Financial Risk Management Framwork & Basel Ii Icmap

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Financial Risk Management FrameworkJaved H Siddiqi

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Risk Management

“Every experience you have is designed to make you stronger”

Javed H. Siddiqi

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Managing Risk Effectively: Three Critical Challenges

GLO

BALISM

GLO

BALISM

TECHNOLO

GY

TECHNOLO

GY

CHANGECHANGE

Management Challenges for the 21st Century

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What is Risk?

•Risk, in traditional terms, is viewed as a ‘negative’. Webster’s

dictionary, for instance, defines risk as “exposing to danger or hazard”.

•The Chinese give a much better description of risk

>The first is the symbol for “danger”, while

>the second is the symbol for “opportunity”, making risk a mix of danger and opportunity.

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Risk Management

Risk management is present in all aspects of life; It is about the everyday trade-off between an expected reward an a potential danger. We, in the business world, often associate risk with some variability in financial outcomes. However, the notion of risk is much larger. It is universal, in the sense that it refers to human behaviour in the decision making process. Risk management is an attempt to identify, to measure, to monitor and to manage uncertainty.

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Risk Assessment

Assess your risk bearing capacity

How much risk can you tolerate?

How much risk protection can you afford?

How much risk are you willing to accept

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Risk Management

Risk management integrates production, marketing & financial decisions

Risk management is a planning process where you assemble and assess information

Every management decision carries risk management implications

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Risk Management Requires

Understanding of Your financial situation

Understanding sources of risk and potential risk

Understanding of risk management tools

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Risk Management Includes:

Evaluation of alternative plans & risk management strategies

Implementation of the plan

Monitoring the plan

Developing probabilities to formalize risk assessment

Steps in theRisk Management Process

Determine the corporation’s objectivesIdentify the risk exposures Quantify the exposures Assess the impactExamine alternative risk management toolsSelect appropriate risk management approachImplement and monitor program

The Bottom Line:It All Boils Down to Capital

“Capital” Assets less liabilities; owners’ equity; net worth Support for (riskiness of) operations Thus, supports profitability and solvency of firm

“Capital Management” Determine need for and adequacy of capital Plans for increasing or releasing capital Strategy for efficient use of capital

Why Do We Care About Managing Capital?

Leads to solvency and profitabilityBenefits of solidity and profitability

Higher company value Happy claimholders Better ratings Less unfavorable regulatory treatment Ability to price products competitively Customer loyalty Potentially lower costs

What Does Capital Management Entail?

CapitalManagement

ProductPricing Financial

Risk Mgt.

SettingObjectives

RaisingCapital

StrategicPlanning

LiabilityValuationAsset

Allocation

RiskManagement

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Capital Allocation and RAPMCapital Allocation and RAPM The role of the capital in financial institutions and

the different type of capital. The key concepts and objective behind regulatory

capital. The main calculations principles in the Basel II the

current Basel II Accord. The definition and mechanics of economic capital. The use of economic capital as a management tool

for risk aggregation, risk-adjusted performance measurement and optimal decision making through capital allocation.

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Role of Capital in Financial InstitutionAbsorb large unexpected lossesProtect depositors and other claim holdersProvide enough confidence to external

investors and rating agencies on the financial heath and viability of the institution.

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Type of Capital

Economic Capital (EC) or Risk Capital.

An estimate of the level of capital that a firm requires to

operate its business.Regulatory Capital (RC).

The capital that a bank is required to hold by regulators

in order to operate.Bank Capital (BC) The actual physical capital held

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Economic Capital

Economic capital acts as a buffer that provides protection against all the credit, market, operational and business risks faced by an institution.

EC is set at a confidence level that is less than 100% (e.g. 99.9%), since it would be too costly to operate at the 100% level.

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Risk Measurement- Expected and Unexpected Loss

The Expected Loss (EL) and Unexpected Loss (UL) framework may be used to measure economic capital

Expected Loss: the mean loss due to a specific event or combination of events over a specified period

Unexpected Loss: loss that is not budgeted for (expected) and is absorbed by an attributed amount of economic capital Losses so remote that

capital is not provided to cover them.

500Expected Loss,

Reserves

Economic Capital =Difference 2,000

0Total Loss

incurred at x% confidence level

Determined by confidence level associated with targeted rating

Pro

bab

ilit

y

Cost

2,500

EL UL

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Financial Risk and Basel

Javed H Siddiqi

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BASEL-I Capital Calculation

Basel I Principles Strengthen the stability of the international banking system Create minimum risk-based capital adequacy requirements

Basel I Benefits Relatively simple framework Widely adopted Increased banks’ capital

Credit Risk + Market Risk

Capital Capital Adequacy Ratio

RIWAC

=

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Basel I Regulatory Capital Rules

Market riskCapital(Tier 3)

Market riskCapital(Tier 3)

• Short-term subordinated debt

SupplementaryCapital(Tier 2)

SupplementaryCapital(Tier 2)

• Perpetual securities

• Unrealised gains on investment

securities

• Hybrid capital instruments

• Long-term subordinated debt with

maturity > 5 years

Core Capital(Tier 1)

Core Capital(Tier 1)

• Stock issues

• Disclosed reserves

– Loan loss reserves to cushion

future losses or for smoothing

out income volatility

• 50% of total capital

Types of capital

Balance sheet assets

Off-balance sheet assets

Non-Traded

Traded

Risk weights

Basel I capital calculation

Capital (Tiers 1, 2, 3)

Risk-Weighted Assets and Contingents

≥ 8%

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RIWAC Calculation

RIWAC

On-Balance Sheet

xCounterparty Weighting

Off-Balance Sheet Risk

xCounterparty Weighting

xCredit Conversion Factor

= +

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RIWAC Weightings

On-Balance Sheet Risk

Banks SovereignsCorporate

s

Non OECD

OECD Non OECD OECD

100% 20% 100% 0% 100%

Off Balance Sheet Risk Cont. liabilities

Financial Guarantees

100% 20% N/A N/A 100%

Transactional Contingents

50% 10%N/A N/A

50%

Secured LCs Issued

20% 4%N/A N/A

20%

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BASEL I- RIWAC Examples

CorporateXYZ Bank Lends USD 100 M to UAE Corporate for 1 year Capital = USD 100 M X 100% (Risk Weight) X 8% (Capital

Adequacy) = USD 8 M

BanksXYZ Bank Lends USD 100 M to Barclays Bank for 2 years Capital = USD 100 M X 20% (Risk Weight) X 8% (Capital

Adequacy) = USD 1.6 M

ContingentsXYZ confirms Sight L/C of USD 100 M issued by ABN AMRO Capital = USD 100 M X 20% (Risk Weight) X 20% (CCF) X

8% (Capital Adequacy) = USD 0.32 M

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Basel I regulatory capital rules – Credit risk (1)

Step 1: RWA = On BS exposure X Risk Weight

Step 2: Capital = 8% X RWA

Risk weight (%) On-balance sheet asset category

0Cash & goldObligations on OECD and PAK treasuries

20Claims on OECD banks Govt. agency securitiesClaims on municipalities

50 Residential mortgages

100Corporate bonds, equity, real-estateLess-developed countries’ debtClaims on non-OECD banks

On-balance sheet risk weights and Basel I capital calculation

Risk weight (%) Off-balance sheet asset category

0 OECD governments

20OECD banks and public sector entities

50Corporates and other counterparties

Credit Conversion Factor (%)

Off-balance sheet non-trading assets

0Undrawn commitments – Maturity ≤ 1 year

20Documentary credits related to shipment of goods

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Transaction-related contingencies – warranties, performance bonds

Undrawn commitments – Maturity > 1 year

100General guarantees, standby letters of credit, banker’s acceptance, etc

Off-balance sheet risk weights and Basel I capital calculation for non-trading assets

Step 1: Credit Equivalent Amount (CEA) = Notional amount X Credit Conversion Factor

Step 2: RWA = CEA X Risk Weight


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Basel I regulatory capital rules – Credit risk (2)Basel I regulatory capital rules – Credit risk (2)

Credit Conversion Factor (%)

Interest rates FX and Gold Equity derivatives Precious metalsCommodity contracts

Less than 1 year 0.0% 1.0% 6.0% 7.0% 10.0%

1-5 years 0.5% 5.0% 8.0% 7.0% 12.0%

More than 5 years 1.5% 7.5% 10.0% 8.0% 15.0%

Off-balance sheet risk weights and Basel I capital calculation for trading assets

Step 1: Current Exposure (CE) = Current marked-to-market value of asset

Step 2: Potential Future Exposure (PFE) = Notional amount X Credit Conversion Factor

Step 3: Credit Equivalent Amount (CEA) = CE + PFE

Step 4: RWA = CEA X Risk Weight


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BASEL I- Draw BacksCriticisms of Basel I Accord

• Lack of risk sensitivity of

capital requirements

• One-size-fits-all’ approach to

risk management

• Limited attention to credit risk

mitigation

• Over emphasis on minimum

capital requirements

• Exclusive focus on financial

risk

Consequences in the industry

• Sub-optimal lending

behavior

• Increased divergence

between regulatory

capital and economic

capital

• Regulatory capital

arbitrage through

product innovation

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Objectives “Basel II”

The objective of the New Basel Capital accord (“Basel II) is:

1. To promote safety and soundness in the financial system

2. To continue to enhance completive equality

3. To constitute a more comprehensive approach to addressing risks

4. To render capital adequacy more risk-sensitive

5. To provide incentives for banks to enhance their risk measurement capabilities

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Comparison

Basel I Basel 2Focus on a single risk measure More emphasis on banks’

internal methodologies, supervisory review and market discipline

One size fits all Flexibility, menu of approaches. Provides incentives for better risk management

Operational risk not considered Introduces approaches for Credit risk and Operational risk in addition to Market risk introduced earlier.

