowed. Working the power-dialler is seen

as an intensive job that cannot be maintained for long

periods. The working mode also fits well with the pattern

of hit rates for call connection. The aim at this stage in

collections is to manage the customer not the debt.

Customers are now encouraged to 'phone-in' using a free-

phone number to discuss arrears positions.

The section does make use of agency staff and recognises

that with permanent staff there is a balance to be found

between the quality of staff and the length of time they are

likely to stay with the job. New staff are given a 12 week



training course followed by ongoing training sitting with

an experienced collector and training in the collection

system. The section has supervisors and floor walkers who

are able to provide assistance with lengthy or difficult calls,

although there has been a trend towards a lower number of

supervisor referrals over time.

Outbound power dialling is usually done in the evenings

between 6 and 9 and on Saturday mornings. Daytime calls

are made using the account holders work number and

evening calls using the home number. On being connected

operators are given an initial screen of account information

which includes the last two actions taken with the account,

and the operator can bring up other information including a

full diary of contact as necessary, solutions and promises.

Emphasis is being placed on collecting data on customers

through this process and providing assistance staff with a

'customer-level' view.

Although the Power Dialling section try different strategies

on calls, the current system gives them no way to track the

results of their strategies automatically. The new systems

being implemented have improved this situation so that

actions and responses can be tracked.

The focus of customer assistance is managing the customer

not the asset. Customers are segmented according to the

type and age of arrears and approached with different

strategies based on 'balance and behaviour score'.

Behaviour types are also treated differently in the 'contact-

pay' environment.

Interpersonal skills are a key competency in this area, as

staff need to negotiate with the account holder. The

emphasis is mainly on individual collector judgement in

this section, although the supervisors can monitor collector

performance through the MIS system. One aim here is to

get the accountholder to see the Company as the preferred

creditor, i.e. the one they will pay first. Some

accountholders pay cards bills first in any case, so that they

can retain their credit card. A main aim here is to limit the

loss to the business, either assisting cardholders in keeping

to a repayment plan perhaps by reducing or stopping

interest, or if a repayment plan cannot be achieved, to

decide the most effective method of recovery.

A new member of staff will be learning the role over a

period of up to 6 months, although the exact time is

dependent on the individual collector.

Collectors use TRIAD for champion/challenger strategy

trials.

Once an account has reached a position where solutions are

not being kept it will move into the in-house debt

collection agency, although the route taken by an

individual account depends on the collector's judgement.

The 'in-house' agency is a wholly owned subsidiary with its

own registered company name. The use of the agency,

giving the impression to the customer of external

involvement in the debt collection process, is seen as being

extremely effective. The company also use 6 external

agents and benchmark their performance against the in-

house agent. Debts are allocated outside on the basis of

recent performance. Monthly performance statistics are

monitored closely.

The Company is looking to use debt sale more in the future

on earlier stage delinquencies.



4.7.3. Case C: Large Volume Lender- Retail Card, Personal Loans

Company C offer three types of product; a retail

chargecard, unsecured personal loans and a reserve

account. The average delinquent balance of a personal loan

account (£6,500) is significantly higher than those on card

accounts (£800) and this can influence the strategy for

dealing with arrears in the different account types. The

company deals with around 2.5 million active accounts and

has over 50 million account records. Like many retail cards

the company find that customers use this as a last resort

borrowing facility and delinquency has risen. However,

recover income as a percentage of arrears has grown in

recent years as a result of restructuring collection processes

and strategies. The approach has become more aggressive

in timing and collection effort in early stage delinquency.

Accounts are charged off into collection/recovery after 90

days arrears.

A number of computerised systems are used to manage the

accounts from application time through to collections, as

illustrated below. The system is highly automated to deal

with high volumes of accounts with automated inbound

procedures and predictive dialer outbound.

Company C use packaged systems supplied by Experian (a

major credit reference agency). An application processing

system is used to process applications for credit with

accepted applications being passed to the account

management system. The account management system

monitors for various types of delinquency, including going

into arrears and cardholders exceeding their credit limit.

Behavioural scores are produced for accounts on a regular

basis, and these are used in areas such as setting of shadow

limits (the maximum credit limit an account would be

allowed), processing credit limit changes and deciding

strategies for dealing with arrears.

C A R D P A C- A c c o u n t

M a n a g e m e n t

A U T O S C O R E- A p p lic a tio n

P ro c e s s in g

T R IA D- B e h a v io u ra l

s c o rin g /s tra te g y

O L C (O n lin e C o lle c tio n s )- C o lle c tio n s

M a n a g e m e n t

Chart 4.7.3.1 – Computer Systems Used from Application to Collection



The behavioural score classifies the risk associated with

the account as high, medium or low. Company C a

behavioural scoring and strategy package to control the

decision making processes in account management and

collections. The company subscribes both good and bad

account information to a closed user group at a credit

reference agency, so account information from other

lenders is available to their decision systems.

If an accountholder misses a payment the collections

system is activated and an indicator on the account is set to

reflect its arrears status. This indicator, together with others

indicating for example an over limit situation are used in

deciding whether to include the account in the stop list sent

to stores. Many of the accounts in this early stage of arrears

will make a payment to resolve their arrears without further

action; they may be account holders who have gone on

holiday and forgotten to pay their bill first, for example.

Accounts which regularly pay late will be moving in and

out of arrears as they go through a monthly cycle. At this

stage there is a high proportion of debt rescheduling. The

collections system interfaces with the strategy management

system to decide on how to progress an account through

collections.

Accounts in arrears are classified by risk or a ‘propensity

to pay score’ and placed into queues for contact with each

queue containing accounts with similar characteristics e.g.

high risk accounts with low balances. There can be up to

200 different queues, with accounts put forward for action

from each on a review date basis. Accounts are

automatically moved to a different queue as a result of

customer contacts, so that they are in the correct queue for

their next scheduled contact. The behavioural score and

account balance are key in prioritizing actions.

The aim throughout the collection process is to establish

contact with the account holder and make arrangements for

payment. Initial contact is initiated 5-10 days after a

payment has been missed preferably by phone, or if this is

not possible, by letter. The next statement will also carry

an arrears message if payment has not been received. If

there is no response to these measures a stronger letter is

sent. If an account progresses to 2 or more payments in

arrears it will be considered for charge-off or debt

recovery.

The telephone/letter cycle will only continue for 60 days

and then an in-house solicitor will send a letter; a notice of

default will be issued after 75 days and the account

charged-off for recovery after 90 days. After 30 days

overdue a late payment charge of £15 is added to the

account. This action has been perceived as having a very

positive effect on collections.

Company C differ from the other collections departments

documented above in that they are more a marketing tool

to the firms retail business whereas for the other firms

financial services are their main business. This has

implications for the way in which they handle arrears and

payment in general. For example, Company C will

encourage customers to use Direct Debit for either full or

minimum payment, offering a reduced interest rate to those

who do. This is not a profit maximising strategy for card

products generally as the provider earns interest on any

balance not paid off each month so full payment would not

be encouraged.



As elsewhere there is an emphasis on customer care, but

this seems to be strengthened further by the marketing

orientation; the aim is always to rehabilitate. The Debt

Management department deal with Citizens Advice

Bureaux, who offer advice to their customer and submit a

payment plan to Company C, and also with CCCS, an

organisation offering professional financial advice and debt

counselling with a fee to the creditor of 15% of the debt.

Financial difficulties account for 25-30% of Company C’s

debts. In these cases account holders are offered a lower

payment or interest is suppressed, with a review of the

situation taking place after 3 months. At that point if there

still a possibility of improvement the account will be

scheduled for review after a further 3 months. If there is no

sign of improvement the debt is passed to debt recovery.

Contrary to experience elsewhere Company C did not find

the setting up of an in-house debt recovery company with a

separate identity effective so debt recovery is done through

outside companies.

The department consists of 67 staff in Early/Mid

Collections and 19 in Debt Management and Recovery. All

charged-off debt (90+ days) is passed to external DCA’s.

Company C is moving towards a more flattened

management structure and away from ‘specialist teams’.

The departmental manager gets a report on the

performance of the company and communicates news on

the business as a whole and on local issues to the staff via

monthly team briefings. The computer systems provide

information on the status of each processing queue and the

activities of each team to enable the manager to identify

bottlenecks and adjust things accordingly. Staff are

encouraged to make suggestions for improving the

department through a formal suggestion scheme.

A new recruit to the department is first given a two week

induction to the company as a whole, followed by a period

of up to five weeks structured training under the guidance

of a more experienced mentor. The exact length of the

training period is determined by the recruit’s abilities.

The telephone team deal with incoming calls and will work

the outgoing contact queues between calls. It is normal

policy to try telephone contact first, but if this has not been

successful after 3 days then letters are used. The evening

shift also work primarily on telephone contact.

Company C have a power dialler which is used in

telephone contacts. The dialler will work a selection of

queues generated by the collection system. Operators are

aware of the type of queue being processed so that they can

be prepared for a particular type of call, and the operator

will not be given a mixture of calls from widely different

queues mixed together. This is helpful in that the operator

is not having to make dynamic changes of tactic for each

call, thus increasing effectiveness.

The Company use 6 DCA’s 2 of which are for 2nd

placement. In addition they use 2 trace and collect

agencies. Performance measurement is undertaken and

benchmarking. The external DCA’s may manage some of

the ATPs which have been set up internally. The Company

sells written-off debt including ‘goneaways’ and IVA’s.



Q: What techniques do you use to develop score-cards?

A: We use a number of techniques in developing

scorecards. The main one is traditional regression analysis

and most of our scorecards have been developed using this

technique either by ourselves or by third parties such as

Experian. We also use neural networks (e.g. for fraud

detection). In the past we have experimented with genetic

algorithms as a methodology.

Q: What types of score are used, how many different

scores are there, what outcome is modelled?

A: We have application scores to predict the likelihood of

someone becoming 'bad' (30 days in arrears). We have

behavioural scores which are used in collections to predict

the likelihood of someone becoming delinquent or

‘propensity to pay’. These are used in segmenting cases for

different action sets. At 60 DPD we have a propensity to

pay scorecard that predicts the likelihood of someone

paying their arrears again. The scores are used for

segmenting for different actions.

Q: Do you use Strategy Management/Champion-

Challenger approaches?

A: 'Strategy Manager' is used in application processing and

is our main decision manager incorporating the application

scorecards and our overriding policy rules (e.g. decline for

CCJs).

Champion-challenger is currently used in our collections

environment (TRIAD) to select a random percentage of

accounts for different action sets. The outcome of these

different actions are then monitored and compared to the

Champion (e.g. increased recovery income, more accounts

rehabilitated) and if they are better than the Champion they

replace it and a new Challenger is introduced in an iterative

way.

This function is also available in Strategy Manager during

application processing and we plan to use it to challenge

whether our policy rules are effective by taking on

controlled samples of accounts who would normally fail

some criterion and monitor their performance.

Q: What type of monitoring do you do?

A: Standard reports from TRIAD showing recovery

income and numbers of accounts at each stage of

delinquency. We also use roll rates to show movements

between delinquency stages. We have performance data on

all customers showing all application details and scores

and their actual outcome.

4.7.4. Case D: International Bank – Collections and Recovery

Company D represents the collection activity for 4 banks

under its ownership in the UK. The collections operation

deals with unsecured finance: personal loans, current

accounts, credit cards. Outstanding balances on these

products are typically £6000 for loans, £500 on current

accounts, £1700 on credit cards. The collections operation

deals with 180,000+ accounts per annum.

Delinquent accounts arrive in collections at various stages

of delinquency depending on the product. Loan accounts

will be dealt with when they reach 5 days past due; current

accounts 30-45 days depending on a behavioural risk

score; credit cards 2 days past due or according to risk

score. Scores are determined at the bank level and the



TRIAD system is used to set strategies and champion-

challenger test. The collection system uses Debt Manager.

The collection team have a power dialler, case/diary

system, online CRA data, ability to take payments by

switch and can negotiate ATPs. Initially the department

contacts and tries to collect under the banks name and uses

phone/letter cycles. Debts are segmented by risk and value

to determine actions. Higher risk accounts will receive up

to 3 calls in a short time period. The collection operation

recently reviewed its strategy and has taken a more

aggressive stance. This was in response to a number of

perceived trends: customers are not longer worried about

indebtedness, there is less stigma, they use fee paying

counsellors more frequently, average balances are

increasing month on month, IVA’s and bankruptcy is

increasing, instalment payments offered by debt

management companies are too small.

