UNDERSTANDING CREDIT SCORING TECHNIQUES AND BEST PRACTICES

Understanding Credit Scoring Techniques and Best Practices

FCFP Forum October 12-13, 2006Atlantic City, NJ

Jan Rowland, Ph.D.Leader, Data and Analytical Strategy

Rich Ferrera, CCELeader, Trade Credit Best Practices

Copyright (c) 2006 D&B. All rights reserved.These materials are provided by D&B as a service to its customers, may not be copied or distributed, and may be used for informational purposes only.

Understanding Predictive Scoring Techniques and Best Practices 2

Agenda

• Challenges in today’s credit risk management discipline – How credit scoring can help

• Overview of credit scoring – What is a credit score

– Who uses credit scores

– How are credit scores created

• Credit scoring best practices – Credit Application Evaluation

– Portfolio Management

– Collections

– Fraud Screening


In today’s fast-paced business environment, managing risk and improving cash flow are more challenging than ever before…

• You are at greater risk from incurring potential bad debt due to bankruptcy and fraud

• You need to increase cash flow at a time when economic pressure is causing companies to use you as a source of funding by paying you slower

• You are under pressure to make your credit function more efficient without increased risk

• You must comply with increased regulation, such as the Sarbanes-Oxley Act, which requires financial executives and credit practitioners to better understand risk in their portfolios

• You need to do all of the above very well … while maximizing your company’s sales by approving all reasonable requests for credit!!!


Businesses are seeking best practices for developing objective, accurate risk assessment systems that address key questions...

Credit Credit Application Application EvaluationEvaluation

PortfolioManagement

How can we be sure we are efficiently and consistently delivering credit decisions across the entire organization that are consistent and comply with policies and drive revenue?

How can we consistently analyze risk exposure across the whole organization to protect the firm from an unforeseen major loss?

Business Need Credit scoring can helpQuickly and more accurately assess risk among your new business applicants

Easily identify changes in risk across your entire portfolio to minimize exposure and decrease costs


1. ReduceRisk

2. IncreaseSpeed

Credit scoring can help businesses answer these questions and maximize their company’s profitability by providing five critical benefits

3. IncreaseEfficiency

4. IncreaseConsistency

5. IncreaseSales

• Target Credit-Worthy Customer for Future Promotions

• Increase Approval Rates

• Ensure Equal, Objective Treatment of Each Applicant

• Apply Consistent, Objective Decisions Across the Organization

• Quickly Handle Obvious Approvals/Declines

• Less Data is Required to Make Accurate Decisions

• Decrease Bad Debt• Reduce Exposure to High

Risk Accounts

• Analysts Only Focus on Difficult Accounts• Increase Volume of Accounts Evaluated with

Same Staff


Agenda







– Collections

– Fraud Screening


Credit scoring is a quantitative tool to assess the risk of lending money to a particular consumer or business

• Consumer credit scores predict how you will pay your credit cards, utility bills, car loans, mortgage etc.

• Business credit scores predict how a business will pay it’s trade credit, business loan, business card, lease, office utilities, legal services etc.

• Results of a credit score provide guidance regarding:– Who will get credit

– How much credit they should get

– What pricing strategies should be extended to enhance profitability


Credit scores come in a variety of flavors. When choosing a credit score for your company it is crucial to ensure the event the model is predicting clearly addresses your critical business needs

• Delinquency Models predict the future payment performance of your business customers

• Bankruptcy Models predict the likelihood of a business failing

• Recovery Models are applied to customers you placed in collection. They predict the likelihood of recovery and provide an estimated collection amount

• Fraud Models identify businesses that have a higher likelihood of being fraudulent


Agenda







– Collections

– Fraud Screening


One out of three businesses are currently using credit scoring to help manage their receivable portfolio

• 36% of the 329 businesses surveyed have integrated credit scoring into their risk management practices

– These businesses tend to have more than $1 billion in sales and over 7,500 active accounts

– 92% of businesses surveyed use credit scoring for new account evaluation and 88% review existing customers

• Another 42% of businesses surveyed anticipate utilizing credit scoring within the next 5 years

• 8 out of 10 businesses currently using a credit scoring system report that the scoring system is meeting their expectations

Source: CRF Study. Credit Scoring: The Future of Decisioning in the A/R Process, 2003