Broad brush structure More risk sensitivity

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Economic Objectives

Efficiency: best use of capital across business lines, impetus for risk based pricing and operational cost savings

Stability: ensure capital protection consistent with shareholder value optimization

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Economic Objectives

Growth sustainability: balanced Portfolio risk and return

Equity: level competitive playing field across(big and small) banks

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Overview of Basel II PillarsThe new Basel Accord is comprised of ‘three pillars’…The new Basel Accord is comprised of ‘three pillars’…

Pillar I

Minimum Capital Requirements

Establishes minimum standards for management of capital on a more risk sensitive basis:

• Credit Risk• Operational Risk• Market Risk

Pillar II

Supervisory Review Process

Increases the responsibilities and levels of discretion for supervisory reviews and controls covering:

• Evaluate Bank’s Capital Adequacy Strategies

• Certify Internal Models• Level of capital charge• Proactive monitoring of

capital levels and ensuring remedial action

Pillar III

Market Discipline

Bank will be required to increase their information disclosure, especially on the measurement of credit and operational risks.

Expands the content and improves the transparency of financial disclosures to the market.

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Development of a revised capital adequacy framework Components of Basel II

Pillar 1 Pillar 2 Pillar 3

The three pillars of Basel II and their principles

Basel II

Supervisory review process

• How will supervisory bodies assess, monitor and ensure capital adequacy?

• Internal process for assessing capital in relation to risk profile

• Supervisors to review and evaluate banks’ internal processes

• Supervisors to require banks to hold capital in excess of minimum to cover other risks, e.g. strategic risk

• Supervisors seek to intervene and ensure compliance

Market disclosure

• What and how should banks disclose to external parties?

• Effective disclosure

of:- Banks’ risk profiles- Adequacy of capital

positions• Specific qualitative

and quantitative

disclosures- Scope of application - Composition of

capital - Risk exposure

assessment - Capital adequacy

Minimum capital requirements

• How is capital adequacy measured particularly for Advanced approaches?

• Better align regulatory capital with economic risk

• Evolutionary approach to assessing credit risk- Standardised (external

factors)- Foundation Internal

Ratings Based (IRB)- Advanced IRB

• Evolutionary approach to operational risk- Basic indicator- Standardised- Adv. Measurement

Issu

eP

rin

cip

le

• Continue to promote safety and soundness in the banking system

• Ensure capital adequacy is sensitive to the level of risks borne by banks

• Constitute a more comprehensive approach to addressing risks

• Continue to enhance competitive equality

Objectives

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Overview of Basel II Approaches (Pillar I)

Approaches that can befollowed in determination

of Regulatory Capitalunder Basel II

Approaches that can befollowed in determination

of Regulatory Capitalunder Basel II

Total Regulatory

Capital

Total Regulatory

Capital

Operational Risk

Capital

Operational Risk

Capital

CreditRisk

Capital

CreditRisk

Capital

MarketRisk

Capital

MarketRisk

Capital

Basic IndicatorApproach

Basic IndicatorApproach

Standardized Approach


Advanced Measurement

Approach (AMA)

Advanced Measurement

Approach (AMA)



Internal Ratings Based (IRB)

Internal Ratings Based (IRB)

FoundationFoundation

AdvancedAdvanced

StandardModel

StandardModel

InternalModel

InternalModel

Score CardScore Card

Loss DistributionLoss Distribution

Internal ModelingInternal

Modeling

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The Three Pillars

The First Pillar - Minimum Capital Requirements

The Second Pillar - Supervisory Review Process

The Third Pillar - Market Discipline

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Pillar 1

Calculation of the total minimum capital requirements for credit, market and operational risk.

The minimum capital requirements are composed of three fundamental elements: a definition of regulatory capital, risk weighted assets and the minimum ratio of capital to risk weighted assets.

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RISK BASED SUPERVISION

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BASEL II : CAPITAL CHARGE

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Credit Risk

The standardized approachThe Internal Ratings-Based Approach

Foundation Advanced

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CREDIT RISK WEIGHTS

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Credit Exposure Classes

Sovereigns- countries, central banks and multilaterals with 0% risk

Banks and non-banks- banks, investment houses, securities firms

Retail-individuals/persons & their guarantees(credit card, personal loan, rem, small business) or pools of these loans with similar characteristics

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Credit Exposure Classes

Sme- exposure to individual owner, partners and enterprises owned by group usually with government incentives or programs

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Coverage And Compliance 110 signatory countries (ye 2003).

All banks, investment houses and securities firms, asset/fund management companies and bank owned/controlled insurance companies.

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C & C

Banking areas affected: regulatory compliance, audits, risk management practices, accounting standards, financial products and services, human resources, it/systems

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Internal Ratings Based

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FIRB VS. AIRB

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IRB

Borrower risk rating- inherent creditworthiness without considering facility type or security arrangements. Transformed into a PD

Facility risk rating-risk rating considering the various security arrangements or credit risk mitigation techniques(thus lower LGD values)

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IRB

CollateralsNettingGuarantees and credit derivatives

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LGD Valuations

FOUNDATION IRB CI REAL ESTATE= 35% RECEIVABLES FULLY SECURED LOANS=35% OTHER PHYSICAL COLLATERALS=40% UNSECURED LOANS=50% FINANCIAL ASSETS (SCALED BY HAIRCUTS)= 0.5-

15% SUBORDINATED CLAIMS=75%

ADVANCED IRB BANK OWN ESTIMATES

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Credit Risk Mitigants

Collateral Standard haircuts(issuer,rating, tenor, type) Mark to market Operational risks(eg. Legal) Concentration risks

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Credit Risk Mitigants

Netting Master netting legal agreements(net positions) Marked to market all Transactions Currency and maturity mismatches

Creditderivatives/guarantees Counterparty/issuer risks Derivatives documentation (legal) Market risks

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Credit Risk Impact

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Credit Risk Impact

IRB estimated to reduce credit risk capital charges by 2-3% versus standardized approach. Another possible 10-20% capital charge reduction versus foundation approaches.

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Key Basel Compliance Requirements

Reliable historical credit statistics: default rates, recoveries (e.G. Market valuation of collaterals), portfolio concentration data, financial statement analysis/ratio history and projections, exposure valuation)

Intensive credit risk analysis and portfolio modeling Skills

Integrated central exposure system with on line Analysis/processing functions

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Key Compliance Requirements

Robust internal ratingsAppropriate use of credit risk/var modelsAppropriate credit risk rating and

modelling software

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Market Risk Compliance

Timely and accurate daily mark to market accounting/data and valuation of fx and securities portfolio

Reliable and robust value at risk model Including historical simulation/ backtesting And stress testing results

Integrated on line market risk monitoring And control system

Well trained users(back, front and middle Office)

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Ops Risk

The Basic Indicator ApproachThe Standardised ApproachAdvanced Measurement Approach

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Ops Risk Impact

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Operating Risk Compliance

High awareness level of operational risk and Control inherent in all business processes, their Likelihood and financial loss impact significance

Timely and reliable information /monitoring of key Operational risk indicators/events (transaction Volume, financials, system downtimes, control Exceptions, process errors etc) to form part of Operational event loss data base

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Operating Risk Compliance

Establishing minimum risk control Benchmarks/standards and gaps versus actuals

Intensive operational risk & control trainingRobust operational risk models (loss given

event, Probability of loss, exposure indicators)

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Pillar 2 – Supervisory Review

Intended not only to ensure that banks have adequate capital to support all the risks in their business, but also to encourage banks to develop and use better risk management techniques in monitoring and managing their risks.

Supervisors are expected to evaluate how well banks are assessing their capital needs relative to their risks and to intervene, where appropriate.

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Pillar 2

Three main areas suited to treatment under Pillar 2:

Risks considered under Pillar 1 that are not fully captured by the Pillar 1 process (e.g. credit concentration risk)

Those factors not taken into account by the Pillar 1 process (e.g. interest rate risk in the banking book, business and strategic risk)

Factors external to the bank (e.g. business cycle effects).

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Four Key Principles of Supervisory Review

Principle 1: Banks should have a process for assessing their overall capital adequacy in relation to their risk profile and a strategy for maintaining their capital levels.

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Four Key Principles

Principle 2: Supervisors should review and evaluate banks’ internal capital adequacy assessments and strategies, as well as their ability to monitor and ensure their compliance with regulatory capital ratios. Supervisors should take appropriate supervisory action if they are not satisfied with the result of this process.

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Four Key Principles

Principle 3: Supervisors should expect banks to operate above the minimum regulatory capital ratios and should have the ability to require banks to hold capital in excess of the minimum.

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Four Key Principles

Principle 4: Supervisors should seek to intervene at an early stage to prevent capital from falling below the minimum levels required to support the risk characteristics of a particular bank and should require rapid remedial action if capital is not maintained or restored.

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Pillar 3 Market Discipline

The purpose of Pillar 3 - market discipline is to complement the minimum capital requirements (Pillar 1) and the supervisory review process (Pillar 2).

Encourage market discipline by developing a set of disclosure requirements which will allow market participants to assess key pieces of information on the scope of application, capital, risk exposures, risk assessment processes, and hence the capital adequacy of the institution.

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Banks approach to Basel II TransformationA Journey of Seven Steps…

Phase I: Gap Analysis Phase II: ImplementationRoadmap

Phase III: Implementation

Phase IV: ComplianceAnd Certification

Supervisory Certification,Parallel Run and Go Live

Basel II Program Initiation

Gap AnalysisImplementation Roadmap

Organization, Policies And Processes Redesign

Data Management & IT Applications

Analytics- Models, Methodologies and Validation

Approach to Basel II: Approach to Basel II: Recommended Seven Steps

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Challenges

Establishing a sound credit risk Rating system Enhancing risk management Infrastructure: var

based Measurement using central data Repository and risk engines

Capital allocation by Business:higher returns to Compensate higher risks

Establishing a risk based culture

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MINIMUM CAPITAL REQUREMENTS FOR BANKS (SBP Circular no 6 of 2005)

IRAF Rating

Required CAR effective from

Institutional Risk Assessment Framework (IRAF)

31st Dec. 2005 31st Dec., 2006 and onwards

1 & 2 8% 8%

3 9% 10%

4 10% 12%

5 12% 14%

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Operational Risk and the New Capital Accord

Operational risk is now to be considered as a fully recognized risk category on the same footing as credit and market risk.

It is dealt with in every pillar of Accord, i.e., minimum capital requirements, supervisory review and disclosure requirements.

It is also recognized that the capital buffer related to credit risk under the current Accord implicitly covers other risks.