After 60-90 days a default notice is issued if there have

been no payments. This is dealt with by an in-house

solicitor under the solicitors’ name. ATP’s may be

negotiated at this stage. At 135-140 days the debt will be

passed to the first internal DCA. The system is highly

automated with little human intervention with automated

strategies. Write-off occurs at 180 days so this period 140-

180 represents an attempt to gain an arrangement and

rehabilitate the customer.

The department has an in-house litigation team and around

6,700 accounts per month move into litigation. The

litigation team are charged with gathering information on

assets and income in order to ascertain if the account is

worth taking to court for recovery. Accounts where there is

poor information will be passed to external DCA’s. The

success rate on litigation is 2-3% of balances recovered.

The department uses 8 external DCA’s, 6 deal with trace

and collect. The bank sells debt to 4 debt buyers. The debt

is allocated randomly to DCA’s but in future the

department will allocate on the basis of DCA performance.

At the moment there is no integration of information

systems with the DCA’s. Commission rates are 20-25% for

1st

placed debt and 35% for 2nd

placed debt. After 270

days the debt will be withdrawn if the DCA has been

unsuccessful. Increasingly the department is selling debt at

2-3p in the £.

There are 120 FTE’s working on inbound and outbound

telephone collections. The internal DCA has 20 FTE’s; 15

staff work ‘specialist collections’ ; 8 work on tracing, 8 on

fraud and 20 in litigation. A team of 6 manage external

DCA’s and debt management organisations. Staff are

trained for 6 months in policies, procedures, negotiation

both on the job and in class. The staff have cash collection

targets, and are monitored on promises and talk time.

The department is looking at activity-based costing,

producing a ‘customer-level’ view, and process

benchmarking.



4.7.5. Debt Management and Collection in the Utilities Sector

This section draws on information from a number of

sources. The CMRC has run benchmarking groups from

major companies supplying gas, water and electricity

which has generated data on the billing, collection and

cycles. Information on practices and processes supporting

collection and recovery were shared by the group. More

detailed interviews were conducted with companies in the

water industry. These case studies are reported along with

a synthesis of ‘best practice’.

The Utilities sector by definition have large volumes of

customer accounts and debts to manage in that all

households and businesses utilize their services. The

process generally follows that charted below ; metering,

billing, collections and recovery. The vast amounts of data

and information generated at each stage suggests that there

is much scope for using data analytics and automated

processes to support debt management.

The purpose of the Utilities Benchmarking Forum was to

define and measure a series of comparable Key

Performance Indicators covering debt management issues

in the utilities sector; to identify and share best practices;

and to identify and quantify drivers of performance

improvement. The Forum collected and compared detailed

data on all aspects of debt management which was

subjected to some sophisticated statistical analysis of the

data.

The data sets were split by household/consumer supply and

business/commercial supply. This analysis in this section of

the report focuses on household supply. The detailed

questionnaire was organised in terms of activity under the

main headings of: customer acquisition; customer billing;

live account management; final account management; cost

effectiveness; and results. The results section measures bad

debt/sales; days sales outstanding, aged debt profiles,

customer retention/attrition.

Chart 4.7.5.1 – Entire Billing Process (Source SAP Business Intelligence)



Although the forum collected and compared data on a large

number of dimensions of the debt management operations

the following key performance indicators provided much

focus of attention:

• days sales outstanding

• bad debt as a percentage of sales

• age of debt profile

• tracing results on "gone away" customers

• number of "gone aways"

• contact calls per hour

• percentage of outbound calls on power-dialler

• percentage of customers on direct debit

• percentage of customers with known phone

number

• percentage of accounts with held bills.

Multivariate statistical analysis was been undertaken to

examine the patterns of variation in key variables such as

the bad debt ratio, using techniques such as multiple

regression analysis. The purpose of this analysis is to

determine what factors drive the differences in bad debt

levels between services, over time and in relation to debt

management practices and customer-base characteristics.

For instance, we are able to model the bad debt ratio taking

into account the simultaneous effect of many determining

characteristics.

A model of the factors impacting on debt levels i.e. debtor

days; aged debt profile; levels of uncollectible and bad

debt; write-off - was developed to guide statistical analysis

and good practice. This is summarised in the chart below:

Factors Impacting on Debt in the Utilities Sector

Customer TypeEmployment StabilityIncome StabilityDeprivation/Geo‐demographicsCustomer Risk /Debt ProfileMarital StatusProperty Type

Customer MobilityChange of SupplierChange of AddressChange of RegionChange in Circumstances

Customer KnowledgeAccurate AddressAccurate Phone Numbers Name of Bill Payer Head of HouseholdHousehold OccupantsProperty TenureService UsageChange in UsageAcorn Code/Geo‐demographics

Billing CycleAccurate ‘Read’ Accurate Billing (Customer Details; Usage/Tariff)‘Clean’ BillTimely BillingDispute Resolution

Payment ArrangementPayment tailored to riskPayment tailored to income (available £’s)Deposits arranged according to riskConvenient payment methodsMaximise cash‐flow (NPV)

Customer ContactCollections strategyContact ‘Success’ rateCall effectivenessSolutions negotiated/ATPDispute resolutionPromises keptCash CollectedOutsource decision

Chart 4.7.5.2 – Factors Impacting on Debt in the Utilities Sector



Each of these factors is thought to impact on the customer

debt profile. Some of these factors relate to management

practices and the efficiency of the collections processes;

others relate to the ‘nature’ of the customer-base and the

company’s ability to gather and maintain intelligence on

the customer. Often the former (collection efficiency) can

be ‘constrained’ by the latter (poor customer information).

Clearly much of credit management and collection activity

is dependent on having a good customer relationship

management data-base. Of vital importance is accurate

‘customer information’ that is details of the person charged

with paying the bill at the address and accurate contact

details i.e. address, phone number, mobile number, work

phone number, email address etc. This activity, of course,

involves tracking changes in occupancy and movements of

indebted customers. Activity is geared to attempting to

minimise the proportion of the customer-base that is ‘gone

away’ or ‘unknown’ and verifying properties that are

‘vacant’ or ‘unoccupied’. Gas and Electricity customers

can change supplier at the same address whereas water

customers only change supplier by moving into another

supplier region. Knowledge of the customer’s employment

status, income and assets (i.e. property owner) is important

for both tracking changes in customer circumstances and

tailoring payment methods and tariffs to customer risk

(available £’s) and, of course tailoring the payment method

to suit the customer’s circumstance. Service suppliers

should attempt to maximise the present value of cash-

flows. For instance, if a bill is due for payment in total at a

particular point in time then it should if possible be

collected at that time. Arrangements to pay over a longer

period (budget accounts, monthly direct debit) effectively

reduce the NPV of revenues.

Accurate billing will have a bearing on debt profile since

an accurate bill will be subject to fewer disputes and

queries which delay the collection process. Bills which

relay on meter readings may be held up and queried if an

accurate meter reading has not taken place. Bills may be

estimated and/or be based on an inaccurate reading. The

proportion of estimated bills or the proportion of customers

yet to have a meter reading will impact on the debt profile

of the customer-base. Where there are disputes the more

quickly that they are settled the more quickly revenues can

be collected. The aim is to collect due revenues at the first

billing and therefore maximise cash flow and minimise

collections costs.

Employment, income and property information, as

suggested above, will be useful in gearing payment method

to customer type and ascertaining whether security or a

deposit should be requested. The task is to ease the

payment for the customer where appropriate and/or make

payment as convenient as possible to avoid arrears and

delinquency. For some utilities this may involve using a

pre-payment meter or usage on a ‘pay as you go’ basis.

Clearly water companies, who have an un-metered

customer-base, predominantly, do not have this option.



Collections activity, should an account become overdue,

depends on having customer information and accurate

billing/usage information. Customer information should

guide the collections approach and billing information will

facilitate the resolution of disputes. Collections activity

should involve ‘informed’ and ‘prompt’ action after the

initial sequence of billing and reminder. Early contact via

phone will establish the customer’s ‘problem’ with

payment, resolve any dispute or payment method problems

and ‘collect’ immediately or establish a promise to pay.

More sophisticated operations will prioritise collections

actions or letter/phone sequences based on risk scores and

account balances. Debt progression will be based on

risk/behaviour profiles in order to minimise collection

costs. The collections performance will be a function of the

accuracy of customer contact details and current phone

numbers. Decisions on later stage debt progression i.e.

outsourcing to DCA’s or legal action should be based on

cost-recovery probabilities.

4.7.6. Best Practice in Collections and Recovery: Evidence from US Utilities

Interviews were undertaken with members of the

International Utility Group, a group of US Utility

Companies offering combined services, gas, electricity and

water. A follow up interview was conducted with the credit

and collections managers of a US Water Company. The

purpose of this series of interviews was to document

current collections and recovery practices in the US

Utilities, assess and document perceptions of ‘best

practice’ and analyse current collections performance and

trends in the key performance indicators used for

benchmarking.

Common elements of ‘best practice’ as perceived by US

practitioners can be summarised as follows: Collection and

‘revenue recovery’ activities are regarded as central to the

success of Utility Company performance and are organised

around clear and simple ‘mission statements’ which all

employees are aware of and focused on. Mission

statements tend to be ‘customer focussed’ which recognise

that effective collections and low write-offs ultimately can

lower prices for the customer-base. As one utility

remarked, “we want to minimise the percent of accounts

overdue, we aren’t doing customers a justice by letting

them get so far behind”

An example of the key elements of such a mission

statement was: “to keep rates low for customers and

improve net income by – minimising write-offs;

maintaining a safe, cost-effective operation; ensuring that

every customer pays for the service that they use”

The idea is that all actions are aligned to ‘corporate goals’.

An individual employee is encouraged to understand how

their own work ‘fits’ or contributes to overall goals

Best practice involves ensuring effective policies and

processes throughout the life-cycle on the customer – from

customer recruitment through to debt recovery. At all

stages of the life cycle the customer’s risk has to be

assessed, measured and monitored. Risk assessment is not

a ‘one-off’ activity but is undertaken at the ‘front-end,

middle and back-end’. Clearly such risk assessment

requires a considerable customer intelligence data-bank

that can be analysed where relationships between risk and

payment can be understood and modelled and ‘behaviour’

scores implemented.



The life-cycle can be categorised as:

(1) ‘front-end’ that deals with new or returning customers

applying for the service. The processes involved in setting

up a new account involve positively identifying the

customer, risk scoring the customer using a credit bureau

application score and analysing the risk history of the

premises being supplied. There may be amounts owing

from the customer of ‘premises’ that would be settled

before a new account is established. In the latter case,

depending on the circumstances, the owed bill might be

settled or waived prior to connection of supply. Based on

risk scores the new account may be set up only after a

deposit is made.

There may be several alternatives in relation to the amount

and conditions of the deposit e.g. advance payments,

deposit in instalments. For instance a customer may be

required to pay a deposit if (a) they have filed for

bankruptcy (b) there is a possibility of default on payment

in the future (c) an existing customer has moved into

delinquency (d) the account has been back-billed for usage

because of theft (e) the customer has an unpaid bill from

previous service (f) the customer only wants the service for

a short period. Typically deposits are calculated as 2

months usage.

Revenue Recovery Customer Impact

Active Accounts

Final Notices Mailed

Accounts For Collection Action

Collection Actions

Disconnects

Past DueFinal BillWrite-off

% of Customers

Field -47% OTC- 53%

Effective FieldWork – 42%

OTC contact– 58 %

-100%

- 12%

- 6%

- 3%

- 0.8%

- 0.4%

-0.2%

Chart 4.7.6.1 – Revenue to Recovery – Customer Impact



(2) ‘Middle’ relates to account management and

maintaining customer service. The key to good revenue

management is accurate and consistent billing, the setting

of payment arrangements appropriate to customer risk and

circumstances (including additional deposits if required),

and effective collections actions (outbound calls and field

actions) first billing, final notices, service charges etc. An

example of the collection process is given below with the

approximate percentage of the customer base which

progresses through the account management and collection

process:

Behavioural scoring underpins account management and

collection actions. Collection actions include final notices

issued, outbound collection calls and field visits. Other

actions that might be implemented as a result of behaviour

scores could be requests for additional deposits or

establishing a payment arrangement with the customer.

The risk score dictates whether or not to incur the costs of

collection activities. One utility found scoring useful when

evaluating ‘final account’ customers. The behavioural

scoring system generated a ‘final account score’. This

score was used to make a ‘will pay/won’t pay’ prediction

and assign more resource to the ‘won’t pay’ segment and

prioritise collection actions.