Agenda







– Collections

– Fraud Screening


Credit scores are just one component of a comprehensive scoring system that can help you manage risk among your new and existing accounts

3

2

1

Higher Risk

Decline or

Cash Terms

Commercial Bureau

Information

Application for Credit

Automated Scoring

Consumer Bureau

Information

Application Processing

Business Decision

Rules

Medium Risk

Analyst Review

LowRisk Immediate Approval

Information Scores Decision Rules

Technology


INFORMATION: The most predictive scorecards are designed to utilize the widest range of information

• Payment experiences provide an accurate picture of how a company is paying a wide variety of financial obligations

• Public record information (Suits, liens, judgments, bankruptcies and UCC filings) could affect a company’s ability to pay and survive

• Financial information provides an understanding of the financial strength of a business and it’s ability pay on time

• Firmographic information identifies higher risk business segments


INFORMATION: Hundreds of data variables are analyzed to determine the credit scoring model variables; here are some commonly used ones

• Receivables

• Payables

• Cash

• Dividends

• Current Liabilities

• Current Assets

• Working Capital

• Net Worth

Financial

• Payment History

• Trade Experiences

• Bank Loans

• Secured Financing

• Public Filings

• Previous Bankruptcy

• Trends

• Condition Assessment

Credit

• Line of Business

• Size (employee, sales)

• Years in Business

• Business History

• Suits, Liens, Judgments

• HQ/Branch/Single Loc.

• Location

• Special Events

Business Demographics


0%

5%

10%

15%

20%

25%

30%

Probability Of Delinquent Payment

26.3%

11.7%

7.3%

4.6%

0.7%

INFORMATION: The precise combination of the key business and principal owner characteristics provide the most accurate assessment of risk

Compounding Effects of Multiple Negative Factors

Payment Index

Negative Experiences

Industry

Region

Business History


SCORES: Simply put, credit scoring is the process of using historical outcomes to predict future outcomes

Historical Outcome

A proven, effective risk evaluation tool to condense hundreds of attributes about the business and/or business owner into one easy to interpret

score, that estimates a company’s future performance

95

Risk Assessment

95 / 100= ‘A’Very

likely to pay on time

Business and Business Owner Characteristics

(Variables)

Predictive Models rely on Statistics which utilize “Probabilities” which apply to groups -- you must judge score performance on a large sample, not on

an individual business


SCORES: There are various approaches for creating the optimal combination of business attributes

• Rules Based vs. Statistical methodologies

• Standard vs. Custom scores

• Commercial vs. Small Business scores


SCORES: The most common Credit Scoring methodologies are

• Expert / Judgmental / Rules Based

– Rules and weights are set by the user based on their experience

– Complete flexibility setting up decision criteria

– Automates your current policies & procedures, but does not improve accuracy of assessment

• Statistical

– Utilizes multivariate statistical techniques to find significant correlations between business attributes and delinquency or failure

– Weights derived mathematically based on the relative importance of each business attribute

– Typically results in most accurate assessment of risk


SCORES: While Custom Scoring Models are an option, most businesses begin their risk assessment with a statistically-based, generic commercial model

• Standard Scoring Models- Sample and outcome selected from business bureau universe (does not use

your data)

- Predicts likelihood of a business paying any financial obligation on time

- Performance can be validated on own portfolio

- No Up-front investment is required

• Custom Scoring Models- Most predictive solution

- Combines information from a user’s customer base with bureau data

- Predicts likelihood of a business paying you on time

- Objective of model can be tailored to fit specific business goals

- Requires a representative sample of user’s experience


SCORES: Finally, you will want to map the optimal score to the types of businesses in your portfolio

• Commercial Risk Scores- Scores driven purely by information about the business (commercial data)

- Most often used for risk assessment of small to medium size businesses

• Small Business Risk Scores- Scores driven by information about the business (commercial data) and

business owner (consumer data)

- Most often used for risk assessment on micro-businesses (emerging businesses using consumer credit) and small businesses (for example, less than 10 employees or decisions under $100,000)

- Well suited for companies willing to adopt consumer credit legal requirements


Ownership

Time as owner

Time since most recent delinquency

% Good trades

# of public records

ATTRIBUTESATTRIBUTESCHARACTERISTICCHARACTERISTIC

SCORES: Regardless of which approach you select the final scorecard will be comprised of points assigned to attributes of a characteristics. The accumulation of points determines the ultimate score.