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Operational risk

Background

Description

• Three methods for calculating operational risk capital charges are available, representing a continuum of increasing sophistication and risk sensitivity:

(i) the Basic Indicator Approach (BIA)

(ii) The Standardised Approach (TSA) and

(iii) Advanced Measurement Approaches (AMA)

• BIA is very straightforward and does not require any change to the business

• TSA and AMA approaches are much more sophisticated, although there is still a debate in the industry as to whether TSA will be closer to BIA or to AMA in terms of its qualitative requirements

• AMA approach is a step-change for many banks not only in terms of how they calculate capital charges, but also how they manage operational risk on a day-to-day basis

Available approaches

Available approaches

Operational risk is defined as the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. This definition includes legal risk, but excludes strategic

and reputation risk

Operational risk is defined as the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. This definition includes legal risk, but excludes strategic

and reputation risk

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The Measurement methodologies

Basic Indicator Approach:

1. Capital Charge = alpha X gross income

* alpha is currently fixed as 15% Standardized Approach:

2. Capital Charges = ∑beta X gross income (gross income for business line = i=1,2,3, ….8)

Value of “Greeks” are supervisory imposed

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The Measurement methodologies

Business Lines Beta Factors1. Corporate Finance 18%2. Trading & Sales 18%3. Retail Banking 12%4. Commercial Banking 15%5. Payment and Settlement 18%6. Agency Services 15%7. Asset Management 12%8. Retail Brokerage 12%

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Operational risk is the risk of loss resulting from inadequate or failed internal processes, people, and systems or from external events.

Categories of OR events Execution, Delivery & Process Management (processing error, information

transfer, data coding,...) Clients, Products & Business Practices (clients misinformation, complaints and

discounts due to errors, products mispecification...) Internal fraud (thefts and frauds by employees) External fraud (hold-up, thefts,..) Employment practices & workplace safety (contract termination, disputes with

employees...) Damage to physical assets Business disruption & system failures (IT break-down, hacking...)

I. Definition

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I. Definition

The Specific Nature of Operational Risk Embedded risk

Not a transaction-risk but a risk embedded in processes, people and systems and due to external events.

Inherent risk A large part of operational risk is inherent to the business in which we are

engaging and inherent to management processes. Hidden risk

The costs due to OR are difficult to trace or anticipate since most are hidden in the accounting framework.

Leads to underestimation of the risk (e.g. information security). Unstable risk

Not linearly linked to the size of the activities. Small activities can be very risky high risk, and vice versa.

OR can be very unstable and grow exponentially in a short period. Reputation risk

A second order risk, leading to additional damage in the form of damage to reputation.

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Underlying causes of operational losses : processes - people - systems -

or external events.

Legal risk included , strategic and reputation risk excluded.

Appropriate manager per category of operational event :

Execution, Delivery & Process Management : ORM

Clients, Product & Business Practices : ORM

Internal fraud : Inspection / ORM

External fraud : Inspection

Employment practices & workplace safety : Security

Damage to physical assets : Security

Business disruption & system failures : Security

I. Definition

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General Objective :

Define rules and procedures for banks to properly cover

their different types of risks due to business activity.

Three Pillars

Pillar One : Capital Adequacy - formulas and calculations

Pillar Two : Supervisory Review Process - adjustment of

supervision to individual risks profiles

Pillar Three : Market Discipline - information disclosure

II. Outlines of the Basle Reform

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Regulatory Capital for OR introduced for the first time

Rule of thumb : OR capital = 12% of minimum capital requirement

Basic indicator approach (BI ):

OR capital function of gross income (15%)

Gross income = interest margin + fees + other revenues

Only accessible to local banks

Standardised approach ( )

OR capital function of gross income per business line

Beta factor between 12% and 18% of gross income, estimated via

QIS on a sample of 29 institutions.


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Advanced Measurement Approach (AMA ) in Basle II:

• Banks are free to model their OR capital themselves

• Strongly recommended for internationally active banks

• Floor capital at 75% (so far) of the capital level under the Standardised Approach, and 9% of total regulatory capital

• Submitted to quantitative and qualitative standards, such as:

incident reporting history of 5 years, minimum 3 years;

mapping of risks and losses to regulatory categories

independent ORM function;

implication of the senior management;

written policies and procedures;

active day-to-day OR management.


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Advanced Measurement Approach (AMA ) in Basle II:

• Several types of models admitted by the Committee:

Loss Distribution Approach (LDA) : purely quantitative

Scorecard approach :mainly quantitative : assessment of risk level

and quality of risk management based on different dimensions

Mix of the two : capital calculations based on incident data +

adjustments to account for risk management quality


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Quantitative approach : LDA (Loss Distribution Approach)

• Frequency distribution of losses per business line : Poisson distr.

• Severity distribution of losses per business line : logN distr.

Both distributions are combined by Monte Carlo simulations.

III. Modelling Operational Risk

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LDA• Modeling of frequency and of severity distribution of losses, per business line• Internal data : to model to body of the distribution• External data : to model extreme events (tail of the distribution)

Frequency

Loss amount

Body region Tail region

Internal data External data

Cut-off mix

99.9% = Required Capital

III. Modelling Operational Risk

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Paradox of the incident data collection :• Data collection is mandatory,• But external data essentially drive the capital amount.

Remaining issues on :

the cut-off mix

the relevant data to include (different processes in each firm)

Crucial data choice in the capital determination

Data collection needed for active ORM reasons.

III. Modeling Operational Risk

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Dashboards - Dynamic risk analysis

Key Risks /Key Performance Indicators

Risk & Control Self-Assesment (RCSA)

Internal Reporting : Mapping of losses

Four Dimensions of Operational Risks

IV. Managing Operational Risk

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Incident reporting tool :

Free to define, often Access based

Full reporting tool, for management purposes

Internal control when encoding

Fields to include per event :

1. Date

2. Event localisation : BU, department, service

3. Event type : codification of Basle categories

4. Business line : codification of Basle categories

5. Comment : nature of the event

6. Gross Loss amount

7. Recovery amount : via insurance / other

8. Actions taken : preventive / corrective

9. Reporter coordinates.

Dimension One : Incident Reporting

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First exploitation possibilities of an incident database

Summary statistics of the losses

! Matching the organisation chart rather than the Basle categories

Total losses, Min, Max, Frequency

“Low Frequency, High Severity” events

Identification of the potential “uncapped” risks

Top loss analysis

Examples?

“High Frequency, Low Severity” events

Recurrent, small, similar events

May signal a breach in control

Could be inherent to the activity (to be included in pricing)

Dimension One : Incident Reporting

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Dashboards Periodic reporting (monthly/quarterly) of KRI’s Early warning: timely identification of changes in control level : change

in the trend

Example

UNIT TOTAL ALLNumber Amount Average Loss/Income % TOP 5 amounts

Q 1 1.Q 2 2.Q 3 3.Q 4 4.

5.PER TYPEType xNumber Amount Average Loss/Income % TOP 5 amounts

Q 1 1.Q 2 2.Q 3 3.Q 4 4.

5.

Dimension Two : Dynamic Loss Analysis

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Dimension Three : Key Risks & Key Performance Indicators

People: turn-over, temporary staff, overtime, client complaints, absenteeism

Processing: outstanding confirmations, (status/duration of) reconciliation; failed &

overdue settlements; claims & complaints; manual bookings; reversals

Accounting: volumes & lead-times suspense-accounts; reversals;

Systems: logs of downtimes; hacking-attempts; project-planning-overruns

Risk Category KRI Measures Required*Tolerance Levels

Actual Score Indicator Management Action

Transaction Recording/ Processing

Front/Back Office reconciling items

No >1 day, Value

Transaction Recording/ Processing

Net marginal cost of interest charging

Value

Trade Settlement Trade Fails % of month's trades, duration of total fails

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Dimension Three : KRIs & KPIs

Headlines : Regular KRI reporting for all businesses and functions

Green, Amber and Red thresholds for all KRI’s

Develop new/better KRI’s on on-going basis

Discuss all KRI reports in OR committee

Immediate management response to red and amber

KRI’s

Trend analysis and local lessons learnt program

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Dimension Four : RCSA

Identification Assessment Mitigation

K E Y R IS K S

ID E N T IF IE DR IS K S

U n id e n tif ie dr isk s

C O N T R O L

T R A N S F E R

A V O ID

A c c e p ta b le r isk s

U N A C C E P T A B L ER IS K S

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Identification

Incident reporting analysis

Check list from the key risks library

Prioritization list with the line management

Orientation questionnaires with selected people

from the department.

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RCSA performed by local management, with the support of ORM RCSA processes for all key businesses and functions

High level management driven identification of key risk areas

Apply & document the analytic RCSA process

Report & discuss the outcomes of a RCSA in ORC

Implementation & progress-tracking of mitigating actions and

key risk indicators (KRI)

Line management is responsible and key for the output

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Assessment : Impact / Probability MatrixBased on a risk analysis report which reflects all (residual) risks and controls.

IMPACT

CatastrophicMajor

Possible

ModerateMinorInsignificant

Rare

Unlikely

Likely

Almost certain

PROBABILITY

• 1• 2• 3

• 4• 5

• 6• 7

• 8 • 9

• 10• 11• 12

• 13

• 14

• 15

• 16

• 18

• 19

• 17• 22

• 21

• 20

• 23

Note : each point on the graph represents a different event or potential risk.

Ex. Misleading capture screen in equity brokerage

Ex. Product misspecification

97


Mitigation of uncapped or significant risks via :

Better controls : process control / supervision /

training,

Transfer : insurance policies / merge of

activities,

Avoidance : activity suppression / outsourcing /

automation.

98

Quantitative assessment of active ORM techniques

Principle : modify the parameters of the losses distribution, to include

the impact of the active management.

Risk Adjusted Return on Capital (RAROC) adaptable to Operational

Risk.

We define:

with EL and EC readily available.

Operational Income is assumed equal to 5% of total revenues.

CapitalEconomic

ELIncomeOperatingRAROClOperationa

V. Measuring the impact of ORM

99


Scenario : AMA approach, and target RAROC of 18%. Board Objective : ORM should reduce EL by 15%.