Scoring process and customer data-bases are used to :

improve applicant identification; make deposit

management more effective; reduce delinquencies; reduce

the number of disconnections; reduce the costs of

collection activities; minimise the number of calls and

contacts related to collection activities i.e. make them more

effective; increase the level of customer satisfaction;

reduce charge-offs/write-offs; calculate reserves more

accurately. As a result of the implementation of scoring

systems in the collections process one utility claimed a 1.6

million reduction in correspondence, 12% reduction in in-

bound calls, 59% reduction in disconnections and field

visits, 25% reduction in delinquency over 30 days and 40%

in delinquency over 60 days, and a 12% reduction in DSO.

Collection actions are evaluated and any ‘loopholes’ in the

processes are identified and dealt with. Of course, the US

utilities undertake benchmarking activities in order to

identify variations in performance and to learn to improve

practices and processes.

(3) ‘Close Service’ involves closing the account by

providing the customer with a final bill and includes

dealing with cases that have filed for bankruptcy. Actions

classified as ‘pre-write-off recovery’ will be undertaken

such as final demand letters, tracing, transferring balances

to active accounts, the use of external DCA’s, fraud

investigations.

4.7.7. Key Performance Indicators used in Debt Management

• Bad Debt Loss Ratio =

Net Uncollectibles divided by revenue

• Delinquency ratio =

Total Number of delinquent customers divided by

active customer-base

• Days Sales Outstanding

• Aged Debt Profile

• Operating Costs per employee

• Customer Accounts per Credit Employee

• Average Cost of Collection per Customer



• Collections Effectiveness Index =

____ ( 1- non current receivables ) * 100______

(last month’s total A/R + sales for current month) – current A/R)

the proportion of overdue amounts at the end of

the month relative to the total amount of

receivables available for collection during the

month.

4.7.8. Best Practice in Collections and Recovery: The Water Sector

In this section we provide some detailed survey and case

study evidence on credit management practice in the water

sector. First we detail a guide to ‘good practice’

synthesized from the various interviews and data. We then

evaluate current practice against this checklist.

This guide to good practice in the water sector was derived

from structured interviews and consultation carried out

with representatives from the UK water industry. The

purpose of these interviews was to provide a check list of

feasible/desirable activities, processes and information

requirements deemed necessary to implement an effective

collections operation. Larger operations clearly have the

scale economies to implement certain systems and

processes which may not be the case in the smaller supply

companies. Later in the report we document the current

practices of a representative sample of water supply

companies against this check list.

Case studies from these interviews are reported later in this

report. Detailed questions were asked relating to customer

type and knowledge, billing cycles, payment methods and

arrangements, customer contact and account management,

collections and recovery and training, technology and

software.

A Guide to Good Practice

Customer Type and Knowledge

CharacteristicsName of PayeeDate of BirthMarital StatusAccurate AddressAccurate Phone Number(s)Previous addressHousehold OccupantsProperty TypeProperty TenureEmployment StatusHomeowner Status

Data‐base managementAcorn/Mosaic/Geo‐demographicsDeprivation/Geo‐demographicsCustomer Risk ProfileChanges of contact detailsData update and enhancement strategy

Absconder managementTrack house movesTrack gone‐away/vacantIdentify ‘unknown’, empty propertyIn‐house/external tracing capabilityReturned bill coding Returned bill strategyVerify persistent non‐payers in occupation

Billing Cycle

Tariffs and SegmentationEnsure tariffs are correctmetered/un‐meteredhousehold/commercialidentify ‘vulnerable’ customers

BillingBilling clear and understandablecater for disadvantaged (e.g. Braille, large print)

‐ clarity of debt progression proceduresfor the customer and employees

Timely billingmeter reading to billing efficiency

Queries and DisputesAccurate and regular meter readingsReview tariffs appliedMinimise ‘estimated‘ readingsQuery and dispute resolutionphone in helplineletter answer efficiencycall‐in (face to face) facilitysegmented contact centreemployee discretion/empowerment

People, Training and Technology

PeopleMission statementTraining (classroom,on‐the‐job)Empowerment and discretionQualificationsSpecialisationwhere appropriateTargets and incentives where appropriate

Technology/SoftwareAutomation and integration where possibleManual interventionOptimise flow processesDocument processes/proceduresData‐base management and ‘scoring’Champion‐challenger facilityManagement Information System

Chart 4.7.8.1 – A Guide to Good Practice



4.7.8.1. Areas of Disadvantage Specific to Water

There are a number of areas that prevent and/or constrain

water supply companies from adopting the ‘best practice’

model in collections and recovery. Sophisticated

collections operations rely on detailed customer level

information to build automated collection systems driven

by ‘behavioural scoring’ models. Collection activities are

prioritised and varied according to customer risk and

balances outstanding. Management information systems

facilitate the varying of collection strategies and debt paths

for each customer and the costs-benefits are analysed for

continual improvement. Collection activities are proactive

and intense in early stage arrears (30 days overdue).

Contact rates with customers are high. Of course, most

companies providing a product or service can ‘choose their

customers’ i.e. reject high risk customers, price the risk,

and insist on advance payment and or security/collateral.

Some key factors in relation to ‘customer information’ and

‘early’ collections activities or ‘sanctions’ are not available

to the collections operations of water supply companies.

Water companies are constrained by regulations governing

the water supply contract and the (sequence of) actions that

can be taken in the event of payment default (e.g. ban on

disconnection). Some investments in collection technology

and software may only be feasible for large scale

operations (e.g. the technologies employed by large

volume lenders).

Payment Methods and Arrangements

Payment MethodsDirect Debit PenetrationStrategies for payment from non‐bank account customersDirect deductions from benefitsInstalment/Budget Account Arrangements(weekly/fortnightly/monthly)‘Switch’, ‘over‐the‐phone’ paymentsInternet paymentsPayment tailored to income (available £’s)Deposits arranged according to riskConvenient payment methodsCharitable trust

in‐houseexternalShared

Maximise cash‐flow (NPV)

Customer Contact and Account ManagementTimely response to overdue/queriesPhone contact (alternative numbers)MinicomPower‐dialler/Caller linked to account data‐baseStrategy for ‘engaged’, ‘voicemail’ etc‐ Letter strategyIn‐bound customer contact and managementPhone help‐lineDocument imaging and management systemAccount management systemOut‐bound calling facility and management

Collections and RecoveryCollectionChase action

‐ Speed of response‐ Reminder Strategy ‐ Letter Sequence, Clear ‘Instructions’, Clear ‘debt progression’‐ Phone/Letter alternatives

Powerdialler/Caller linked to account data‐baseDiary/case management systemAlternative contact methods (Phone/SMS/Personal Visits)Segmented DelinquentsBehavioural/Collection ScoresPrioritisation of actions and sequencesEffective ‘timing’ of actionsEffective sequence and wording of written notices

Escalation Strategy‐ Behaviour score – debt progression sequence

LitigationPre‐court action predictive modellingverification of debtverification of customer incomeverification of customer ‘assets’Policy on recovering court costsPrompt actionApproach to court optionscharges on incomecharges on propertyGarnisheeWarrantsOral examination

External Debt CollectionEnsure Code of Practice (CSA membership)Benchmark DCA panelAccess to performance informationAccess to debt ‘outcome’ informationContractual arrangementsTerminated/open debt policyStrategy on placement (1st, 2nd, litigation etc)



These issues are summarised below and will be

documented in our check-list of ‘good practice’ later in the

report:

No choice over ‘customer’ (applicant)

Water supply companies are unique in that they have a

commitment to supply every household regardless of risk

or payment behaviour. They cannot credit vet new

customers or retrospectively risk score existing customers.

No security deposits can be requested in relation to supply.

No contract with the customer

Water companies supply water without having a ‘contract’

with the customer. This, amongst other things, means that

they can only gather information about the customer if the

customer volunteers it. Basic information such as name and

address of the customer, phone contact details,

employment status etc are often unknown. Such

information is regarded as essential for most other

‘collection’ operations.

The problem of ‘gone-aways’ can be more pronounced for

this sector because the customer feels under no obligation

to inform the supplier when moving property (unlike

telephones, gas and electricity where the supplier may

move with the customer)

No customer ‘risk assessment’ on connection or in

‘account management’

Lack of a contract and customer level information means

that water companies cannot employ ‘risk and behavioural

scoring’ methods that are used in most other collection

environments to prioritise actions and debt path sequences

thus minimising collection costs. Behavioural scores

require payment behaviour information along with

customer characteristics information.

Chart 4.7.8.2 – Number of Customers using Prepayment Meters



No pre-payment meter option

Gas and Electricity supply companies manage customer

risk by installing pre-payment meters for customers with a

history of payment difficulties. This is an option not

available to water supply companies. The growth in the

usage of pre-payment meters is summarised in the chart

below:

Minimal level of customer information prior to

‘delinquency’

In most collection environments effort is placed on

proactive collections. This involves identifying customers

with payment difficulties and resolving the problem prior

to delinquency. Should a customer go into early stage

delinquency (e.g. 1 missed payment) then early efforts to

recover arrears are made. Water companies will have

limited information about a customer until the customer

has defaulted on a payment. Chasing actions therefore

takes place much later than in other collection

environments and it is only at this stage that some

customer level data can be gathered.

Infrequent billing/payment behaviour

Infrequent billing and payment (unless on monthly) makes

it more difficult to assess customer risk and build timely

‘behavioural scores’. Behavioural scoring, as mentioned

earlier really requires data from frequent transactions (e.g.

monthly bills and payments). Water companies do not have

the volume and frequency of information to build effective

scores.

Behaviour scoring unsophisticated

Behavioural scoring requires both frequent payment

behaviour data and basic customer characteristics data (see

above).

Champion-Challenger

Champion-challenger collection strategies are used by

large lenders. Varying collections approaches and the

ability to test new strategies is seen as essential for

effective collection. Water companies have to adopt a

predictable sequence of collections actions (by regulation)

and don’t have the decision support infrastructure to adopt

champion-challenger.

Relatively small outstanding balances

Initially a customer in arrears with water charges will have

a relatively small outstanding balance (£300-£400).

Collection actions may not be cost effective.

Continuous charging therefore accumulating debt

Water charges accumulate year on year and can build into

a substantial debt for a customer that has neglected to pay.

The higher and older the debt, the more difficult it is to

collect

Limited or ineffective ‘early’ sanctions for non-payment

Water supply companies have no sanctions to prompt

payments other than court action. Effective use of the

courts requires detailed customer level information on

income and assets and may be more cost effective when

large volumes of actions are processed.



Debt accumulated before effective action can be

implemented and/or enforced

By then time a debtor gets to court the debt may have

accumulated to a significantly higher level making it more

difficult to collect.

4.7.9. Credit and Debt Management Practice in the Water Industry

The data presented in this section is derived from a study

carried out on a sample of sixteen water sector companies.

Areas covered included the structure of the debt recovery

department in relation to customer base, timings and

effectiveness of debt recovery operations, bill referral,

county court actions, the use of scoring and customer

profiling, knowledge of the customer base, tracing and

outsourcing and the payment options offered (frequency

and methods). The charts below show the responses from

each individual firm and the high, low and mean figures for

each variable. Not all companies responded to all questions

either because the question was not applicable and/or the

data was not available. The identities of responding firms

have been made anonymous for the purpose of this section.

4.7.9.1 General Information

In this section, information was sought from each company

regarding their domestic and commercial customer base

and the extent to which customers are billed directly versus

local authorities or other agents. Information was also

recorded on the level of staffing in each recovery

department. For the purposes of analysis the responding

companies have been divided into two categories, large

companies (turnover in excess of £1 million) and small

companies (turnover less than £1 million).

4.7.9.2 Direct billing and other methods

As can be seen below, the majority of companies bill the

customer base directly with 9 of the 18 respondents

indicating that direct billing accounts for 100% of activity.

However, when this variable is broke down by size of

customer base large companies in the sample average 89%

of customers directly billed compared with almost 100%

for the small water provider. One large company reports

that at present, only 57% of their customer-base represent

direct billing. This breakdown can be seen in the chart

below.