Owns Facility

40

Leases Office Space

25 40

11+yrs50

6-10yrs40

3-5yrs35

0-2 yrs20 50

<6mo15

6 – 1220

13- 2440

13 – 2440 40

SCORESCORE

<10%10

10 – 49%20

50 – 79%30

80% & Up40 40

10+-40

5 – 9-10

1 - 515

00 0

170Total

High Risk Low Risk0 200


SCORES: As an illustration, here’s a business that has a higher risk of delinquency vs. one that has a lower risk of delinquency

• Restaurant business established in 2005

• Management has history of previous bankruptcy

• Payments are typically 60+ days past terms

• There are suits filed against this firm

• Leases office space

• Manufacturing business established in 1979

• There is no history of management involved with previous bankruptcy or other negative experiences

• Payments are typically paid within terms

• There is no evidence of suits, liens or judgments

• Owns facility

Higher Risk Business Lower Risk Business

Please note this is for illustration and that the final determination of risk level is based on the combination of data variables.


SCORES: The credit score is then used to distinguish good accounts from bad ones and to set approval and decline cutoffs that meet your risk and sales objectives

Risk Class

Score Percentile

% of Bads Identified

1 91-100 2-4% 97-99%

2 71-100 30% 4-6% 88-93%

3 31-100 70% 8-9% 57-62%

4 11-100 90% 11-13% 26-34%

5 1-100 100% 13-17% 0%

Approve accounts that score a 71 and above, which is 30%

of your new applications…

% of Accounts

10%

…and you’ll identify & screen out up to 93% of bad accounts.

…you’ll have a delinquency rate

of only 6%...

Delinquency Rate


DECISION RULES: Credit professionals can maximize the impact of credit scores by combining their decision rules with credit scores to drive credit decisions

ScoringDecision

RulesCredit

Decision

Percentile Ranking

% of Accounts

% of Bad Accounts Expected

Net Worth Credit Credit Line

91-100 10% 1%$1M+

$1<$1MApprove Approve

Up to $20,000 Up to $10,000

31-90 60% 28%$1M+

$1<$1MApprove Approve

Up to $10,000 Up to $5,000

11-30 20% 27% _Analyst Review

1-10 10% 44% _ Approve Pre-Pay Only


Agenda







– Collections

– Fraud Screening


Credit Scoring best practices enable businesses to efficiently protect themselves from higher risk customers

Portfolio Management

Credit Application Evaluation

Collections

Fraud Screening

• Prioritize Internal Efforts based on Collectibility

• Optimize Use of Third party Agencies

• Portfolio Analytics & Benchmarking• Account Management & Monitoring• Dynamically Update Credit Lines• Trigger Collections Activity on

Delinquent Accounts

• Screen for Previous Fraud• Evaluate Potential for Future

Fraud

• Automatic Approval/Decline• Set Credit Line• Price for Risk


AnalystReview

GrayArea

CREDIT APPLICATION EVALUATION: Scoring makes the credit process more efficient by segmenting accounts for automated approval, decline, special terms or requiring analyst review

ImmediateApproval

Decline orSpecial Terms

ApplicationProcessing

OutsideInformation

Applicationfor

Credit

BusinessDecision

Rules

AutomatedScoring

• Very Low Scores• “Knockout” Criteria

• Middle Scores• High Exposure• Review Criteria

• High Scores• Low Exposure• Targeted Markets

• Fraud Risk Score• Delinquency Score• Failure Score


CREDIT APPLICATION EVALUATION: Let’s look at a best practice implemented by one business using a standard credit score in its new account risk management process

• Situation: Client needed a system to replace a credit decision matrix that would:

- Reduce lease application turnaround time from five (5) hours per application

- Improve productivity by automatically approving lowest risk applicants and rejecting highest risk applicants

• Solution: Client implements a generic commercial credit score which predicts the probability that an applicant will become severely delinquent within the next 12 months in their new applicant decision-making process

• Results:– Client reduced lease application turnaround time from 5 hours to 1 hour 45

minutes

– Client increased processing volume to more than 75,000 application per year without increasing staff