Minus x% in the number of events in Business Line “i”, for the event types “j,k,l”.

Dashboard: Systematic reduction of events in BL “i”, event types “j,k,l”

Minus x% in the number of events in BL “i”, minus y% in the severity of losses for event types: “Internal fraud” and “Processing errors”.

Audit tracking: Application of audit recommendations in BL “i”

Minus x% in frequency and minus y% in severity for event types “Clients, products and business practices”,

Business line reorganization: New product review process for all BL

Cut off the x top losses, all Business Lines Lessons learned: Analysis of largest losses in Business Line (BL) “i”

Impact on the distributions Risk Management Action

100


-22%-20%---18%--19%--15%-15%-14%-15%-11%-18%-15%-37%Expected Loss

-14%-22%---10%--9%--10%-12%-5%-10%-3%-10%-11%-9%Unexpected Loss

-10%-10%---4%--4%---------Severity

-12%-22%---9%--7%--9%-12%-2%-10%-2%-10%-11%-8%Reg. Capital (by

cell)

-12%-12%---13%--15%--14%-15%-14%-15%----Frequency

-15.1%--7.0%-4.1%-9.7%-5.9%-3.9%-9.6%Reg. Capital (by

BL)

BL Reorganization Audit Tracking Dashboards Lessons Learned

-2

(2,2)

-2

(2,1)

-2

(1,2)

-6.1%

-2

(1,1)

-

(2,2)

-

(2,1)

-

(1,2)

-8.2%

-

(1,1)

-

(2,2)

-

(2,1)

-

(1,2)

-5.8%

-

(1,1)

-

(2,1)

Reg. Capital (total)

Number

Induced changes

-9.1%

-

(1,1)

--

(2,2)(1,2)

101


0.75%0.43%0,51%0.28%-BL2 – Retail Banking

243,922140,041165,38791,112-BL2 – Retail Banking

243,922202,704232,937189,114-TOTAL

BL Reorganization Audit Tracking DashboardsLessons

Learned Default AMA

Maximum acceptable cost (in % of total income)

-0.36%0,39%0.56%-BL1 – Asset Management/Private Banking

0.49%0.41%0,47%0.38%-TOTAL

-62,66367,55098,003-BL1 – Asset Management/Private Banking

BL Reorganization Audit Tracking DashboardsLessons

Learned Default AMA

Maximum acceptable cost (in currency units)

27.49%26.55%27.24%26.36%25.54%TOTAL

31.02%27.37%28.32%25.94%27.11%BL2 – Retail Banking

25.23%

Audit Tracking

25.54%

Dashboards

27.11%

Lessons Learned

22.57%

Default AMA

22.57%

BL Reorganization

BL1 – Asset Management/Private Banking

Operational RAROC

102

VI. Conclusion

ORM Goals– at board level : Decrease the likelihood of a catastrophic event

Cost - benefit analysis of controls

Compliance with regulatory requirements

Lower economic & regulatory capital

ORM Goals and Ways – at business unit level : Consolidated incident reporting

Involvement of line management

Active Management of operational risks

Set-up and use of dashboards

Implementation of RCSA

103

Market Risk and Basel II

It is the risk that the value of on and off-balance sheet positions of a

financial institution will be adversely affected by movements in market rates or prices such as interest rates, foreign

exchange rates, equity prices, credit spreads and/or commodity prices resulting in a loss to earnings and

capital.

104

FinancialRisks Liquidity Risk

Operational Risk

Regulatory Risk

Human FactorRisk

Market Risk

Equity Risk

Interest Rate Risk

Currency Risk

Commodity Risk

Trading Risk

Gap Risk

Credit RiskPortfolio

Concentration Risk

Transaction Risk Counterparty Risk

Issuer Risk

Types of financial risk

105

Market Risk under Basel II

Standardized ApproachBuilding Block Approach: Capital charge captured separately for

each risk and then summed. Trading book used for general and specific risk in interest and equities markets. Both trading and banking books are used for general risk in currency and commodities markets.

Internal ModelVAR modeling: On daily basis and 99th percentile one-tailed

confidence interval is to be used, 10days holding period.

106

• Convergence of Economies• Easy and faster flow of information• Skill Enhancement• Increasing Market activity

Why the focus on Market Risk Management ?

Leading to

•Increased Volatility•Need for measuring and managing

Market Risks•Regulatory focus•Profiting from Risk

107

Measure, Monitor & Manage – Value at Risk

Value-at-Risk

Value-at-Risk is a measure of Market Risk, which measures the maximum loss in the market value of a portfolio with a given confidence

VaR is denominated in units of a currency or as a percentage of portfolio holdings

For e.g.., a set of portfolio having a current value of say Rs.100,000- can be described to have a daily value at risk of Rs. 5000- at a 99% confidence level, which means there is a 1/100 chance of the loss exceeding Rs. 5000/- considering no great paradigm shifts in the underlying factors.

It is a probability of occurrence and hence is a statistical measure of risk exposure

Value at Risk

Certainty is 95.00% from 2.6 to +Infinity

.000

.005

.011

.016

.022

0

108.2

216.5

324.7

433

1.5 2.9 4.3 5.6 7.0

108

Variance-Variance-covariancecovariance

Matrix

Variance-Variance-covariancecovariance

Matrix

MultiplePortfoliosMultiple

Portfolios

YieldsDurationYields

Duration

Incremental VaR

Incremental VaR

Stop LossStop Loss

PortfolioOptimization

PortfolioOptimization

VaRVaR

Features of RMD VaR Model

Facility of multiple methods and portfolios in single modelReturn Analysis for aiding in trade-offFor Identifying and isolating Risky and safe securitiesFor picking up securities which gel well in the portfolioFor aiding in cutting losses during volatile periodsHelps in optimizing portfolio in the given set of constraints

109

Value at Risk-VAR

Value at risk (VAR) is a probabilistic method of measuring the potentional loss in portfolio value over a given time period and confidence level.

The VAR measure used by regulators for market risk is the loss on the trading book that can be expected to occur over a 10-day period 1% of the time

The value at risk is $1 million means that the bank is 99% confident that there will not be a loss greater than $1 million over the next 10 days.

110

Value at Risk-VAR

VAR (x%) = Zx%σ

VAR(x%)=the x% probability value at risk

Zx% = the critical Z-value

σ = the standard deviation of daily return's on a percentage basis

VAR (x%)dollar basis=

VAR (x%) decimal basis X asset value

111

Example: Percentage and dollar VAR

If the asset has a daily standard deviation of returns equal to 1.4 percent and the asset has a current value of $5.3 million calculate the VAR(5%) on both a percentage and dollar basis.

Critical Z-value for a VAR(5%)= -1.65, VAR(10%)=-1.28, VAR(1%)=-2.32

VAR(5%) = -1.65(σ) = -1.65(.014) = -2.31%

VAR (x%)dollar basis= VAR (x%) decimal basis X asset value

VAR (x%)dollar basis= -.0231X5,300,000 = $-122,430

Interpretation: there is a 5% probability that on any given day, the loss in value on this

particular asset will equal or exceed 2.31% or $122,430

112

Time conversions for VAR

VAR(x%)= VAR(x%)1-day√J

Daily VAR: 1 day Weekly VAR: 5 days Monthly VAR: 20 days Semiannual VAR: 125 days Annual VAR: 250 days

113

Converting daily VAR to other time bases:

Assume that a risk manager has calculated the daily VAR(10%) dollar basis of a particular assets to be $12,500.

VAR(10%)5-days(weekly) = 12,500 √5= 27,951

VAR(10%)20-days(monthy) = 12,500 √20= 55,902

VAR(10%)125-days = 12,500 √125= 139,754

VAR(10%)250-days = 12,500 √250= 197,642

114

Understanding of Asset & Liability Management (ALCO)

The process of making decision about the composition of assets and liabilities and their risk assessment is known as asset /liability management.

The decisions are usually made by the asset/liability management committee (ALCO) that is responsible for the overall financial direction of the bank.

115

Classification of Assets and Liabilities

Rate-sensitive assets (RSAs)Rate-sensitive liabilities (RSLs) Those assets and Liabilities whose interest return or costs vary

with interest rate changes over given time horizon referred to as rate sensitive assets/liabilities.

Non rate-sensitive (NRS) Those assets and Liabilities whose interest return or costs do

not vary with interest rate movement over the same time horizon referred to as non-rate sensitive

116

Gap and Relative Ratio

Gap= RSA – RSL

Relative gap ratio= Gap/Total assets

Interest–sensitivity ratio=RSA/RSL

117

Interest–sensitivity

A financial institution at given time may be asset or liability sensitive.

Asset sensitive e.g. RSA(100B)-RSL(50B) Positive gap or Interest-sensitivity ratio > 1 Bank will experience an increase in their net interest income when

interest rate increase and a decrease in their net interest income when interest rate fall.

Liability sensitive e.g. RSA(50B)-RSL(100B)

Negative gap or Interest-sensitivity ratio < 1 Bank will experience an decrease in their net interest income when

interest rate increase and a increase in their net interest income when interest rate fall.

118

Gap, Interest Rate Changes, and Net Interest Income

Gap Change in Interest Rates

Change in Net Interest

Income

Positive RSA>RSL Increase Increase

Positive RSA>RSL Decrease Decrease

Negative RSA<RSL Increase Decrease

Negative RSA<RSL Decrease Increase

Zero RSA=RSL Increase No Change

Zero RSA=RSL Decrease No Change

119

Managing Interest Rate Risk Rs/$ Gap

Aggressive asset/liability management The aggregative asset/liability management focuses

on increasing the net interest income through altering the portfolio of the institution.

Defensive asset/liability management The goal of defensive asset/liability management is

to insulate the net interest income from changes in interest rate

120

Duration Gap Analysis

The duration gap is the difference between the duration of a bank’s assets and liabilities.

It is a measure of interest rate sensitivity that helps to explain how changes in interest rate affect the market value of a bank’s assets and liabilities, and, in turn, its net worth.