% of Directly billed customers

0102030405060708090

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

%


0

1020

30

4050

60

70

8090

100

Min Max Mean

Respondent ID

% SmallLarge

Chart 4.7.9.1

Chart 4.7.9.2



A number of respondents (8) indicated that they bill via their

own local authority with the highest percentage billed using

this channel being 14% for one individual company. On

average 4.92% of bills from the larger firms (by customer-

base) in the sample are via a local authority compared with

just 0.21% for smaller companies. Clearly the use of LA

collection would be beneficial for the water sector and reduce

overall collection costs (i.e. because of duplication) if the right

kind of commercial arrangement could be agreed with the

LA’s. Currently many water suppliers regard LA collection as

not being cost effective.

Other agents or water companies are also used by 7 of the

sample with one company indicating 32% of all billing via

this method. None of the smaller water companies in the

sample currently use agents or water companies to bill their

customer base.

A full summary of the information on billing to each

respondents’ customer base can be seen in the chart to the

right. As can be seen to the rightt, the majority of

companies bill the customer base directly with 9 of the 18

respondents indicating that direct billing accounts for

100% of activity.

% of Customers billed via local authorities

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

%

% of Customers billed via other agents/other water companies

0

5

10

15

20

25

30

35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

%


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16Respondent ID

% of customersbilled via otheragents/otherwater companies

% of customersbilled via localauthorities

% of directly billedcustomers

Chart 4.7.9.3

Chart 4.7.9.4

Chart 4.7.95



Companies responding to the survey were asked about

their internal collections activities and whether or not they

have an internal recovery department. All 16 companies

indicated that they have an internal debt recovery

department. 10 companies stated that they have an internal

field recovery department and 6 companies indicated that

they have an internal collection agency. The results of the

ratios of customer base to staff can be seen below.

When the number of staff per 1000 customer is analysed

there is a slight difference between the two samples. Larger

water companies have 0.04 per members of staff per 1000

customers and smaller firms have 0.05 members of staff

per 1000 customers. This represents an average of 22,225

customers per staff member (large firms) and 26,415

customers per staff member (small companies).

The time taken in days for collection of debt along with the

% success at each stage is a strong indicator of the

effectiveness in collections. As can be seen in the charts

below information was gathered on the timing of bills to

first, second and third notice and the success rate at each

stage. On average it takes the water sector 20 days before

the first notice is issued. These findings are consistent for

both sizes of company in the sample (19.75 days – large;

19.29 days – small).

Customer base per staff member

0

10000

20000

30000

40000

50000

60000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

no. c

usto

mer

s

Staff Per 1,000 Customers

0

0.02

0.04

0.06

0.08

0.1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

%

Time from bill to 1st notice

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

No.

days

Chart 4.7.9.6

Chart 4.7.9.7

Chart 4.7.9.8



Each company in the sample issues a second notice and the

average number of days it takes to issue is 35 days. Slight

differences are evident in the timing of the second bill with

an average of 32 days for the smaller and 36 days for larger

water utilities.

11 of the 16 companies indicated that they issue a third

notice to late paying customers. The average number of

days among respondents it takes for the third notice to be

issued is 48 days. Greater differences emerge according to

the size of company at the 3rd

notice stage. It takes on

average 56 days for the larger companies in the sample to

bill the third notice compared with just 44 days among the

smaller sector.

Where firms were able to provide information on the

success rate of billing at each stage the results showed an

average of 57% of bills being paid in the water industry on

first notice. An average of 38% of bills are successfully

paid at second notice and 42% at third notice.

4.7.9.2 Telephone Contact

Information was also sought on the time taken between billing

and first and second telephone contact with the customer. As

can be seen opposite, it takes an average of 58 days for the

water sector to make telephone contact with the customer after

the first bill.

Time from bill to 2nd notice

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

No.d

ays

Time from bill to 3rd notice

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

No.d

ays

Bill to 1st telephone contact

0

20

40

60

80

10

0

1 2 3 4 5 6 7 8 9 1

0 11 12 13 14 15 1

6MinMa

xMea

nRespondent ID

Chart 4.7.9.9

Chart 4.7.9.10

Chart 4.7.9.11



Large companies take considerably less time to contact the

customer by telephone after the first bill (46 days)

compared with larger smaller companies (53 days).

Telephone contact with the customer is made on average

70 days after the bill is first issued.

The companies were asked the time taken from the bill to

referral to an external agency. As can be seen below it

takes on average 131 days before referral. Larger

companies and smaller companies roughly take the same

time in this case.

The water utilities were also asked the time taken before a

County Court claim is made. Where applicable firms

indicated that on average it takes 82 days before a court

claim is made.

As can be seen there is a diversity in terms of the number

of court claims made by respondents.

Bill to 2nd telephone contact

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

No.

day

s

Bill to country court claims

0

50

100

150

200

250

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

No.

of d

ays

How many County Court claims did you raise in 2002/03?

0100002000030000400005000060000700008000090000

100000110000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Min

Max

Mea

n

Respondent ID

Num

ber

Bill to referral to external agency?

0

50

100

150

200

250

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

No.

of d

ays

Chart 4.7.9.12

Chart 4.7.9.13

Chart 4.7.9.14

Chart 4.7.9.15



When county court claims are analysed according to customer

base there is clearly an increase in claims according to the

customer base size (see below). There may well be scale

effects that determine the cost effectiveness of court action.

4.7.9.2 Enforcement

9 companies indicated that they enforce a warrant of

execution and the chart below shows the number of

warrants carried out be each respondent in 2002/2003.

10 of the companies responding indicated that they enforce

an attachment of earnings on the customer.

0

0.5

1

1.5

2

2.5

3

3.5

0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000

Number of warrants 2002/03

0

2000

4000

6000

8000

10000

12000

14000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

Num

ber

Number of attachment of earnings 2002/03

0

4000

8000

12000

16000

20000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

Num

ber

% of success of attachment of earnings

0

20

40

60

80

100

1 2 3 4 5 6 7 8 16 9 10 11 12 13 14 15 MinMax

Mean

Respondent ID

%

Chart 4.7.9.16

Chart 4.7.9.17

Chart 4.7.9.18

Chart 4.7.9.19



4.7.9.3 Scoring and Customer Profiling

7 of the respondents to the survey indicate that they use

scoring/profiling/customer segmentation as part of their

debt recovery process. 9 of the companies provided

information on the percentage of customers that they hold

telephone numbers for. On average the sector holds

telephone numbers for 56% of their customer base.

4.8.5 Identifying Good Practices in the Water Sector

In the previous sections of this report we have documented

and analysed the collections and recover practices of

leading edge organisations in the financial services in order

to establish current ‘best practice’. We have shown that the

collections and recovery operations of large volume

lenders in the consumer credit industry are characterised by

sophisticated customer-base information systems,

outbound call centres and automated decision-making

driven by behavioural scoring and constantly varying

collection/recovery strategies.

These sophisticated collections operations rely on detailed

customer level information to build automated collection

systems driven by ‘behavioural scoring’ models. Collection

activities are prioritised and varied according to customer

risk and balances outstanding. Management information

systems facilitate the varying of collection strategies and

debt paths for each customer and the costs-benefits are

analysed for continual improvement. Collection activities

are proactive and intense in early stage arrears (30 days

overdue).

Contact rates with customers are high. Of course, most

companies providing a product or service can ‘choose their

customers’ i.e. reject high risk customers, price the risk,

and insist on advance payment and or security/collateral.

The utilities in Gas and Electricity have options to manage

risk by pre-payment meters and, of course, can stop supply

in cases of non-payment thus minimising further losses.

These companies supply on a contract basis and therefore

have a right to customer-level information when setting up

an account, chasing delinquent payments and tracing

absconders.

Adopting all aspects of the ‘best practice’ model is not

feasible for water sector companies due to regulatory and

legal constraints and the technological investments that

require large scale activities. We have highlighted the areas

where the water companies are at a disadvantage when

competing for household repayments generally and in

relation to the other utilities.

% of customers with known telephone numbers

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 MinMax

Mean

Respondent ID

%

Chart 4.7.9.20



In this section we focus on extant ‘good practice’ in

collections and recovery in the utilities sector and

specifically the water sector. The purpose is to distil and

draw up a check-list of good practice relevant to the water

sector both as a benchmark from which to evaluate current

practice and guide future development. We can draw on

information from a number of sources. We conducted

detailed structured interview with the billing and

collections departments of a cross section of UK water

companies in order to identify trends and developments in

collections and document the key elements of perceived

good practice.

4.8.5.1 Case Study Analysis

During a series of detailed interviews were undertaken

with a cross-section of water supply companies. The

interview schedule was based on a combination of the large

volume lenders questionnaire and the debt focus

questionnaire. The sample consisted of a selection of the

largest and smallest water companies and reflected both

rural/urban and north/south. Eight companies were

interviewed in detail. The case study selection reported

below brings out some of the salient features of ‘good

practice’ in water company collection and recovery

operations and highlights efforts made by the water sector

to emulate ‘best practice’ given current regulatory

constraints. The full selection of detailed interviews are

summarised in the check-list of good practice at the end of

this section. Commercial confidentiality precludes the

reporting of detailed individual cases.

Case 1 – large volume, out-sourced collection operation

This water company operates in a geographical region that

has a population of over 7 million. The customer base has

2.8 million domestic customers and over 250,000

commercial customers. The domestic customer base is

predominantly un-metered (85%), almost 17000

households are unknown i.e. billed as ‘the occupier’. The

company operate a ‘hardship’ fund for income-deprived

customers where payments are matched £ for £ by the

company in order to reduce and manage arrears.

The billing and collection aspects of the business is out-

sourced and has around 190 employees. Internal to the

water company is a small ‘revenue strategy’ team of 15

people who decide the overall customer strategy and

policy; deal with regulatory issues and provide

management information and reports. The out-sourced

operation deals with billing, debt recovery and has an in-

bound call centre with a further 3-400 staff. The call centre

deals with routine payment arrangements and customer

service. Staff can take payments over the phone and

actively encourage the setting up of direct debit by offering

a discount.

Bills are issued in February and March for payment on the

1st

April. From the 15th

-28th

April reminders are issued

and the call centre can react to calls about reminders. The

customer-base is segmented into ‘poor payers’ and ‘better

payers’ based on previous years experience, bad payers

being reminded first. After 21-28 days a legal notice is

issued through an in-house solicitor. An in-house collection

agency can be used for collections at this stage (going

under a different name).



Few summonses are issued and county court action

according to the customer characteristics. The company

attempt to segment by council/non-council, rented/owner,

acorn classification, previous CCJ history, voters roll

matching and information about the customer’s income and

assets. Enforcement is usually by warrant and a small

number of charging orders. The internal DCA has 13 staff.

The DCA receive debts after the legal notice i.e. at 45-60

days delinquency. Summonsing is usually carried out by an

external DCA. External DCA’s are benchmarked against

the internal DCA.

Scoring is used but is quite crude and ranks customers

based on the previous years’ experience. A behaviour score

of 0 to 100 is allocated to customers and can be used to

tailor collection sequences and operate a champion-

challenger environment. Serious debtors are managed

through ‘Debt Manager’ software which has strategy and

champion-challenger functionality.

The company periodically try and update customer

information and phone number accuracy. If there is a

change of tenancy the company try and obtain information

basic customer level information. The company have an

out-bound calling strategy pre and post reminder and are

planning to build behavioural scoring into the system to

drive strategy. The company indicated that they ‘lack tools

for collection’ i.e. customer level data. Improvements in

data and data capture would facilitate a more flexible rather

than predictable collection sequence.

Payment methods are as flexible as possible and tailored to

customer income with an active policy of rehabilitating

delinquent customers back into good payment habits.

Case 2 – smaller company, outsourced collection

operation

This company has close to 500,000 un-metered domestic

customers and 250,000 on meters. Meters can be fitted free

of charge but only 5% of the customer base per year switch

to meters and these tend to be low volume customers.

The billing cycle for unmeasured domestic customers is

documented in the tables below for half-yearly payers and

instalment customers. In all there are 140 different

payment plans. Approximately, 30% of the customer-base

pay by 10 instalments, by direct debit. Although, currently,

no incentives are offered for direct debit. Metered

customers have a reading twice annually and usually pay

on a budget plan with a fixed sum per month taken on

direct debit.



