Building an Internal Building an Internal Rating System : Rating System :

Conceptual Conceptual FrameworkFramework

Building an Internal Building an Internal Rating System : Rating System :

Conceptual Conceptual FrameworkFramework

Michael PengMichael Peng

04/19/23 2

Agenda

1. Key attributes of an Internal Rating System

2. Expected Loss Framework

3. Rating and PDs

4. Exposure and Facility tracking

5. Loss Given Default

6. Case Study – Rating Management System

7. Concluding Comments

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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.

Internal rating system is the prerequisite for advanced credit risk management, and each financial institution is expected to develop its own internal rating system. Every institution faces a different business environment, so each system should have its own design. For example, a more simple framework might be suitable for small institutions . There is no single answer for the framework of internal rating systems, such as the number of rating grades, a definition of each rating grade, and the method of rating assignments. Financial institutions need to introduce their own system depending on the characteristics of their loan portfolios, their operations, the objectives of the rating system, and other factors. Obviously, the institutions need to make necessary adjustments flexibly due to changes in the business environment.

What is an Internal Rating System ?

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The New Basle Capital Accord – Consultative Document, April 2003

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

•Two dimensional rating system•Risk of borrower default

•Each borrower must be assigned a rating•Transaction specific factors (For banks using advanced approach, facility rating must exclusively reflect LGD)

•Minimum of seven borrower grades for non-defaulted borrowers and one 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

How is IR related to Basel II?

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Why Building Internal Rating System (1)?

When banks build their internal rating system, their objective is twofold.

• First they want to assess the creditworthiness of companies during the loan application process.

• Second they want to use rating information to feed their portfolio management tools designed to produce regulatory capital or economic capital measures.

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The Use of Internal Rating System

• Setting upper credit limits based on rating grades: For example, institutions can extend a smaller amount of loans to low-graded borrowers and thereby avoid the risk of credit concentration in them.

• Setting authority ranks for loan approval by rating grade: For example, loan officers at bank branches can make loan decisions for only a limited amount of loans to low-graded borrowers.

• Simplifying the loan review process for higher-graded borrowers: Risk-based allocation of risk management resources can improve efficiency of the overall loan review process.

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Foundation IRB Vs Advanced IRB Approach

Foundation IRB Approach

Advanced IRB Approach

Values for Loss given default (LGD) and exposure at default (EAD) are provided by the regulatory authority.

Values for Loss given default (LGD) and exposure at default (EAD) are determined by each bank through internal modeling with a data of 5-7 years.

Assessment of values of credit mitigants is done by the regulatory authority.

Banks may assess the value of its credit mitigants.

For retail exposure, there is no foundation IRB (only advanced IRB where besides PD, the bank concerned will have to estimate LGD & EAD.)

Advanced IRB is applicable to retail exposure also.

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An Overview of credit risk measurement under BIS II Framework

Quantitative Evaluation

Qualitative Evaluation

Internal Rating

Loss Given Default(LGD)

Exposure at Default(EAD)

Correlation

Stress Testing

Cal

cula

tion

of C

redi

t R

isk

Am

ount

Exp

ecte

d Lo

ss (

EL)

Une

xpec

ted

Loss

(U

L)

Ris

k C

ompo

nent

s

Financial Data

Portfolio Monitoring

Provisioning

Pricing

Profit Management

Capital Allocation

Reporting to the Board

Migration Matrix

Probability of Default (PD)

Quantification of Credit Risk

Internal Rating System

Internal UseSource: BoJ Sep 2005

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A Simple Look on Pillar 1 IRB Tasks

Internal Use

“Use Test”*: Pricing,

Portfolio Monitoring,

Credit Risk Quantification?

Validation Work

Architecture of an Internal Rating System,

Quantitative Rating Model

Qualitative Evaluation

Estimation of Risk Components

Risk estimates (i.e., PD, LGD, EAD) predictive and accurate?

Source: BoJ Sep 2005

* Use Test: IRB provision that requires ratings and default and loss estimates to “play an essential role” in the Institution’s credit approval, risk management, internal capital allocations and corporate governance functions.

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Facility/ Exposure details

Ratings summary

Collateral and LGD details

Qualitative inputs

Audit Trail

Overview of a

Rating Management System

Quantitative inputs

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Internal ratings System (RMS): User Interface

Qualitative assessment

Quantitative Assessment

Rating Templates

External Ratings

External Models

Peer comparison

Bank’s own internal view

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1. Key Attributes of an Effective

Internal Rating System

• Consistent analytical approach to ratings and PDs – all asset classes

• Transparency of methodology;

• Visible audit trail;

• Logical workflow, including sign-off and permissions;

• Open architecture with a modular approach that is easily adaptable

and scalable;

• Data access aligned with roles and responsibilities; and

• Centralised information storage

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2. Expected Loss Framework

Each prospective or existing loan facility must undergo three consecutive stages to determine expected loss.

Stage 1 Stage 3Stage 2

x x = Expected Expected LossLoss

Rating (PD)

CorporatesBanksInsuranceProject FinanceSME

Exposure Exposure at Defaultat Default

SeniorityMaturity etc

DataCollateralHaircut Policy

Loss Given Default

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3. Ratings and Pds

Across different asset classes

The methodologies used for assessment of creditworthiness of different asset

classes should balance:

• the volume and scope of data available, with

• the relative exposure of the bank

Retail

SMEs

Large Corporates

Banks Insurance

Specialised Finance

Public Sector

High volume of data + Low Exposure

MODELS ARE SUITABLE

Low volume of data + High Exposure

RATING TEMPLATES ARE SUITABLE

Typical Loan BookTypical Loan Book

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Large corporates and

specialised lending

Characteristics of these sectors

• Relatively large exposures to individual obligors

• Qualitative factors can account for more than 50% of the risk of obligors

• Scarce number of defaulting companies

• Limited historical track record from many banks in some sectors

Statistical models are NOT applicable in these sectors:

• Models can severely underestimate the credit risk profile of obligors given the low

proportion of historical defaults in the sectors.