NW=A-L

∆NW= ∆A- ∆L

121

Measurement of the Duration GapBalance Sheet DurationAssets Rs Duration (Yrs) Liabilities Rs Duration

(Yrs)Cash 100 0.00 Deposit 1 Yr 600 1.00

Loans 400 1.25 Deposit 5 Yr 300 5.00

T. Liabilities 900 2.33

Mort 500 7.00 Equity 100

Loans 1,000 4.00 1,000

DGAP (duration gap)=Da-WDL

DGAP (duration gap)=4.0 – (0.9)(2.33) = 4.00-2.10= 1.90 YearsDa= Average duration of assets

DL=Average duration of liabilities

W=Ratio of total liabilities to total assets

Suppose that current interest rate are 11% and are expected to increase by 100 basis points(1%)

%age change in the Net Worth=%∆Net Worth= (-1.90)(1/1.11) = -1.7%

Amt change in the Net Worth=∆Net Worth= (-1.90)(1/1.11) x TA= -1.7%X1000= -17

122

Duration Gap, Interest Rate and Changes in Net Worth

Duration Gap

Change in interest Rate

Change in Net Worth

Positive Increase Decrease

Positive Decrease Increase

Negative Increase Increase

Negative Decrease Decrease

Zero Increase No Change

Zero Decrease No Change

123

History

COUNTRY YEAR NATURE RESULTS

Mexico 1994-95

Exchange rate crisis

Budget deficit increased leading to massive government borrowing. The resultant money supply expansion pushed up prices.

East Asia 1997 Bank run crisis Capital flight. Bank run crises and currency run crises latter in 1999.

Russia 1998 Interest rate crisis.

Huge rise in budget deficit.

Ecuador 1999 Currency crisis Currency depreciated by 66.3% against the US dollar.

Turkey 2001-02

Interest rate instability

Overnight interbank interest rate increased by 1700% . Domestic interest rate reached 60% . Domestic stock market crashed.

Argentina 2001-02

Debt crisis Default on public debt.

124

Credit Risk Management

125

Credit Risk

Credit risk refers to the risk that a counter party or borrower may default

on contractual obligations or agreements

126

Standardized Approach (Credit Risk) The Banks are required to use rating from External Credit Rating

Agencies (ECAIS). (Long Term)

SBP Rating Grade ECA Scores PACRA JCR-VIS Risk Weight (Corporate)

1 0,1 AAA

AA+

AA

AA-

AAA

AA+

AA

AA-

20%

2 2 A+

A

A-

A+

A

A-

50%

3 3 BBB+

BBB

BBB-

BBB+

BBB

BBB-

100%

4 4 BB+

BB

BB-

BB+

BB

BB-

100%

5 5,6 B+

B

B-

B+

B

B-

150%

6 7 CCC+ and below

CCC+ and below 150%

Unrated Unrated Unrated Unrated 100%

127

Short-Term Rating Grade Mapping and Risk Weight

External grade (short term claim on banks and corporate)

SBP Rating Grade

PACRA JCR-VIS

Risk Weight

1 S1 A-1 A-1 20%

2 S2 A-2 A-2 50%

3 S3 A-3 A-3 100%

4 S4 Other Other 150%

128

MethodologyCalculate the Risk Weighted Assets

Solicited Rating

Unsolicited Rating

Banks may use unsolicited ratings (if solicited rating is not available) based on the policy approved by the BOD.

129

Short-Term Rating

Short term rating may only be used for short term claim. Short term issue specific rating cannot be used to risk-

weight any other claim.

e.g. If there are two short term claims on the same counterparty.

1. Claim-1 is rated as S2 2. Claim-2 is unrated

Claim-1 rated as S2 Claim-2 unrated

Risk -weight 50% 100%

130

Short-Term Rating (Continue)

e.g. If there are two short term claims on the same counterparty.

1. Claim-1 is rated as S4

2. Claim-2 is unrated

Claim-1 rated as S4

Claim-2 unrated

Risk -weight 150% 150%

131

Ratings and ECAIs

Rating Disclosure

Banks must disclose the ECAI it is using for each type of claim.

Banks are not allowed to “cherry pick” the assessments provided by different ECAIs

132

Basel I v/s Basel IIBasel: No Risk Differentiation

Capital Adequacy Ratio = Regulatory Capital / RWAs (Credit + Market) 8 % = Regulatory Capital / RWAs

RWAs (Credit Risk) = Risk Weight * Total Credit Outstanding Amount RWAs = 100 % * 100 M = 100 M

8 % = Regulatory Capital / 100 M

Basel II: Risk Sensitive Framework

RWA (PSO) = Risk Weight * Total Outstanding Amount = 20 % * 10 M = 2 M

RWA (ABC Textile) = 100 % * 10 M = 10 M

Total RWAs = 2 M + 10 M =12 M

133

RWA & Capital Adequacy Calculation(In Million)

Customer Title RatingOutstanding

BalanceRisk

WeightRWA = RW * Outstanding

CAR (%)Total Capital

Required

PAKISTAN STATE OIL AAA 100 20% 20 8% 1.6

DEWAN SALMAN FIBRE LIMITED A 100 50% 50 8% 4.0

RELIANCE WEAVING MILLS (PVT) LTD BBB+ 100 100% 100 8% 8.0

RUPALI POLYESTER LIMITED B 100 150% 150 8% 12.0

Total: 400 320 25.6

134

Credit Risk Mitigation (CRM)

Where a transaction is secured by eligible collateral.

Meets the eligibility criteria and Minimum requirements.

Banks are allowed to reduce their exposure under that particular transaction by taking into account the risk mitigating effect of the collateral.

135

Adjustment for Collateral:

There are two approaches:

1. Simple Approach

2. Comprehensive Approach

136

Simple Approach (S.A) Under the S. A. the risk weight of the

counterparty is replaced by the risk weight of the collateral for the part of the exposure covered by the collateral.

For the exposure not covered by the collateral, the risk weight of the counterparty is used.

Collateral must be revalued at least every six months.

Collateral must be pledged for at least the life of the exposure.

137

Comprehensive Approach (C.A)

Under the comprehensive approach, banks adjust the size of their exposure upward to allow for possible increases.

And adjust the value of collateral downwards to allow for possible decreases in the value of the collateral.

A new exposure equal to the excess of the adjusted exposure over the adjusted value of the collateral.

counterparty's risk weight is applied to the new exposure.

138

e.g.Suppose that an Rs 80 M exposure to a particular counterparty is secured by collateral worth Rs 70 M. The collateral consists of bonds issued by an A-rated company. The counterparty has a rating of B+. The risk weight for the counterparty is 150% and the risk weight for

the collateral is 50%. The risk-weighted assets applicable to the exposure using the

simple approach is therefore:

0.5 X 70 + 1.50 X 10 = 50 million

Risk-adjusted assets = 50 M Comprehensive Approach: Assume that the adjustment to exposure

to allow for possible future increases in the exposure is +10% and the adjustment to the collateral to allow for possible future decreases in its value is -15%. The new exposure is:

1.1 X 80 -0.85 X 70 = 28.5 million

A risk weight of 150% is applied to this exposure:

Risk-adjusted assets = 28.5 X 1.5 =42.75 M

139

Credit riskBasel II approaches to Credit Risk

Standardised Approach Foundation Advanced

Internal Ratings Based (IRB) Approaches

Evolutionary approaches to measuring Credit Risk under Basel II

• RWA based on externally

provided:– Probability of Default (PD)– Exposure At Default (EAD)– Loss Given Default (LGD)

• RWA based on internal

models for:– Probability of Default (PD)

• RWA based on externally

provided:– Exposure At Default (EAD)– Loss Given Default (LGD)

• RWA based on internal

models for– Probability of Default (PD)– Exposure At Default (EAD)– Loss Given Default (LGD)

• Limited recognition of

credit risk mitigation &

supervisory treatment of

collateral and guarantees

• Limited recognition of

credit risk mitigation &

supervisory treatment of

collateral and guarantees

• Internal estimation of

parameters for credit risk

mitigation – guarantees,

collateral, credit derivatives

Basel II provides a ‘tailored’ or ‘evolutionary’ approach to banks that is sensitive to their credit risk profiles

Increasing complexity and data requirementIncreasing complexity and data requirement

Decreasing regulatory capital requirementDecreasing regulatory capital requirement

140

Credit Risk – Linkages to Credit Process

Transaction Credit Risk Attributes

Exposure at Default

Loss Given Default

Probability of Default

Exposure Term

Economic loss or severity of loss in the event of default

Likelihood of borrower default

over the time horizon

Expected amount of loan when default occurs

Expected tenor based on pre-payment, amortization,

etc.

CREDIT POLICY

RISK RATING / UNDERWRITING

COLLATERAL / WORKOUT

LIMIT POLICY / MANAGEMENT

MATURITY GUIDELINES

INDUSTRY / REGION LIMITS

BORROWER LENDING LIMITS

PortfolioCredit Risk Attributes

Relationship to other assets within the portfolio

Exposure size relative to the portfolio

Default Correlation

Relative Concentration

141

The causes of credit risk

The underlying causes of the credit risk include the performance health of counterparties or borrowers.

Unanticipated changes in economic fundamentals.

Changes in regulatory measures Changes in fiscal and monetary policies

and in political conditions.

142

Risk ManagementRisk Management activities are taking place

simultaneously

RM performed by Senior management and Board of

Directors

Strategic

Macro

Micro Level

Middle management or unit devoted to

risk reviews

On-line risk performed by individual who on behalf of bank take calculated risk and manages it at their

best, eg front office or loan originators.