Unmeasured Billing and Recovery Cycle

Half-yearly Customers Min No of days Cumulative No days

since previous since initial bill action Bill 0 0 Reminder 21 21 Pre-court claim notice 14 35 Pre-litigation letter1 14 49 Pre-litigation letter2 6 55 Court Claim 8 63 Judgment 22 85 Post-Judgment letter1 1 86 Post-Judgment letter2 28 114 Enforcement letter1 14 128 Enforcement Action 14 142

Instalment Customers Min No of days Cumulative No days

since previous since initial bill action Booklet 0 0 Reminder (1 month arrears) 21 21 Pre-court claim and instalment Cancellation notice 14 35 Pre-litigation letter1 6 41* Pre-litigation letter2 6 47 Court Claim 8 55 Judgment 22 85 Post-Judgment letter1 1 86 Post-Judgment letter2 28 114 Enforcement letter1 14 128 Enforcement Action 14 142



Approximately 74% of the customer-base pay or agree a

plan on receiving the first bill. After the second reminder

20% of the customers either pay or contact customer

service. 4-5% of the customers receive the pre-litigation

letter and 7000 cases per year are pursued through the

courts. Normally 9-10,000 summonses are issued of which

about 50% progress to judgment. The company have

limited information about the customer to be able to assess

whether court action might be worthwhile. Enforcing

judgments is a major problem and there are significant

debts that are over 48 months old i.e. ‘hardened debtors’. A

range of enforcement actions are tried from warrants to

charging orders to attachment of earnings. However, debt

from ‘hardened debtors’ is building and 52% of

outstanding debt is owed by only 15% of the customer-

base. The credit management function has 42 full-time

staff and 2 field staff. The credit management function is

split into 3 teams (Credit Management, Litigation and

Enforcement, Income protection). The Credit Management

team deal with front-end collections, letter and phone

contact and follow the process through to court action and

judgement.

The Litigation and Enforcement team (10 people) apply

available enforcement procedures for debt recovery. The

third team (income protection) deal with special cases and

accounts that have fallen through other processes.

They are involved with tracing and liase with debt

collection agents. The company use a panel of 3 DCA’s and

recover debt form previous occupiers with debt. They

manage some post litigation instalment (repayment) plans.

The advantage of DCA’s is that they have the technology –

power diallers, monitoring systems and collection

software. The company has not the scale of operation to

justify investment in out-bound calling facilities and

because of a lack of customer-level data.

Case 3 – large company, in-house operation

This is a large scale operation covering over 3 million

customers. Almost 3.5 million domestic customers are

directly billed and around 700,000 have meters. The scale

of the operation in terms of collections and recovery

actions is summarised in the chart below (See chart below).

The company processes large volumes of court claims and

enforcements. Around 3% of the customer-base is dealt

with by 6 local authorities who collect water charges with

property rent. Almost 40,000 accounts have unknown

occupancy and the company has to attempt to find out

occupier details for the billing and collection process as

well as tracing absconders.

CUSTOMER RELATIONS

600CommercialSuppliesCut Off for Non Payment

3,500 Charging Orders Issued

3.8m Calls Answered

xx m BillsRevenue £ xx m

Bad Debt xx %

22,000 Attachment Of Earnings

1m LegalNotices

2.5m ReminderNotices

50,000Debt Related Visits

140,000Outbound Calls made 260,000

Telemessages

InstalmentCancellations180,000

95,000Court Claims

Large Volume Collections Operation

Chart 4.8.5.1 – A Large Volumes Collections Operation



The company has a process-driven credit management

operation with specialist teams in different locations across

the supply region. Like most companies the billing and

collection cycle is adjusted to cater for metered and non-

metered, domestic and commercial customers. The

company has a large volume collection operation akin to

other large scale lenders. The salient features are illusrrated

below.


LitigationClaims

LitigationEnforcement

DEBT

DEBT

Collection(Comm)

Collection(Dom)

Predictive Dialler

Payment Processing

External Agencies

CCA Visits (Field)

Collection

Litigation enforcement

Support Services

PAYMENT

SECURED

FRONT OFFICEBILLING &

OPERATIONALCONTACTS

DEBT ENQUIRIES CONTACTS

BACK OFFICESALES & BILLING

BACK OFFICECREDIT

MANAGEMENT STR

ATE

GIC

CH

AN

GE

SER

VIC

ES

CUSTOMER METERING CREDIT MANAGEMENT

FIE

LD

ST

AFF

SALES

COMPLAINTS REVIEW TEAM

PERFORMANCE PLANNING




Behavioural Scoring

The company has developed a behavioural scoring system

to flag risky accounts and tailor appropriate action. The

behavioural score, developed in-house, ranks customers on

a 0-99 index according to payment history. The score can

be used to vary the debt path and the timing of actions

according to risk so that risky customers are progressed

more quickly. The score can be used to segment the

customer-base for action on the power-dialler out-bound

calling and could facilitate champion-challenger collection

actions backed up by a sophisticates MIS and data-base

management technology and activity-based costing.

Litigation

The Company processes large volumes of accounts for

court action and litigation, approximately 80,000 per

annum. The company is moving towards a more

sophisticated screening process before legal action is taken.

It is important to ascertain the profile of the debtor prior to

legal action to ensure that the action will be cost effective.

The profiling includes a behavioural score, the existence of

previous CCJ’s, Acorn profile, deprivation index, home

ownership and rateable value and employment status. A

team of 40 staff are involved with dealing with the court

system. The company use all options to enforce successful

judgements with charges on income or assets being the

most preferred. Debt management software is used to

process post-judgement accounts.

Case 4 – medium to large company, in-house operation

This company has a customer base of approximately 1.2

million accounts and covers both domestic and commercial

accounts. Like the previous case the company has

developed, in-house, a risk scoring system that drives and

prioritises collections actions.

Recovery Paths and Steps

UD1Overdue Account

App 101Day 14

UD2Notice of Legal

ActionApp 103Day 35

UD3Solicitor'ss Letter

App 114Day 56

UD4Agency or

SueDay 77

UnmeasuredDomestic

UC1Payment Demand

App 110Day 14

UC27 Day Letter

App 092Day 35

UC6Agency or

SueDay 100

UnmeasuredCommercial

UC3Audit Report to

assess ifdisconnection

possibleDay 56

UI4/MI4Withdrawal of

Instalment PlanApp 107Day 91

UI5/MI5Solicitor'ss Letter

App 114Day 112

UI6/MI6Agency or

SueDay 133

UnmeasuredInstalments/Multi

Instalments

UI2/MI2Overdue Inst Plan

App 112Day 49

UI3/MI3Instalment Arrears

App 113Day 70

MD1Overdue Account

App 101Day 21

MD2Final demand

App 102Day 42

MeteredDomestic

MD3Solicitor'ss Letter

App 114Day 63

MD4Agency or

SueDay 84

MC1Payment Demand

App 110Day 21

MC27 Day Letter

App 092Day 42

MC6Agency or

sueDay 96

MeteredCommercial

MC3Audit Report to

assess ifdisconnection

possibleDay 52

Metered MultiInstalments/Budget Plan

Closed Accounts

CA1Overdue Account

App 101Day 14

CA2Solicitors Letter

App 104Day 35

CA4Send toTrace &CollectAgencyDay 77

OccupierUnknown

OU1Occupier

Unknown A/FApp 159

OU2Inst. to Disc

App 162

OU3Visit DCAApp 160

CA3Solicitor'ss Letter

App 114Day 56

UI1/MI1Nothing Sent

App 099Day 28

MI/BP4Withdrawal of

Instalment PlanApp 107Day 111

MI/BP5Account reviewed- If no payment,

re-pathed to MD3/MC5

MI/BP2Overdue Inst Plan

App 112Day 51

MI/BP3Instalment Arrears

App 113Day81

MI/BP1Nothing Sent

App 099Day 21

OU4Martin E Visit

App 260

UC4Property Visit

ReportApp 093A

Day 58

UC5Solicitor'ss Letter

App 114Day 79

MC4Property Visit

ReportApp 093A

Day 54

MC5Solicitor'ss Letter

App 114Day 75

Chart 4.8.5.3 – Recovery Paths and Steps



Typical debt paths are reported in Chart Case 4.1. Collections

actions can be varied according to risk so that a different

collection strategy can be adopted in a champion-challenger

type environment. The Company has an in-bound and out-

bound call centre operation and makes out-bound calls usually

in the evening. The collectors chase up payment, are able to

take payment over the phone (Switch), encourage direct debit

take up and/or arrangements to pay. An important aspect of

the work is to ensure that customer contact details are up to

date and as complete as is possible.

The company deal with 6 DCA’s, 2 of which specialise in

trace and collect. The DCA performance is monitored and

benchmarked to ensure continual improvement and to identify

areas where the DCA’s can perform better than in-house

collection/recovery efforts.



Good Practice Matrix CHECK LIST CODE: Not Present/implemented = X Partial/Planned = 1

Significant/Partially Implemented = 2 Complete/Fully Implemented = 3 WATER COMPANIES

Existing OFWAT

guideline? Regulatory constraints Scale effects 1 2 3 4

5

6 7

8

Customer Type and Knowledge

Name of Payee -

Having no contract with the customer limits the amount and type of customer level data

2 2 2 2 2 2 2 2

Date of Birth - 1 1 1 1 1 1 1 1 Marital Status - 1 1 1 1 1 1 1 1 Accurate Address - 2 2 2 2 2 2 2 2 Accurate Phone Number(s) - 2 2 2 2 2 2 2 2 Previous address - 1 1 1 1 1 1 1 1

Household Occupants - Partial Information In all cases 1 1 1 1 1 1 1 1

Property Type - 2 1 2 1 1 2 2 1 Property Tenure - 1 1 2 1 1 1 1 1 Employment Status - 1 1 1 1 1 1 1 1 Homeowner Status - 2 1 2 1 1 2 2 1 Data-base management Acorn/Mosaic/Geo-demographics YES As above 2 1 2 1 1 2 2 1 Deprivation/Geo-demographics YES 2 2 2 2 2 2 2 2

Customer Risk Profile - No credit reference information

Scoring limited by data/information 2 1 2 1 1 2 2 1

Changes of contact details -

Having no contract means that customers do not feel obliged to inform of vacation of property

2 2 2 2 2 2 2 2

Data update and enhancement strategy -

Scale effects- requires outbound as well as inbound call centre activity

2 1 2 1 1 2 2 1



Absconder management

Track house moves -

Use DCA’s and tracing agencies – internal and external

2 2 2 2 2 2 2 2

Track gone-away/vacant - 2 2 2 2 2 2 2 2

Identify ‘unknown’, empty property - Labour and time- intensive process Scale effects 2 1 2 1 1 2 2 2

In-house/external tracing capability - 2 1 2 1 1 2 2 2 Returned bill coding - 2 2 2 2 2 2 2 2 Returned bill strategy - 2 2 2 2 2 2 2 2 Verify persistent non-payers in occupation - segmentation 2 1 2 1 1 2 2 2 Billing Cycle Tariffs and Segmentation Ensure tariffs are correct - 3 3 3 3 3 3 3 3 - metered/un-metered - 3 3 3 3 3 3 3 3 - household/commercial - 3 3 3 3 3 3 3 3 - identify ‘vulnerable’ customers - 2 2 2 2 2 2 2 2 Billing Billing clear and understandable YES 3 3 3 3 3 3 3 3 - cater for disadvantaged (e.g. Braille, large print) YES

Large investments in billing systems 3 3 3 3 3 3 3 3

- clarity of debt progression procedures for customer and employees YES 3 3 3 3 3 3 3 3 Timely billing 3 3 3 2 2 3 3 3 - meter reading to billing efficiency YES Large % unmeasured 3 2 3 2 2 3 3 3 Queries and Disputes Accurate and regular meter readings - Large % unmeasured 2 2 2 2 2 2 2 2 Review tariffs applied - 2 2 2 2 2 2 2 2 Minimise ‘estimated‘ readings - Targets for % reads 2 2 2 2 2 2 2 2 Query and dispute resolution 3 2 3 2 2 2 3 3

- phone in helpline -

Scale effects of document Imaging and processing systems

3 3 3 3 3 3 3 3

- letter answer efficiency - 3 3 3 3 3 3 3 3 - call-in (face to face) facility - 3 3 3 3 3 3 3 3



Collections and Recovery Collection Chase action - Speed of response YES 3 3 3 3 3 3 3 3 - Reminder Strategy YES 3 3 3 3 3 3 3 3 - Letter Sequence, Clear ‘Instructions’, Clear

‘debt progression’ YES 3 3 3 3 3 3 3 3 - Phone/Letter alternatives - 3 2 2 X X 2 3 X - Powerdialler/Caller linked to account data-

base - 2 2 2 X X 2 3 X - Diary/case management system - 2 2 2 2 2 2 2 2 - Alternative contact methods