– Client is able to automate 69% of their new applications, freeing up its analysts’ time to focus on the 31% of “gray area” cases


CREDIT APPLICATION EVALUATION: In this example a manufacturing company reduced its delinquency from 1.8% to .8% with the integration of a custom credit scoring model

Automated Decisions Manual Review

Approved

Declined

Scorecard Decision Overridden by Analyst 1 Out of 2 Times

.8% Delinquency 3.5% Delinquency 1.8% Delinquency


PORTFOLIO MANAGEMENT: Account management based on your internal data only, limits your ability to assign effective treatment strategies

With internal performance data you may treat all accounts that are 31-60 days delinquent the same

When they should be treated differently

WatchClosely

Send toCollection

CollectLateFees

InvestigateServiceIssue

Increase Credit Line


PORTFOLIO MANAGEMENT: Integrating external business scores into your account management strategy provides you with greater insight to more effectively manage your accounts

* Sort Accounts by Past Due Amount Within Priority Group

Cre

dit

Ris

k(B

ased

on

Cre

dit

Sco

re)

Your Aging

1-30Days

31-60Days

61-90+Days

High

Medium

Low

CollectLateFees

InvestigateService

Issue

Send toCollection

Increase Credit Line

WatchClosely


COLLECTIONS: Collections Treatment Strategy Based On Credit Scores Resulted in a 75% Improvement in Performance

4.76%

1.90%

5.31%

1.37%

0%

1%

2%

3%

4%

5%

6%

1st Qtr. 2nd Qtr.

Traditional Collections Treatment Credit Score Targeting

Sh

are

of

Bal

an

ces

90

or

Mo

re D

ays

Pas

t D

ue 75%

Improvement


In summary, credit scores…

• Predict future events based on historical occurrences

• Are effective tools to evaluate high volumes of transactions to free analyst focus on higher exposure accounts

• Provide effective tools for consistent, efficient and effective risk management evaluation of new and active accounts

• Require four (4) essential components:– Timely, accurate information

– State of the Art predictive scoring techniques and expertise

– Actionable Business Rules

– Automated Decisioning


• Define your business application– Evaluate new applications – New Account Model

– Account and portfolio management – Behavioral Model

– Prioritize collection efforts – Recovery Score

– Fraud detection – Fraud Score

• Clearly state the event you would like to predict

• Understand your target market or portfolio personality– Commercially credit active small to medium size business – Commercial

Scorecards

– Start up and very small businesses that also utilize personal credit to finance their business – Blended Scorecards

The following guidelines will help you choose the scoring solution that best meets your needs…


Understanding Predictive Scoring Techniques and Best Practices

Live demonstration of how credit scores are used in practical

applications


Example Scorecard

Weight Weight Scorecard Component: New Customers Existing Customers* Credit Score 30% 21% Paydex Score 20% 14% Financial Stress Score 25% 18% Yrs in Business 15% 11% Number of Judgments on Account 5% 4% Number of Liens on Account 5% 4% Customer's Pay History with company 30% 100% 100% * Existing Customers include both requests for credit limit extension and contract renewal review

Based on the above weights, each component will be evaluated and scored as follows: Component = Data Element used (e.g. Credit score) Attribute = The reported outcome of the component (e.g. Credit Score is 60) Value = Derived from a lookup table (e.g., Credit Score is 60% x .1 = (60 x .1= 6) Weight = % placed on each attribute Score = Weight x Value for each component Total Score = Sum of each score


Example Scorecard

If Score is 8.00 - 10.00 then N30 days are granted with credit limit equal to 2 x D&B High Credit up to $1,000,000 If Score is 6.00 - 7.99 then N30 days are granted with credit limit equal to 1.5 x D&B High Credit up to $750,000 If Score is 4.50 - 5.99 then N30 days are granted with credit limit equal to 1 x D&B High Credit up to $500,000 If Score is 2.00 - 4.49 then N30 days are granted with credit limit equal to .5 x D&B High Credit up to $250,000 If score is < 2.00 then account does not qualify for N30 days from and the customer is offered COD, CIA or Credit Card as methods of payment

UNDERSTANDING CREDIT SCORING TECHNIQUES AND BEST PRACTICES

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