143

Best Practicesfor

Credit Risk ManagementCredit Risk Management

1. Rethinking the credit process

2. Deploy Best Practices framework

3. Design Credit Risk Assessment Process

4. Architecture for Internal Rating

5. Measure, Monitor & Manage Portfolio Credit Risk

6. Scientific approach for Loan pricing

7. Adopt RAROC as a common language

8. Explore quantitative models for default prediction

9. Use Hedging techniques

10. Create Credit culture

144

Increased reliance on objective risk assessment Increased reliance on objective risk assessment

Align “Risk strategy” & “Business Strategy” Align “Risk strategy” & “Business Strategy”

Credit process differentiated on the basis of risk, not size Credit process differentiated on the basis of risk, not size

Investment in workflow automation / back-end processes Investment in workflow automation / back-end processes

Active Credit Portfolio Management Active Credit Portfolio Management

1. Rethinking the credit process

145

2. Deploy Best Practices framework

Credit & Credit Risk Policies should be comprehensive Credit & Credit Risk Policies should be comprehensive

Set Limits On Different Parameters Set Limits On Different Parameters

Credit organisation - Independent set of people for Credit

function & Risk function / Credit function & Client Relations

Credit organisation - Independent set of people for Credit

function & Risk function / Credit function & Client Relations

Ability to Calculate a Probability of Default based on the

Internal Score assigned

Ability to Calculate a Probability of Default based on the

Internal Score assigned

Separate Internal Models for each borrower category and

mapping of scales to a common scale

Separate Internal Models for each borrower category and

mapping of scales to a common scale

146

3. Design Credit Risk Assessment Process

Credit Risk

Industry Risk Business Risk Management Risk Financial Risk

Industry Characteristics

Industry Financials

Market Position

Operating Efficiency

Track Record

Credibility

Payment Record

Others

Existing Fin. Position

Future Financial Position

Financial Flexibility

Accounting Quality

• External factors• Scored centrally once in

a year • Internal factors • Scored for each borrowing entity by the concerned credit officer

RMD provides well structured “ready to use” “value statements” to fairly capture and mirror the Rating officer’s risk assessment under each specific risk factor as part of the Internal Rating Model

147

Credit Rating System consists of all of the methods, processes, controls and data collection and IT systems that support the assessment of credit risk, the assignment of internal risk ratings and the quantification of default and loss estimates.

The New Basle Capital Accord

• Appropriate rating system for each asset class• Multiple methodologies allowed within each asset class (large corporate , SME)

•Each borrower must be assigned a rating

•Two dimensional rating system•Risk of borrower default•Transaction specific factors (For banks using advanced approach, facility rating must exclusively reflect LGD)

•Minimum of nine borrower grades for non-defaulted borrowers and three for those that have defaulted

CORPORATE/ BANK/ SOVEREIGN EXPOSURES

•Each retail exposure must be assigned to a particular pool

•The pools should provide for meaningfuldifferentiation of risk, grouping of sufficiently homogenous exposures and allow for accurate and consistent estimation of loss characteristics at pool level

RETAIL EXPOSURES

4. Architecture for Internal Rating

148

ONE DIMENSIONAL

Risk Grade I II III IV V VI VII

Industry XBusiness XManagement XFinancial XFacility Strucure XSecurity XCombined X

RRMD’s modified TWO DIMENSIONAL approach

Rating reflects Expected Loss

CONCEPTUALLY SOUND INTERNAL RATING MODEL – CAPTURES PD, LGD SEPARATELY

Client RatingRisk Grade I II III IV V VI VIIIndustry XBusiness XManagement XFinancial XClient Grade X

Facility RatingRisk Grade I II III IV V VI VIIFacility Structure XCollateral XLGD Grade X

Differs from the two dimensional system portrayed above in that it records LGD rather than EL as the second grade. The benefit of this approach is that rater’s LGD judgment can be evaluated and refined over time by comparing them to loss experience.

The Facility grade explicitly measures LGD. The rater would assign a facility to one of several LGD grades based on the

likely recovery rates associated with various types of collateral, guarantees or

other factors of the facility structure.

4. Architecture for Internal Rating…contd.

149

What is a Rating System? A rating system is one by which borrowers/facilities

are systematically assigned to (grouped into) rating grades according to the credit risk characteristics (rating criteria or risk factors) of the borrowers/facilities

Rating grades 1 65432 7 default

150

Types of Rating System:Hybrid Rating System

Rating systems that uses both expert judgements and statistical modelling techniques - the most commonly-used rating systems in industry

Classic expert judgement-

based systemPure model-based system

Expert judgement-based system with

quantitative guidelines

Model-based system with judgemental

overrides

Expert-derived models

Constrained judgement

Spectrum of Rating Systems

Hybrid system - the most commonly-used in the industry

151

Types of Rating System:An Example

RISK FACTORS SCORE RELATIVE IMPORTANCE

Subjective factors1. Management 32% Strong 100 Weak 02. Entry barrier 25% High 100 Low 0

Objective factors 3. Gearing 34.5% <=50% 100 > 50% 04. Earnings growth 8.5% >= 10% 100 < 10% 0

Risk factors &

scores determined

by judgements

Relative importance determined by models

152

Types of Rating System:An Example

The range of scores would lie between “0” (i.e. weak management, low entry barrier, gearing >50% and earnings growth <10%) to “100” (i.e. strong management, high entry barrier, gearing <=50% and earnings growth >=10%)

Assume the Bank maps score ranges to rating grades:

e.g. if a borrower has a strong management, the industry has low entry barrier, the gearing is 80%, and earnings growth is 30%, then it would have credit score: 10032% + 025% + 034.5% + 1008.5% = 40.5 and the borrower would be assigned to rating grade 5

Rating grades 65432 7

(95,100] (70,95] (60,70] (50,60] (40,50] (20,40] [0,20]

1

Score ranges

153

FIRB Approach for corporate, bank & sovereign exposures: Bank estimates PD for each borrower rating LGD, EAD and M are prescribed by the SBP (supervisory estimates)

AIRB Approach for corporate, bank & sovereign exposures: Bank estimates PD for each borrower rating it also estimates LGD for each facility rating it also estimates EAD for each facility type it also calculates M according to rules prescribed by the SBP

For retail exposures: Bank estimates PD, LGD and EAD for each pool

Quantification of a Rating System

154

For FIRB or AIRB Approach for Corporate/Commercial/SME, bank/FI & sovereign exposures, 3 methods can be used to estimate the PD of a borrower rating

1. Internal default experience

2. Mapping to external data

3. Statistical default models

Quantification of a Rating System:PD of Corporate/Commercial/SME, Bank/FI & Sovereign Exposures

155

1. Internal default experience:

e.g. in the past 5 years, annual default rates of borrowers assigned to rating grade 4 were 10%, 12%, 9%, 8% and 11% respectively. PD of rating grade 4 for this year can be estimated as the simple average of these default rates, i.e.:

(10% + 12% + 9% + 8% + 11%) 5 = 10%


156

2. Mapping to external data:

e.g. By comparing the rating criteria of its internal rating system with those of the Moody’s, Bank concludes that 50% of the borrowers assigned to its rating grade 2 would have Moody’s ratings “Baa1”, 25% “A3” and 25% “Ba1”. In the past 5 years, average annual default rates of these Moody’s ratings were 3%, 2% and 4% respectively. The Bank’s rating grade 2 can be estimated as:

50% 3% + 25% 2% + 25% 4% = 3%

There are many types of mapping methodologies


157

3. Statistical default models:e.g. Bank uses a model-based rating system, under which PD is estimated for each borrower. There are 3 borrowers assigned to rating grade 3, with PD estimated to be 4.5%, 5% and 5.5% respectively by the model. PD of rating grade 3 can be estimated as the simple average of the individual PDs of these borrowers, i.e.:

(4.5% + 5% + 5.5%) 3 = 5%

5% will be used for all the 3 borrowers for CAR purpose, regardless of the individual PDs generated from the model

Quantification of a Rating System:PD of Corporate/Commercial/SME, Bank & Sovereign Exposures

158

What is Validation?

Basel definition: “encompasses a range of processes and activities that contribute to an assessment of whether ratings adequately differentiate risk, and whether estimates of risk components appropriately characterise the relevant aspects of risk”

Bank’s responsibility to demonstrate its rating system meets minimum requirements

Review of a Bank’s validation process a major part of the IRB recognition process

159

Six Principles of the Validation

Six Principles of the Validation of the Basel Accord Implementation

(i) Validation is fundamentally about assessing the predictive ability of a bank’s risk estimates and the use of ratings in credit processes(ii) The bank has primary responsibility for validation(iii) Validation is an iterative process(iv) There is no single validation method(v) Validation should encompass both quantitative and qualitative elements(vi) Validation processes and outcomes should be subject to independent review

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Basel Approach to Validation (1)

Closely aligned with the 6 principles Bank conducts its own internal validation of

the rating system, estimates of risk components & the risk ratings generation processes

Internal validation clearly documented & shared with Regulator

Individuals involved in validation must have necessary skills & knowledge and independence

No universal validation tool

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No industry “best practice” standard on validation

Quantitative techniques very diverse, portfolio specific, and still evolving

Setting prescriptive quantitative standards & benchmarks for IRB systems could stifle innovation

Principles-based approaches by other supervisors

Views of external consultants & industry experts

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Qualitative and Quantitative elements. Qual. - processes, procedures & controls

Corporate governance & oversight, independence, transparency, accountability, use of internal ratings, internal & external audit, use of external vendor models

Quant. - generally accepted techniques

Data quality, accuracy of PDs, LGDs & EADs, model logic & conceptual soundness, estimation & validation techniques, back-testing, benchmarking

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Corporate Governance & Oversight

Board & senior management involvement Understanding of Basel /SBP requirements Understanding & approval of key aspects of IRB system Ensures adequate resources and clearly defines responsibilities Ensures adequate training Integrates IRB systems with policies, procedures, systems,

controls Tracks differences between policies & actual practice (e.g.

exceptions/overrides) Quarterly MIS on rating system performance & regular internal

review Receives regular reports on internal ratings

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Independent Rating Approval Process

General rule that approval of ratings & transactions should be separate from sales & marketing

Independent & separate functional reporting lines for rating “assignors” & rating “approvers” (e.g. credit officers, with well-defined performance measures)

Where ratings are assigned & approved within sales & marketing

mitigate the inherent conflict of interest with compensating controls (e.g. limited credit limits, independent post-approval review of ratings, more frequent internal audit coverage)

Where rating assignment or approval process is automated, verify accuracy & completeness of data inputs

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Annual Review Reviews conducted internally or by external experts Functional independence Should encompass all aspects of the process generating

the risk estimates & usage Compliance with established policies & procedures Quantification process & accuracy of risk component estimates Model development, use & validation Adequacy of data systems & controls Adequacy of staff skills & experience

Identify weakness, make recommendations & take corrective actions

Significant findings reported to senior management & the Board

Independent Review of IRB System & Risk Quantification

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Transparency & Accountability