(Phone/SMS/Personal Visits) - 2 2 2 2 2 2 2 2 Segmented Delinquents 2 2 2 1 1 2 2 1 - Behavioural/Collection Scores - 2 1 2 1 1 2 2 1 - Prioritisation of actions and sequences - Limited by regulation 2 1 2 1 1 2 2 1 - Effective ‘timing’ of actions YES 1 1 1 1 1 1 1 1 - Effective sequence and wording of written

notices YES 1 1 1 1 1 1 1 1 Escalation Strategy - Limited by regulation 2 2 2 2 2 2 2 2 - Behaviour score – debt progression sequence - 2 1 2 1 1 2 2 1 Litigation

Pre-court action predictive modelling - Limited by information available Partial 2 2 2 1 1 2 2 1

- verification of debt - 2 2 2 2 2 2 2 2 - verification of customer income - 2 2 2 2 2 2 2 2 - verification of customer ‘assets’ - 2 2 2 2 2 2 2 2 Policy on recovering court costs - 2 2 2 2 2 2 2 2 Prompt action - 2 2 2 2 2 2 2 2



Approach to court options - - charges on income - 2 2 2 2 2 2 2 2 - charges on property - 2 2 2 2 2 2 2 2 - Garnishee - 2 2 2 2 2 2 2 2 - Warrants - 2 2 2 2 2 2 2 2 - Oral examination - 2 2 2 2 2 2 2 2 - External Debt Collection Ensure Code of Practice (CSA membership) YES 3 3 3 3 3 3 3 3 Benchmark DCA panel - 2 1 1 1 1 2 2 2 Access to performance information YES 1 1 1 1 1 1 1 1 Access to debt ‘outcome’ information - 2 2 2 2 2 2 2 2 Contractual arrangements - 3 3 3 3 3 3 3 3 Terminated/open debt policy - X X X X X X X X Strategy on placement (1st, 2nd, litigation etc) - 2 2 2 2 2 2 2 2 LOCAL AUTHORITY 1 People and Training, Technology and Software People Mission statement - 1 1 1 1 1 1 1 1 Training (classroom,on-the-job) - 2 2 2 1 1 2 2 1 Empowerment and discretion - 1 1 1 1 1 1 1 1 Qualifications - 1 1 1 1 1 1 1 1 Specialisation where appropriate - 2 2 2 2 1 1 2 1 Targets and incentives where appropriate - X X X X X X X X

Technology/Software Automation and integration where possible - 1 1 1 1 1 1 2 1 Manual intervention - 2 2 2 2 2 2 2 2 Optimise flow processes - 2 2 2 2 2 2 2 2 Document processes/procedures - 2 2 2 2 2 2 2 2 Data-base management and ‘scoring’ - 2 1 2 1 1 2 2 1 Champion-challenger facility - 2 2 2 1 1 1 2 1 Management Information System YES 2 2 2 2 2 2 2 2



4.9 Use of Debt Collection Agents

A number of trends and industry dynamics have impacted

on the out-placed debt collection and debt purchase sector.

These include: the surge in consumer debt and increase in

the volumes of delinquent debt that have to be processed;

the increased emphasis on cost effectiveness and

performance benchmarking; the continued re-engineering

of centralised in-house collection and recovery functions

and the development of technology and information

systems devoted to account management; the speed of

response of the major lenders in dealing with delinquent

accounts and a shortening of the time period to write-off.

The latter trend has been given much impetus by the Basel

II rules that have encouraged the lenders to shift debts off

of their books more quickly and to opt for debt sale rather

than commission-based collection since the former

mechanism transfers ownership of the debt.

The Credit Services Association reported that their member

organisations handle around £15 billion of debt on a

commission basis which consisted of over 20 million

individual cases. This represents a rise of £10 billion since

2000. The CSA membership bought around £6 billion of

debt in 2007 making of total of over £21 billion being

passed to the DCA sector. The CSA estimate that their

market will be worth over £24 billion in 2008.

There has been an increasing preference amongst lenders,

(particularly credit cards) to sell debt to debt buyers rather

than place for commission-based collection.

Consolidations in industries that service the debt collection

sector e.g. utilities, telecommunications, and retail

industries have impacted on the market for DCA services.

Industry consolidations imply that organisations have

bigger portfolios and can negotiate lower prices for higher

volumes of business and/or invest in new internal

collection and recovery operations. Price competitiveness

has in turn led to consolidations in the debt collection

industry in order for them to gain efficiencies of scale and

develop close and integrated relationships with key clients.

The sale and purchase of debt portfolios has opened up

avenues for the DCA’s but in turn requires more

sophistication in the pricing and collection processes. A

source of potential revenue growth for the DC industry is

as a provider of a wider range of out-sourced business

services across the credit life-cycle. Outsourcing

receivables management has increased, particularly for

commercial debt. Government and the public sector are

beginning to utilise the services of DCA’s. The growth in

the internet B2C and B2B has translated into more

collection activity on a global scale.

There has been and continues to be a general trend

amongst the large volume collectors to streamline and

rationalise their use of 'external' collection agents alongside

their 'in-house' collection agents. Our original 1998 survey

found that the large lenders would pass out debts, on

commission, to a large range of external collection agents

and on quite an ad hoc basis. At this time the lender viewed

the relationship with the customer as terminated and had no

further interest in the customer Little effort was put into

monitoring the success rate of the different agents. Our

later surveys identified that that large volume lenders were

beginning to prefer to have a closer and more sophisticated

interface with a smaller number, say 4-5, main collection

agents. Often the performance of each agent would be

monitored according to the type and age of debt that they

were working and benchmarked against each other and

against the performance of the in-house collection agent.

Some were operating champion-challenger style

monitoring of the agent's performance. The lenders were

keen to track the customer after they had been passed out



to agents in order to monitor outcomes. This, to some

extent, requires that the collection agent's information

system can integrate with that of the client. Thus the

lenders were attempting to develop seamless information

systems that could track the customer from account

management/customer service through to collections, out

to the collection agents and back into the lender where

possible. The implication for the debt collection sector was

that scale was becoming more important as was the

investment in I-T systems that would rival and or add value

to those of their clients. As a consequence we were seeing

fewer but larger and more sophisticated collection agents

with closer working relationships/interfaces with their

clients.

As in-house collection functions were improving their own

speed of response and internal collection efforts it meant

that the DCA’s were receiving debts that were both

younger and that had been ‘worked’ harder. These trends

have continued into 2007 with the lenders looking for

further efficiencies and additional expertise and

specialisation from the DCA’s.

A potential problem for debt collection agents is that these

'in-house' operations, buoyed by their successes, are

(considering) taking debts from clients other than their

internal clients i.e. become competitors to the external

agents. The response of the larger DCA’s has been to

invest in technology, communications and expertise to

develop a range of specialist services for segmented debt

portfolios. The growth in outsourced recovery services has

created new opportunities.

The lenders used to place debt for collection with DCA’s

after a specific period of time and in-house collection

cycle. The more recent trend is to experiment with placing

at different stages of the collection cycle and employ the

services of DCA’s at various stages of the billing and

delinquency cycle as charted below.

The NewApproach

CustomerAcquisition

Billing & Sales Ledger

ArrearsManagement

DebtCollection

Litigation &3rd PartyCollections

OutsourceIn‐house

Multiple Outsource Points

Period of Delinquency

Chart 4.9.1 – Collections: An Integrated Approach



Analysis the accounts of 177 known DCA’s we can track a

substantial increase in the average turnover and net worth

of these organisations.

Chart 4.9.2 – Turnover Trends in UK Debt Collection market

Chart 4.9.3 – Net Worth Trends in UK Debt Collection market



4.9.1 DCA: Case Study

The diagram below represents the debt processing path of a

large DCA beginning with the matching of debtors to

information sources in order to profile and score the debtor

into a particular debt segment. The DCA uses multiple

collection strategies with an emphasis of early contact with

the debtor.

Contact is a sophisticated process that involves power-

dialling and other telephony timed to achieve the best and

most cost-effective results.

An arrangement to pay can then be negotiated with the

debtor with multiple payment options. Champion

challenger strategies are used to maximise the effectiveness

of collection actions.

The lenders typically will monitor the performance of the

DCA closely and benchmark their performance versus in-

house and other external DCAs. Information systems are

linked to the lender and the DCA service is optimised as

charted below.

Data Enhancement

Portfolio Segmentation

Multiple Collections Strategies

Maximised Contact

Payment Conversion

Optim

ised Co

llections

Multiple data source matching

Full names, correct addresses, home, work and mobile telephone no.s

Segmentation using account characteristics

Type of debt, balance, previous payment history, location, presence of telephone no. etc

Different debt treatment paths for different segments

Varied contact identities, letters, intervals, postal tariffs, payment methods

Application of contact methods and tools at the best times

Use of predictive diallers, SMS and e‐mail, “right time to call” analysis

Optimised collections contributions when contact is made

Most effective payment methods, optimised negotiation tactics, effective default procedures

Compliance

Staff Incentives, training and development

Chart 4.9.1.1 – Example of DCA Collections Process



4.10 Debt Sale and Purchase: Trends and Developments

The debt sale/purchasing market has attracted much

interest in the recent years and is perhaps the fastest

growing segment of the debt collection and management

industry based on the potential value of debt available for

purchase. In the US the debt sale and purchase market is

well established By 2000 It was estimated that the face

value of debt purchased was over $60 billion in the US

which had a collection value of around $3.6 billion. The

market has continued to grow in the US and was over $150

bn in 2006.

In the UK it is difficult to estimate the total size of the debt

sale market since the market continues to evolve quite

rapidly. The market size in 2005/6 was around £6bn face

value selling at an average price of around 8p in the pound.

By 2006/7 this had increased to £7bn and commentators

are expecting the market to peak at around £10bn. Debt

sale is still dominated by ‘distressed debt’ portfolios i.e.

debt that the financial sector would normally write-off

and/or is severely delinquent is sold to the highest bidder

for collection/recovery. In the early stages of the debt sale

market the pricing of ‘distressed debt’ was of little issue

for the seller since any price attracted was a bonus for debt

already written-off. Such debt traded for 1 or 2 pence in the

£. In 2006/7 it is estimated that the average price has

increased to an range between 2-5 pence in the pound as a

result of increased competition in the debt buyer market

and more sophistication in debt pricing. The value of debt

Weekly Service ReviewAll aspects of Client AdministrationAttendees: Account Manager, Client Services Manager

Quarterly Strategic ReviewHigh level review of major projects and future initiatives and improvements UK Board

Inputs Actions

Weekly Collections ReviewDetailed consideration of all collections metricsAttendees: Account Manager, Sector Collections Manager

Monthly Commercial ReviewOverall review of all aspects of service and performanceSales Director, Operations Director

Client Feedback

League Tables

Internal Data / KPI’s

Staff Feedback

Complaints

Legislation and Regulators

Outcomes

Tactical Short Term Actions

Benchmarking and testing of new strategies

Communication of issues to the client

Re‐mapping of business processes

Project based improvement initiatives

Compliance reviews

Client Specific Intranet Site for all key data and information

Chart 4.9.1.2 – DCA Service Optimisation



decreases with age and the numbers of collection cycles

and placing that it has been through. However it is clear

that lenders have developed an interest in selling younger

debt as a means of improving cash-flow and because of the

costs of servicing the debt collection sector when debt is

placed on a commission basis. If the costs of administering

debt collection services (servicing costs) are taken into

account along with commission rates then it may be more

costs effective in some cases to sell debts outright. “As

financial institutions get more comfortable selling debt, we

believe they will sell a greater amount of performance debt

that they want to get rid of for strategic reasons” R H

Reitzel (quoted in the Kaulkin Report 2001, p 38).

Most of the Debt Collection Agents have turned to buying

debt as an alternative to collection on commission in 2004

there were over 60 debt buyers although the DBSG

suggests that currently there are around 40 regular buyers

in the market. The growth in the market has been

facilitated by the supply-side. The major lenders and the

majority of financial services are now selling debt and

developing specialist departments to deal with debt sale

and respond faster to debt sale opportunities. The bulk of

sales are distressed debt attracting the 2-5% price but there

is evidence of sellers selling debt earlier, as in the US,

typically 180 days past due. The changes in accounting

rule, Basel II and capital requirements have had an impact

as a result of changes in internal default definitions. A

further development is the sale of debt that has already

been managed to achieve an ‘arrangement to pay’ via a

debt management company. This type of debt can attract

30-40 pence in the pound. The development of a reseller

market is expected to create further growth in the market.

The main sources of debt sale are credit cards, loan and

overdrafts, retail credit, motor finance and increasingly

mortgage arrears. The utility and mobile phone companies

have sold debt. This debt is typically old and of low value.