Transparency Enable third parties to understand the design, operations & accuracy of

a rating system & to evaluate whether it is performing as intended An ongoing requirement: update documentation when there

are changes Achieved through documentation

Expert judgement-based vs. Model-based rating system

Accountability Identify individuals or parties responsible for rating accuracy & rating

system performance Inventory of models & accountability chart of roles of parties

Establish performance standards Senior individual to take responsibility for overall performance

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The IRS & risk estimates should have substantial influence on decision-making & actions:

Credit approval & pricing,, individual & portfolio limit setting Portfolio monitoring & determining provisioning Analysis & reporting of credit risk information Modelling & management of economic capital Assessment of total credit risk capital requirements Formulating business strategies & assessment of risk appetite Assessment of profitability & performance, and determining

performance-related remuneration Other aspects (e.g. Banks’ infrastructure such as IT, skills & resources

and organisational structure)

Use of Internal Ratings

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Data Quality Accuracy, completeness & appropriateness

Data architecture

Storage, retrieval

& deletion

Data processing

Data collection

IT infrastructure

Reconciliation

IRB data

A/C data

External & pooled

dataUse of statistical

techniques

Staff competency

Management oversight & control

Data quality

assessment p

rogramme

&

internal audi

t

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Quantitative Requirements

Accuracy of PD, LGD, EADDiscriminatory power and calibration BenchmarkingStress testing

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Validation of a Rating System:Back-testing

Back-testing is the direct comparison between the risk component estimates with the realised figures, e.g. PD against default rate of a borrower grade (or pool for retail)

In practice, estimates will never be exactly the same as realised figures. The question is whether the deviation is acceptable, especially when the estimates are smaller than the realised figures (i.e. underestimation)

In general, statistical hypothesis testing can be applied:Null hypothesis (H0):The estimate of the risk component is correctAlternative hypothesis (H1): The risk component is underestimated

To use the hypothesis testing technique, a confidence level needs to be set and a probability distribution of the risk component needs to be defined.

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Validation of a Rating System:Benchmarking

Benchmarking is the comparison of a Bank’s risk component estimates with those of a third party such as estimates by rating agencies

For PD, external benchmarks are generally most useful where backtesting is difficult

For LGD and EAD, as well as PD of small-sized borrowers (e.g. individuals and SMEs), external benchmarks may not be available

LGD and EAD depend heavily on individual Banks’ recovery and credit monitoring policies, and therefore it is possible for there to be big differences of internal estimates from the benchmarks, even for the same type of facilities

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Validation of a Rating System:Stability Analysis

Even if a rating system performs well under certain situations or for certain types of borrowers/facilities, it may not do so in other situations or with other types of borrowers/facilities

Stability analysis examines whether a rating system and/or the risk component estimates remain valid under different situations or for different types of borrowers/facilities. It involves asking questions like: Would the back-testing results remain satisfactory during economic boom as well as

recession? How would distribution of borrowers/facilities amongst rating grades and estimates of

risk components change if certain assumptions are modified (e.g. discount rates in workout LGD)?

What would be the risk component estimates if only a sub-sample of data are used in quantification?

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Validation of a Rating System:Discriminatory Power

Discriminatory power is about the “rank order” of borrowers. It assesses the ability of a rating system to differentiate “bad” borrowers (i.e. those going to default) from “good” borrowers (i.e. those not going to default).

Many quantitative techniques can be used to assess discriminatory power: Accuracy Ratio Receiver Operating Characteristic Measure Pietra Index Bayesian Error Rate Conditional Information Entropy Ratio Information Value Brier Score Divergence

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Generally speaking, all these techniques are to measure the difference between the distribution of the “good” borrowers and that of the “bad” borrowers in relation to risk characteristics, e.g. credit scores, rating grades, income


Frequency

Rating score

“Bad” borrowers “Good” borrowers

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For a perfect rating system, the distribution of “bad” borrowers would not overlap with that of “good” borrowers

Discriminatory power analysis can be applied to borrower ratings of corporate, bank and sovereign exposures

For retail exposures, discriminatory power can be assessed for individual rating criteria that are used in segmentation

As with back-testing, it is difficult to set a “passing mark” for a rating system’s discriminatory power

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‘CREDIT CAPITAL’

The portfolio approach to credit risk management integrates the key credit risk components of assets on a portfolio basis, thus facilitating better understanding of the portfolio credit risk.

The insight gained from this can be extremely beneficial both for proactive credit portfolio management and credit-related decision making.

1. It is based on a rating (internal rating of banks/ external ratings) based methodology. 2. Being based on a loss distribution (CVaR) approach, it easily forms a part of the Integrated risk management framework.

5. Measure, Monitor & Manage Portfolio Credit Risk

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PORTFOLIO CREDIT VaR

Expected (EL)

Priced into the product (risk-based pricing)

Unexpected (UL)

Covered by capital reserves (economic capital)

Pro

bab

ility

Loss (L)

Credit Capital models the loss to the value of the portfolio due to changes in credit quality over a time frame

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ARE CORRELATIONS IMPORTANT

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

99.9

9%

99.6

7%

99.3

5%

99.0

3%

98.7

1%

98.3

9%

98.0

7%

97.7

5%

97.4

3%

97.1

1%

96.7

9%

96.4

7%

96.1

5%

95.8

3%

95.5

1%

95.1

9%

Correlation

Probability of Default

Confidence level

Large impactof

correlations

RELATIVE CONTRIBUTION OF CORRELATIONS AND PROBABILITY OF DEFAULT IN CREDIT VaR

CREDIT VaR

Source: S&P

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3-Year Default Correlations Auto Cons Energ Finan Build Chem Hi tech Insur Leisure R.E. Tele Trans Utility

Auto 4.81 1.84 1.57 0.67 2.68 3.65 3.11 0.67 2.06 2.40 7.04 3.56 2.39

Cons 1.84 2.51 -1.41 0.83 2.36 1.60 1.69 0.52 2.01 6.03 2.49 2.56 1.31

Energ 1.57 -1.41 4.74 -0.50 -0.49 0.94 0.75 0.75 -1.63 0.20 -0.44 -0.28 0.05

Finan 0.67 0.83 -0.50 1.39 1.54 0.52 0.73 -0.03 1.88 6.27 -0.04 1.03 0.67

Build 2.68 2.36 -0.49 1.54 3.81 2.09 2.78 0.41 3.64 7.32 3.85 3.29 1.78

Chem 3.65 1.60 0.94 0.52 2.09 3.50 2.34 0.41 2.12 0.91 5.21 2.61 1.30

High tech 3.11 1.69 0.75 0.73 2.78 2.34 3.01 0.47 2.45 3.83 4.63 2.82 1.67

Insur 0.67 0.52 0.75 -0.03 0.41 0.41 0.47 96.00 0.10 0.46 0.50 1.08 0.22

Leisure 2.06 2.01 -1.63 1.88 3.64 2.12 2.45 0.10 4.07 9.39 3.51 3.40 1.48

Real Est. 2.40 6.03 -0.20 6.27 7.32 0.91 3.83 0.46 9.39 13.15 -1.14 4.78 2.21

Telecom 7.04 2.49 -0.44 -0.04 3.85 5.21 4.63 0.50 3.51 -1.14 16.72 5.63 4.33

Trans 3.56 2.56 -0.28 1.03 3.29 2.61 2.82 1.08 3.40 4.78 5.63 3.85 1.99

Utility 2.39 1.31 0.05 0.67 1.78 1.30 1.67 0.22 1.48 2.21 4.33 1.99 2.07

Corr(X,Y)=ρxy=Cov(X,Y)/std(X)std(Y)

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Overall Architecture

Average variability explained by each industry

Industry Correlation

Step 1

Tenor of Evaluation, Current Rating

Correlations

Transition rates

Step 2Return Thresholds

Simulated Credit Scenarios

Step 3

Monte Carlo simulation

Migration

Portfolio Loss Distribution Spot & Forward Curve for each grade

Recovery Rates

Valuation

Step 4

ExposureDefault

RMD’s approach ‘CREDIT CAPITAL’

STEP 1From the historical correlation data of industries, the firm-to-firm correlations are found.

STEP 2Calculate asset value thresholds for entire transition matrix. This is done assuming that given current rating, the

asset values have to move up/down by certain amounts (which can be read off a Standard Normal distribution) for it to be upgraded /downgraded.

Step 3 Large no. of Simulations (Monte Carlo) of the asset value thresholds preserving the correlation structure using

Cholesky Decomposition is carried out. Asset value thresholds are converted to simulated ratings for the portfolio for each of the simulation runs.

STEP 4Using the forward yield curve (rating wise) and recovery data suitable valuation of each of the instruments in the

portfolio is done for each simulation run. The distribution of portfolio values is subtracted from the original value to generate the loss distribution.

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Credit Risk - Raroc

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7. Adopt RAROC as a common language

What is RAROC ?Revenues-Expenses-Expected Losses+ Return on economic capital+ transfer values / prices

Capital required for•Credit Risk•Market Risk•Operational Risk

Risk Adjusted Return

Risk Adjusted Capital or Economic

Capital

RAROC

The concept of RAROC (Risk adjusted Return on Capital) is at the heart of Integrated Risk Management.

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Will the loan

default?What will bethe exposureat default ?

How much willbe recovered ?

no

yes

Risk ofDefault

Risk ofDefault

Risk ofExposure

Risk ofExposure

Risk ofRecovery

Risk ofRecovery

The 3 components of Credit Risk

Loss = 0

Average (expected) Loss

•Country risk

•Quality of the USR

•Maturity

•Transfer Risk (per product)

•Commitment level

• Current Exposure

•Unused part of the line

•Product Loan Equivalent (LEF)

•Available pledges on assets

•Recovery on unsecured assets

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Risk Adjusted Return On Capital

RAROC = Revenues - Expected LossEconomic capital

with : EL = EDF . EAD . Severity

• EDF = expected default frequency (depending on the risk class / on the ration)

• EAD = exposure at default = outstanding . LEF . (1 - pledges)

• LGD = Severity = loss given default (depending on the type of counterparty)

RAROC - Definition & Hypotheses

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EL = expected losses, very likely, based on historical data

RAROC calculated per transaction / client / group of clients

Revenues : – Credit– Non Credit

RAREV = Risk Adjusted Revenues = Revenues - EL

Minimum required for a non-destroying value loan : RAREV > 0

-> impact on credit pricing


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Economic capital : own funds needed to cover the unexpected losses of a transaction, as they are assessed by the banking institution.

Economic Capital = (EDF) . . 6,3 . LGD . (1-tax) . EAD

where :

(EDF) = (edf. (1-edf))1/2

= default correlation between assets of the same risk class

6,3 = stress factor for a confidence interval of 99.95%

(1-tax) = accounting for fiscal deductibility of losses


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RAROC = (12 %) x 65 % + (RFR + 0,5%) x 35 % = 14.9% = RFR + 10% (1 - 40%)

• ROE = 12 %

• RFR = 5 %

• Tier I / Tier II = 65% / 35 %

• cost of Tier II : RFR + 0,5%

• taxation rate = 40 %

The transaction revenues need to be sufficient to cover the funding costs, ie., to remunerate the economic capital properly.

RAROC - Hurdle Rate

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Raroc - Leverages

Profitability Credit Margin Non Credit revenues

Risk Risk class Credit type Maturity Country of credit

Recovery rate Pledges

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• Investment loan : 1 MM EUR• Bullet repayment• Credit margin : 2%• Pledges : 400,000 eur• No other recoveries• EDF : 1,5%• Maturity : 1 an

EL = 1.5% . 60% . 1000 000 = 9 000 EUR

Eco K = (EDF) . . 6,3 . Severity . (1-tax) . EAD

= (1,5% . 98,5%)1/2 . 2,7% . 6,32 . 60% . 60%. 1MM

= 74 670 EUR

RAROC = 20 000 - 9 000 = RFR + 14.7%

74 670

Raroc - Numerical Example

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• Quantification of the funding cost of the bank per transaction, per product and per client type.

• Management tool of capital, a scarce and an expensive ressource.

• Management by objectives of the banking network’s agents

Uses of Raroc

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• Alignement of regulatory and economic capital

• Validation of internal models -> détermination of risk classes and of corresponding EDF’s.

Basle II RAROC

• Measurement and management of economic capital

• Key role of the EDF’s in Raroc:Raroc = (Revenues - EL) / K EL = EDF . EAD . SeverityK= (EDF)..6,3. sev.(1-tax).EAD

Raroc in Basle II

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• Direct link between the risk class of a debtor and his capital requirement.

• Fine-tuning of the capital requirement based on the bank’s activities and on its risk profile (pillar 2).

Basle II RAROC

• Raroc capital seen as both regulatory and economic.

• Raroc as a global management and optimisation tool for the bank’s activities.

Raroc in Basle II

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RAROC 22%

EVA 310

Risk-adjustedNet income

1750

Capital Charge 1440

Risk-adjustedAfter tax income

1.75%

AverageLending assets

100 000

Total capital8000

Cost of capital18%

Risk-adjustedNet income

2.20%

Net Tax0.45%

Total capital8.0 %

AverageLending assets

100 000

Risk-adjustedincome5.60 %

Costs 3.40

%

Credit Risk Capital

4.40 %

Market Risk Capital

1.60 %

Operational Risk Capital 2.00 %

Income6.10 %

ExpectedLoss 0.50 %

RAROC Profitability Tree – an illustration

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More than 10 years old, but still a flexible and efficient management tool in a modern regulatory environment.

Based on numerous parameters, it is adaptable to new banking products and activities.

Best suited for : the assessment of the credit risk capital of a bank; internal credit risk management; external credit pricing tool .

Raroc - Summary

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8. Explore quantitative models for default prediction

Corporate predictor Model is a quantitative model to predict default risk dynamically

Model is constructed by using the hybrid approach of combining Factor model & Structural model (market based measure)

The inputs used include: Financial ratios, default statistics, Capital Structure & Equity Prices.

The present coverage include listed & ECAIs rated companies

The product development work related to private firm model & portfolio management model is in process

The model is validated internally

.

Derivation of Asset value & volatility Calculated from Equity Value , volatility for each

company-year Solving for firm Asset Value & Asset Volatility

simultaneously from 2 eqns. relating it to equity value and volatility

Calculate Distance to Default Calculate default point (Debt liabilities for given

horizon value) Simulate the asset value and Volatility at horizon

Calculate Default probability (EDF) Relating distance to default to actual default

experience

Use QRM & Transition Matrix Calculate Default probability based on Financials Arrive at a combined measure of Default using both

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9. Use Hedging techniques

InterestRateRisk

SpreadRisk

DefaultRisk

CreditDefaultSwap

CreditSpreadSwap

TotalReturnSwap

BasketCreditSwap

Securi

Securitization

tization

CreditPortfol

ioRisks

Different Hedging Techniques

. . . as we go along, the extensive use of credit derivatives would become imminent

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Credit Risk: Loan Portfolio and Concentration Risk The Portfolio and Individual Securities are prone

to two Type of Risks.

1. Systematic Risk 2. Unsystematic Risk

The Unsystematic Risk can be eliminated with Diversification.

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Models of Loan Concentration Risk

1. Migration Analysis. Migration analysis uses a loan migration matrix (transition

matrix), which provide probabilities that the credit quality of a loan will migrate from one quality class to another quality class over a period of time, usually one year.

2. Concentration Limits. The concentration limit is the maximum permitted loan

amount to that can be granted to an individual borrower in a given sector, expressed as percentage of capital:

3. Subjective Model. e.g. We have already lent too much to this borrower.

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Concentration Limits

Concentration Limit = Maximum loss as a percentage of capital X 1/Loss Rate

e.g. A bank wants to limit its losses in a particular sector to 5% of its capital and loss rate for this sector is 60%.

Concentration Limit = 0.05 X (1/0.6) = 8.33%

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INTERNAL EXPOSURE LIMIT PER PARTY

Risk Rating of the Industry

Risk

Rated “1”

Risk

Rated “2”

Risk

Rated “3”

Risk

Rated “4”

Risk

Rated “5”

Risk

Rated “1”

30% of tier-1 1:1

25% of tier-1 1:2

20% of tier-1 1:3

15% of tier-1 1:4

10% of tier-1 1:5

Risk

Rated “2”

25% of tier-1 2:1

20% of tier-1 2:2

15% of tier-1 1:2

10% of tier-1 2:3

5% of tier-1 2:5

Risk

Rated “3”

22% of tier-1 3:1

15% of tier-1 3:2

10% of tier-1 3:3

5% of tier-1 3:4

2.5% of tier-1 3:4

Risk

Rated “4”

15% of tier-1 4:1

10% of tier-1 4:2

5% of tier-1 4:3

2.5% of tier-1 4:4

2% of tier-1 4:5

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INTERNAL EXPOSURE LIMIT PER GROUP

Risk Rating Industry

Risk Rating “1”

Risk Rating “2”

Risk Rating “3”

Risk Rating “4”

Risk Rating “5”

Risk Rating (Group)Risk Rated “1” 50% of Tier -1

Capital

1:1

45% of Tier -1 Capital

1:2


1:3


1:4


1:5

Risk Rated “2” 45% of Tier -1 Capital

2:1


2:2


2:3


2:4


2:5


3:1


3:2


3:3


3:4

2.5% of Tier -1 Capital

3:5


4:1


4:2


4:3

2.5% of Tier -1 Capital

4:4


4:5

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Migration Analysis

Loan Migration Matrix

Risk Grade at Beginning of Year

Risk Grade at End of Year

1 2 3 D

1 0.85 0.10 0.04 0.01

2 0.12 0.83 0.03 0.02

3 0.03 0.13 0.80 0.04

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Sample Credit Rating Transition Sample Credit Rating Transition MatrixMatrix

( ( Probability of migrating to another rating Probability of migrating to another rating within one year as a percentage)within one year as a percentage)

Credit Rating One year in the futureCredit Rating One year in the futureCCUURRRREENNTT

CREDICREDITT

RRAATTIINNGG

AAAAAA AAAA AA BBBBBB BBBB BB CCCCCC DefaDefaultult

AAAAAA 87.787.744

10.910.933

0.450.45 0.630.63 0.120.12 0.100.10 0.020.02 0.020.02

AAAA 0.840.84 88.288.233

7.477.47 2.162.16 1.111.11 0.130.13 0.050.05 0.020.02

AA 0.270.27 1.591.59 89.089.055

7.407.40 1.481.48 0.130.13 0.060.06 0.030.03

BBBBBB 1.841.84 1.891.89 5.005.00 84.284.211

6.516.51 0.320.32 0.160.16 0.070.07

BBBB 0.080.08 2.912.91 3.293.29 5.535.53 74.674.688

8.058.05 4.144.14 1.321.32

BB 0.210.21 0.360.36 9.259.25 8.298.29 2.312.31 63.863.899

10.110.133

5.585.58

CCCCCC 0.060.06 0.250.25 1.851.85 2.062.06 12.312.344

24.824.866

39.939.977

18.618.600

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10. Create Credit culture

“Credit culture” refers to an implicit understanding among

bank personnel that certain standards of underwriting and loan

management must be maintained.

“Credit culture” refers to an implicit understanding among

bank personnel that certain standards of underwriting and loan

management must be maintained.

Strong incentives for the individual most responsible for

negotiating with the borrower to assess risk properly

Strong incentives for the individual most responsible for

negotiating with the borrower to assess risk properly

Sophisticated modelling and analysis introduce pressure for

architecuture involving finer distinctions of risk

Sophisticated modelling and analysis introduce pressure for

architecuture involving finer distinctions of risk

Strong review process aim to identify and discipline among

relationship managers

Strong review process aim to identify and discipline among

relationship managers

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Effective Management of Risk benefits the bank..

Efficient allocation of capital to exploit different risk / reward pattern across business

Better Product Pricing Early warning signals on potential events impacting business Reduced earnings Volatility Increased Shareholder Value

No Gain!No Risk …

To Summarise….

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Thanks for your attention . . .Thanks for your attention . . .

Financial Risk Management Framwork & Basel Ii Icmap

Economy & Finance

Transcript of Financial Risk Management Framwork & Basel Ii Icmap