Difficulties in collecting this type of debt have depressed

prices. The credit card environment appears to be the most

attractive sector. Here average value is in the region of £

2000-4000. The debtor is likely to be employed with an

incentive to ‘recover’ their position and return to being

credit active. Interviews with a major debt buyer suggests

that the average balance on credit card debt has increased

from £4000 to £8000 in the last 2 years. There has, of

course, been some sale of IVA’s as the volume has

increased but there have been concerns over the quality of

the IVA (the debtor rarely has any assets) and the fees

taken by the IVA practitioner. The market for commercial

debt in the UK is currently small given the scale of

corporate receivables but there is evidence that the market

is beginning to grow e.g from corporate credit cards,

outsourced receivables management operations and

insolvency practitioners.

A problem that is probably hampering the growth of the

debt sale market is that of ‘pricing’. Interviews with major

lenders suggested that there is some lack of ‘trust’ in the

market as a result of extant price variations. If debt is to be

sold at earlier stages and /or segmented by ‘quality’ then

there has to be a mechanism for pricing the individual

debts and the debt portfolio. Clearly in order to price debt

something has to be known about the ‘default probability’,

the collection probability (including percentage recovered),

the timing of possible recovery (i.e. collection period) and

the costs of collection/recovery. The type and source of the

debt will have a bearing on its value in a debt sale. Of

course, ultimately the value of the debt is a function of the

net present value of the future cash-flow in relation to

collection costs. The seller, of course, would wish to



achieve the maximum price for the debt but has an

informational advantage over the potential buyer. That is

the seller is likely to have the information necessary to

accurately price debt but has an incentive not to reveal this

to the buyer. Markets tend not to function well when price

is not transparent. In the US this ‘pricing’ function has

been performed by intermediaries, ‘debt brokers’ who

specialise in portfolio analysis. Accounts can be ‘scored’

independently on the basis of likely recovery rates. Brokers

have the ability to put together more attractive ‘packages of

debt’ emanating from different lenders. There are some

specialist brokers in the UK (eg.TDX and recent US

entrants) but currently most debt is sold in a tender-bidding

environment with inefficient pricing. Once the UK market

has further developed this type of expertise in packaging

and pricing debt then the market should mature and prices

should achieve some uplift. Gauging the ‘quality’ of debt is

problematic at the time of purchase because of

informational asymmetries between buyer and seller and in

relation to the individual debtor. Not least an individual

that has debts with one lender is likely to have debts with

other lenders that could be consolidated by the debt

purchaser. Internet auction markets still do not appear to

have the confidence of the debt sellers yet such systems

have the potential for creating an efficient market in debt

sale/purchase.

Debt buyers have typically invested in sophisticated I-T

and customer scoring capabilities in order to maximise the

efficiency of the debt management and recovery process

and generate profit. This is likely to involve developing a

customer-level view. A major debt buyer indicated that

over 20% of the debts that they receive are from debtors

that are already known to them. That is, debtors tend to

have multiple debts spread across different lenders. A

challenge for the debt buyer is to identify and consolidate

these multiple debts into a single arrangement to pay.

Adding value to account data using scoring models to

understand the debtor profile and determine the NPV of

future cash flows, effective customer contact and

developing realistic and ‘collectable’ ATP’s is fundamental

to generating profitable business.

Further growth in the Debt Purchase market is likely to

come from the sale of non-delinquent receivables, reselling

and from commercial debt.

4.10.1 Case Study: Debt Buyer

Interviews with a large UK buyer focussed on the process

involved in purchasing and processing consumer debt.

Then company employs over 350 full time staff but will

grow to over 600. The company currently processes over 2

million accounts, predominantly from UK lenders but with

an increasing international portfolio with a face value of,

on average, £2000. The average face value has been

increasing with a larger proportion in the region of £4-5000

for cards and £8000 for loans. The average price paid is in

the region of 2-5 pence in the pound but price variations

have been increasing along with the average price paid

Purchase is usually by tender and bidding after due

diligence on the debt portfolio has been carried out. The

source of debt is predominantly distressed credit card debt

with some loan portfolios and retail credit. The company

has not had success with utilities and mobile phone

portfolios. After the notice of assignment has been sent to

the debtor the priority is speedy contact with the debtor by

phone/letter combinations. The aim is to quickly establish

the debtors profile and financial circumstances and

negotiate an arrangement to pay some or all of the

outstanding debt Emphasis on negotiating a realistic deal



that allows the debtor to begin making payments. This may

involve starting the debtor at a low repayment level and

increasing the monthly payments over time. In fact, 55%

of the accounts pay by direct debit and the overall default

rate is around 9%. The debtor is offered other options to

repay including cheques, post office cards, over the phone

collections. The main reasons cited for being in debt are

over-commitment; change in personal circumstances (ill,

divorced, loss of first and/or second income) .

Contact and information is key to a successful outcome.

Contact is mad primarily via a call centre and call centre

staff are trained to establish a relationship with the debtor

and negotiate the arrangement to pay. If an initial deal

cannot be established the options are to write-off, ‘rest’ the

debt for a period (up to 12 months), use a third party or

doorstep collector or explore litigation if the debtor has

assets. Almost 40% of debtors agree to a ATP after first

contact. The company has an internal tracing team to track

debtors that have changed address. Currently the company

does not use external CRA data or the sellers internal

scores but relay on their own internal account data.

However, access to ‘white’ customer information via the

CRA’s is seen as desirable in adding collections.

New accounts are ‘scored’ through an internal scoring

system to determine the probability of repayment and the

accounts are segmented by score and other aspects of

account profile. Further information on income and assets

is gathered via the call centre where possible. Internal

behavioural scores are employed to determine the likely

time scales of repayments and the profitability of the ATP.



5. A Survey of Debt Collection Agents and Debt Buyers

Our previous sections presented an overview of the size of the market for debt collection services and debt sale/purchase. The

research suggests a markets size in the region of £25 billion per year with an increasing share being taken by debt sale. The sector

has been characterised by rationalisation through technology investments and mergers and acquisitions. Fewer and larger agencies

have closer links with their clients through integrated information systems and benchmarking for continuous improvements in

collections and operational efficiency. Consumer and commercial debts derives from banks, finance houses, credit cards, retail

cards, utilities and telecoms and the public sector. In this section we report the results of a survey of individual debt collection

agents and debt buyers in the UK. This follows up our previous surveys in 2003 and 2001 and provides some trend information.

The DCA sector covers both consumer and commercial debt and offers collection on a commission basis or the outright purchase of

debt. In the latter case the debt buyer acquires all of the rights and duties of the original creditor. In the case of contingency debt

collection (commission-based) the ownership of the debt resides with the client and debts can be passed back to the client if

uncollected after a period of time. This creates a secondary and tertiary market for debts since these uncollected debts may be

placed with another DCA. Commission rates are a function of the age and type of debt Trade debt from B2B relationships may be

placed for commission-based collection. The DCA’s offer services such as tracing absconders, asset tracing, repossessions of

goods, litigation, and status reports and investigations.

5.1 Debt Collection Services

• 46% of all agencies offer Debt Purchase, an increase of 27% since 2003.

• Repossession has increased by 25% to nearly half of all agencies.

In terms of Debt Collection services offered by agencies in 2007 significant differences can be seen since 2003 in Repossessions

(up 25%) and Tracing (down 15%), The offering of Process Services and Investigations/Status Reports has declined between the

two time periods. The largest difference between services offered in 2003 and 2007 is in Debt Purchase which is up by 27% among

the sample. 46% of all agencies offer this service in the marketplace.



TABLE 5.1 DEBT COLLECTION AND OTHER SERVICES OFFERED BY RESPONDENTS

CONSUMER DEBT COLLECTION

Consumer debt collection 2003 2007 % change

Trace and collect 60.4% 61.5% 1.1%

Tracing 68.8% 53.8% -15%

Court action 60.4% 53.8% -6.6%

Card recovery 29.2% 23.1% -6.1%

Repossessions 22.9% 48.5% 25.6%

Bailiff 10.4% 7.7% -2.7%

Process serving 35.4% 23.1% -12.3%

Debt surveillance 22.9% 23.1% 0.2%

Status reports and investigations 58.3% 46.2% -12.1%

Outsourced debt management 41.7% 46.2% 4.5%

Debt purchase 18.8% 46.2% 27.4%

Consultancy 45.8% 38.5% -7.3%

Training 33.3% 23.1% -10.2%



5.2 The Market for Debt Collection Services

• 67% of agencies indicate an increasing number of clients.

• 55% indicate a growth of debts being placed in the market.

• No companies report a decline in the number of debts placed.

The respondents to the survey in the 2001, 2003 and 2007 surveys were asked whether their client base and the numbers and values

of debts were declining, stable or increasing.

As in 2001, 67% of respondents indicated that their client-base was increasing. Just over a quarter of respondents indicated that

their client base remained stable with 8% suggesting a decline in client base.

CHART 5.1 CLIENT BASE TRENDS FOR THE DEBT COLLECTION MARKET



Respondents were asked to indicate on a 5-point scale whether the number of debts had been declining (1) increasing (5) in the last

financial year. The statistics suggest a healthy growth in the market for debt collection with 80% of respondents ticking the 4/5

categories on the scale and 55% indicating growth in the number of debts placed at the highest score of 5 in 2007. 46% of

respondents suggested that the market had remained stable and no companies indicated a decline in the number of placed debt.

CHART 5.2 NUMBER OF DEBTS PLACED IN MARKET

5.3 Market Size

• 75% of agencies indicate that market size is increasing in 2007.

• This compares to just 45% in 2003.

• 99% of agencies believe market competitiveness to be increasing.



A number of questions on the survey were designed to obtain information on the nature of the consumer debt collection market.

These questions ascertained opinion on the size/growth of the market overall, specific sources of out-placed debt, the age and

quality of debt that is out-placed and the overall competitiveness of the market for consumer debt collection. Respondents were

asked to indicate whether they thought that the overall market for consumer debt was increasing, stable or decreasing at present. As

can be seen from the chart on the scale from (1) increasing to (5) decreasing almost 75% of respondents indicated that they believed

that the market was increasing in 2007. This compares to just 45% in 2003.

CHART 5.3 MARKET SIZE FOR CONSUMER DEBT

Although the size of the market was generally thought to be increasing the respondents felt that the market for out-placed consumer

debt remained very competitive.

5.3.1 Market Competitiveness for Consumer Debt

The vast majority of respondents indicated that the market for consumer debt collection was very competitive. 85% of firms ticked

4 or 5 on the scale to indicate a currently competitive marketplace. 99% of agencies believe the market competitiveness to be

increasing compared to just 85% in 2003.



CHART 5.4 MARKET COMPETITIVENESS FOR CONSUMER DEBT

5.4 Value and Volumes in the Debt Collection Market

• The largest agencies report a 526% increase in average collective debt value from £228 million in 2003

to £1.2 billion in 2007.

• The average individual debt value has more than doubled since 2003.

• The number of debts worked on per month has increased from an average of 1,200 to 19,000 in 2007.

An increase of 1900%.

• Large agencies work on 40,000 debts per month in 2007 compared with just 1,000 in 2003

The number of debts worked by agencies each month across the entire sample has increased dramatically from between 1,200 in

2003 to 19,000 in 2007. Among the larger agencies this increase is most significant with agencies with over 100 employess

reporting a rise from 1000 debts per month to 40,000 debts per month.



The chart below shows the distribution of debt collectors by the number of debts worked per month i.e. where at least one action

has been taken to collect the debt. In 2001 collectors in the consumer debt market dealt with considerably larger volumes of debt

than those servicing the commercial sector with over half working over 1000 debts per month. In 2003 this trend changed with a

lower volume of debts being worked in consumer collection than before. However in 2007 agencies are now clearly collecting a

higher number of debts per month with 56% of agencies stating that they work over 5000 debts per month.

TABLE 5.2 NUMBER OF DEBTS WORKED PER MONTH – WHOLE SAMPLE

Number of debts 2001 2003 2007

Less than 500 30% 50% 11%

501- 1000 18% 21% 20%

1001 – 5000 41% 14% 13%

Over 5000 11% 15% 56%

The table below summarises information on the average value of debt received in £s. Overall in the sample, the average value of a

debt placed across the entire sample has increased from less than £1000 in 2003 to £2400 in 2007.

TABLE 5.3 VALUE OF DEBTS WORKED PER MONTH – WHOLE SAMPLE

Value of debt 2001 2003 2007

Less than £250 35% 27% 2%

£251-£500 26% 16% 8%

£501-£1000 9% 5% 10%

£1001-£2000 22% 41% 38%

Over £2001 10% 11% 42%



TABLE 5.4 NUMBER OF CLIENTS AND DEBTS WORKED PER MONTH – AGENCY SIZE BREAKDOWN

Size of Agency (employees) Average Number of Clients Average Number of debts

per month worked

Average Value of a Debt

placed

2003 2007 2003 2007 2003 2007

6 to 10 100 80 500 300 £1500 £150

11 to 25 13 8 2920 14000 £4000 £400

26 to 50 35 98 1010 25000 £758 £817

51 to 100 56 112 1300 11500 £1860 £5250

Greater than 100 156 30 1000 40000 £1087 £2370

The table below gives an indication of the total values and total numbers of consumer debts placed with the respondent debt

collection agents organised by size of the agent. As can be seen below the largest agents have seen a significant increase in the

value associated with the largest agencies operating in the market. In 2003 the largest agencies reported a total value of £228

million for debts placed. This figure in 2007 is now £1.2 billion.

TABLE 5.5 TOTAL VALUE AND TOTAL NUMBER OF DEBTS PLACED – AGENCY SIZE BREAKDOWN

Size of Agency

(employees)

2001 2003 2007

number Value number value number value

6 to 10 13,000 £3,125,000 26,000 £6,500,000 3,600 £520,000

11 to 25 14,000 £10,000,000 68,000 £22,757,250 168,000 £67,200,000

26 to 50 177,000 £62,045,829 212,000 £130,000,000 300,000 £245,000,000

51 to 100 200,000 £141,000,000 290,000 £200,000,000 338,000 £104,000,000

Greater than 100 779,000 £210,000,000 911,000 £228,000,000 980,000 £1,200,000,000



A factor affecting the collection success rate will obviously be the age of the debt that is being received into the collection agency.

The survey gathered information on whether the debt collection agents were handling primary, second or third placed debts and the

proportions of the total debt received that could be categorised under these headings. Again it is clear that some agents specialise in

first placed debt whereas others take a high proportion of second and third placed debt.

TABLE 5.6 SECTORS FOR DEBT COLLECTION ACTIVITIES

Sector Average % of Total Business

2003 2007

Bank 45 47

Credit Cards 60 48

Finance Houses/ Retail 40 45

Local Authority/ Central 55 51

Utilities 82 60

Telecoms 60 30

Mail Order 40 38



Respondents were asked to indicate which were the fastest growing or declining sectors for out-placed consumer debt. Responses

were coded on a five-point scale from Declining (1) to Growing (5).

TABLE 5.7 GROWING AND DECLINING SECTORS FOR CONSUMER DEBT

Declining Stable Growing

1 2 3 4 5

2001 2003 2007 2001 2003 2007 2001 2003 2007 2001 2003 2007 2001 2003 2007

Banking 4.2 0 20.2 4.2 14.3 9.8 42 14.3 9.1 50 57.1 50.0 0 14.3 10.9

Credit cards 4.5 0 15.3 13.6 0 0 27.3 27.8 13.1 36.4 55.6 57.1 18.2 16.7 14.5

Finance

houses

8.7 0 11.8 4.3 5 10.4 34.8 40 22.2 52.2 45 44.4 0 10 11.2

Retailers 4.5 0 11.7 18.2 6.7 1.4 40.9 60 1.5 36.5 20 29.7 0 13.3 55.7

Utilities:

Gas 0 7.1 0 21.4 0 14.3 14.3 42.9 14.3 42.9 42.9 28.5 21.4 7.1 42.9

Electricity 0 7.1 12.8 20 0 22.2 20 42.9 11.1 26.7 42.9 22.2 33.3 7.1 31.7

Water 7.1 8.3 40.2 14.3 0 19.8 21.4 50 20.7 35.7 25 0.0 21.4 16.7 19.3

Telecoms:

Fixed line 7.1 0 0 7.1 40 0 28.6 40 1.7 35.7 13.3 63.8 21.4 6.7 34.5

Mobile 0 0 0.8 5.6 14.3 2.2 16.7 57.1 35.4 27.8 28.6 32.1 50 0 29.5



There appears to be growth in a number of sectors judging by the responses on the 4 and 5 points on the scale. However, some

sectors are generating a faster growth for the out-placed debt industry. In 2007 the fixed line telephone sector is the most buoyant

sector with 98% of collection agents indicating a 4 or 5 on the growth scale. This compares to just 29% in 2003.

Collections within the retail sector shows the second largest growth among respondents with 85% of collection agents indicating

this to be a growing market. The credit card industry has continued the 2003 growth trend which is most likely a result of the

growth of this particular industry. 72% of respondents indicate this to be a growth market.

The water industry is the one sector which is reported to be declining in terms of growth in 2007.

Questions over the last seven years have solicited opinion on the age and the quality of out-placed consumer debt. These

characteristics clearly have a bearing on the difficulty of collecting these debts and the efforts and resources that have to be

employed to collect the debts.

As can be seen below, 39% of companies state that the total value of debts comes from their largest client.

TABLE 5.7 VALUE OF DEBTS FROM LARGEST CLIENT

2007

Largest client 39%

2nd

largest client 14%

3rd

largest client 9%



5.5 Quality and Volumes in the Debt Collection Market

• 51% of agencies in 2007 feel that the quality of consumer debt is worsening.

• 66% believe that debt is getting older in 2007 compared to 11% in 2003.

• The majority of agencies have between 21 and 50 clients.

In 2003 43% of respondents thought that the quality of out-placed debt was generally worsening. This figure in 2007 is 51% in the

sample. 18% of respondents indicated that the quality of consumer debt was improving.

CHART 5.5 QUALITY OF CONSUMER DEBT



In 2007, 69% of companies feel that debt was generally getting older. This is compared to just 11% in 2003.

CHART 5.6 AGE OF CONSUMER DEBT

Over 60% of collection agents generate their business from under 50 clients and generally collection agents are dealing with fewer

clients than in 2003. The table below summarises the data further.

CHART 5.7 NUMBER OF CLIENTS WORKED FOR



5.6 Debt Purchase

• The largest buyer of debt in 2007 paid £458 million compared to just £28 million in 2003.

A 1600% increase in the last four years.

• 63% indicate the Debt Purchase market is still growing in 2007.

• 64% state that prices paid for purchased debt are increasing.

• Prices paid for debt are now more concentrated in 2007 and average 8p in the pound.

CHART 5.8 DEBT PURCHASE MARKET GROWTH

The general growth of the debt purchase market continues in 2007 with 63% of companies indicating an increased market.

However, a quarter of respondents (25%) report the market to have stabilised compared to 18% in 2003.

A series of questions were included in the 2003 and 2007 surveys aimed at gathering further information on the debt purchase

activities of UK collection agents.



The largest buyer of debt purchased a face value of £458 million compared to just £28 million in 2003. Of the total debt purchased

in 2007 an average of £30 million was collected during the last year.

In the sample prices paid for debts varied between 5p to 18p in the pound. The average price paid in the pound is 8p in 2007. This

shows more of a concentration of debt sale pricing since 2003 when the range was between 1p and 24p in the pound. As can be

seen below 64% of responding agents indicate that overall prices are increasing in the debt purchase market.

CHART 5.9 GROWTH IN PRICES PAID IN DEBT PURCHASE - 2007

Companies were also asked the percentage of debt purchased which is collected directly, restructured or resold. As can be seen in

the table below 89% of purchased debt is collected, 10% is sold on to another party and 1% is restructured.

TABLE 5.8 % OF PURCHASED DEBT SENT FOR COLLECTION

What percentages of consumer debt do you: 2007

Collect 89%

Restructure/ refinance 1%

Resell 10%



5.7 Litigation and Bankruptcy

• 16% of live consumer debts were under some form of litigation process in 2007.

• Only 3% of debts are collected via the court process.

• There were only 434 court actions from an average of 228,000 debt placements in the last yer.

• The number of IVA’s has increased by 700% in the last three years.

• 78% of agents have accounts linked to an IVA.

• IVA Default Rates have more than tripled in the last three years.

• 98% of defaults are re-scheduled by agencies.

• The average value of each bankruptcy has doubled in 2 years to £6000.

One of the most important aspects of debt collection is contact with the debtor. When individuals get into arrears they often become

increasingly difficult to trace. As can be seen the agencies were asked the percentage of their live consumer workload which was

goneaway and then successfully traced in the last financial year. 23% of consumer debts were reported to be goneaway with 17%

successfully traced. This means that 6% of all accounts were untraceable in the last 12 months.

TABLE 5.9 % OF PURCHASED DEBT SENT FOR COLLECTION

Live consumer debts in 2007 2007

Gone away 23%

Successfully traced 17%

As can be seen below 16% of live consumer debts were under some form of litigation process in 2007 – although agencies only

reported an average of 434 court actions per year. When this is considered in the context of agencies handling on average 19,000

placements per month, clearly the legal process is not being used significantly.



TABLE 5.10 % OF PURCHASED DEBT IN LITIGATION


In litigation 16%

No. of court actions 434

There were slightly more consumer debt referred to court during 2007 with an average of 1428 across the sample. Of these cases

only 3% of debts were received.

TABLE 5.11 % OF TOTAL DEBT REFERRED TO COURT


Number referred to court 1428

% of total number of debts received 3%

5.7.1 Individual Voluntary Arrangements (IVA’s)

The collection agents were asked if any of their collectable debts were operating under an Individual Voluntary Arrangement. 78%

of the agencies responding to the survey had accounts which were linked with an IVA.

CHART 5.10 % OF AGENTS WITH ACCOUNTS OPERATING UNDER AN IVA



The average number of IVA’s which collection agents had agreed to in the last 12 months stands at 354.

TABLE 5.12 NUMBER OF IVA’s AGREED TO IN LAST 12 MONTHS

2007

Number of IVAs 354

Total Average Value £1,268,667

The agents were also asked to indicate how these figures had changed in the last three years. As can be seen below the number of

IVA’s in 2004 stood at just 50 with an average total value of £185,000.

TABLE 5.13 NUMBER OF IVA’s AGREED TO IN LAST 3 YEARS

2004

Number of IVAs 50

Total Average Value £185,000

The average length of time for an IVA is among the sample is 4.75 years. Agents also indicated that they expect to receive 38p in

the pound under an IVA and would accept a minimum of 32p.



In terms of default rates collection agents were asked to state the the percentage of IVAs which had defaulted over the last 3 years.

As can be seen below default rates have more than tripled during the last three years and now stand at 13%.


Default rates of IVA’s 2007

Last year 13%

Last 2 years 9%

Last 3 years 4%

98% of these defaults were rescheduled in the last year. 2% were written off.

TABLE 5.15 DEFAULTS WHICH HAVE BEEN RESCHEDULED IN LAST YEAR

2007

Re-scheduled 98%

Written-off 2%



5.7.2 Bankruptcy

The responding agents reported an average of 250 bankruptcies in the last 12 months with an average total value of £1, 458,000.

This represented 1.35% of the total consumer debt workload.


2007

Number 250

Total value £1,458,000

When asked to compare the figures of each individual debt there has been a progressive increase in the average individual of each

bankruptcy in the last two years. As can be seen below the average value of each bankruptcy is £6000 – almost doubling in size

from £3200 two years ago.

TABLE 5.16 BANKRUPTICES IN THE LAST TWO YEARS

Value

Average value currently £6000

Average value 1 years ago £5200

Average value 2 years ago £3200



References 1 Creditaction Debt Facts and Figures – October 2007

2 Creditaction Debt Facts and Figures – October 2007

3 Bank of England (UKV2QB) UK Personal Borrowing Outstanding

4 Bank of England “Statistical Release” September 2007

5 Financial Risk Outlook 2006, Financial Services Authority

6 BBC News website – www.bbc.co.uk

7 National Consumer Council “Debt Summit” November 2006

8 Creditaction Debt Facts and Figures November 2007

9 Council of Mortgage Lender 2007

10 Citizens Advice Bureau Press Release September 2007

11 Experian Press Release November 2007

12 British Bankers Association Statistics September 2007

13 Office for National Statistics and Bank of England October 2007

14 Creditaction Debt Facts and Figures – October 2007

15 Finance and Leasing Association Statistics 2007

16 Euler Hermes Press Relase 2007

17 World Factoring Yearbook (BCR) 2006)

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