• Statistical models fail to include and ponder qualitative factors.

• Models’ results can be highly volatile and with low predictive power.

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European Bank

Evaluation of

Qualitative Factors

Credit factors

Weights

Large corporates and specialised lending Sample template – Insurance Companies

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Clear and consistent

rating criteria

Large corporates and specialised lending Sample template – Insurance Companies

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Evaluation of Quantitative Factors

European Bank

Large corporates and specialised lending Sample template – Insurance Companies

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Quantitative Assessment Based on S&P’s Experience

Benchmarks are provided per sector and market

All Combined 1 2 3 4 5

TAC/Total Assets >45% 20%-39% 5%-20% 2%-4% <2%

Pre-Tax Rtn on Assts >8% 2%-7% (0.2)%-2% (2.1)%-(0.2)% <(2.1)%

Gross Ex/GWP <5% 5.1%-17% 17.1%-39.0%

39.0%-45.1% >45.1%

Growth in gross premium (%)

>20% 10%-20% 1%-10% (5)%-1% <(5)%

Gross Premium Income (USD Millions)

>900 500-900 30-500 30-10 <10

Net Inv Yield >10.1% 5%-10.1% 2%-5% 0.5%-2% <0.5%

Inv Assets - (Bonds+Cash)/TAC

<2% 2.1%-5% 5%-8% 8%-12% >12%

Cash In/Cash Out >200% 99%-200% 20%-99% 10%-20% <10%

Short Term Assets + Bonds / Total Assets

>90% 75%-90% 50%-75% 30%-50% <30%

Large corporates and specialised lending Sample template – Insurance Companies

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1

2

3

4

5

6

S&P 1-yr PD

AAA 0

AA 0.02

A 0.02

BBB 0.19

BB 0.88

B 5.44

CCC 23.76

1 2 3 4 5 6

AAA 1

AA 3 2 1

A 5 1

BBB 5 1

BB 1 6 1

B 2 1 4 2

CCC 1 4

S&

P S

cale

Internal Rating Scale

• Use of external default data• Prepare for CBO/CLO

Satisfy board regarding the validity of an

internal rating system

Identify areas of inconsistency in

order to improve an

internal ratings process

Backtest model results versus S&P ratings or estimates Compare results and map the scales

Backtesting and Mapping to External Indicators of PD

Large corporates and specialised lending Sample template – Insurance Companies

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Rating Assignment Horizon—Relationship with Business Cycle: point-in-time vs. through-the-cycle

system

The time horizon of assessing the creditworthiness of borrowers in assigning ratings is also important. Two different approaches may be taken in considering the effect of the business cycle in assigning ratings. One is a point-in-time point-in-time system (PIT rating). In PIT rating, risks are evaluated based on the current condition of a firm regardless of the phase of the business cycle at the time of evaluation. The other is a through-the-cycle system (TTC rating). In TTC rating, risks are taken into account on the assumption that a firm is experiencing the bottom of the business cycle and is under

stress.

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PIT Rating vs TTC Rating

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4. Exposure and Facility Analysis

Exposure and Facility Analysis - Typically a corporate obligor will have a number of facilities with a bank, including secured and unsecured loans and overdraft facilities

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5. LGD and Definition of default

US

BASEL II

UK

FRANCE

GERMANY

ITALY

Credit obligation default

90 days credit obligation

default

Debt restructuring

Bankruptcy

The definition of default is not the same in all countries, often bank behaviour is linked to national legal specificities

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5. LGD – Loss Given Default -

LGD Behaviour in the US

Average Overall Recovery By Industry, some differencesIndustries with 9+ Observations

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LGD BehaviourLGD Behaviour by debt Structure and Industry

Overall - No Clear pattern!!Overall - No Clear pattern!!

Need More data

Clear definitions

Need to pool data

04/19/23 27

Loss Given Default

Loss Given Default: LGD information is scarce and complicated

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Expected Loss

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Concluding Comments

To build an internal rating system for Basel II you need:

1. Consistent rating methodology across asset classes

2. Use an expected loss framework

3. Data to calibrate Pd and LGD inputs

4. Logical and transparent workflow desk-top application

5. Appropriate back-testing and validation.

Standard & Poor’s Risk Solutions

04/19/23 30

Inputs

Business Processes

BIS II – Standard Approach

Internal Rating Approach

BIS II – IRB Foundation

BIS II – IRB Advanced

Portfolio Approach

Risk AppetiteCapital AllocationActive Portfolio Mgmt.Mitigation StrategiesRisk Averse PricingRAPM & VaR limitsEcoCap Optimisation

IRB Parameters Macroeconomic Forecasts

Internal Estimate PD Internal Estimate LGD Internal estimate EAD

Internal Estimate PD Supervisory LGD Supervisory EAD

External PD Supervisory LGD Supervisory EAD

Regulatory Capital Requirement

Regulatory Capital Requirement

Risk-Adjusted PricingProvisioning PoliciesLimits Based on ELEarly Warnings

Correlations

Diver

sifica

tio

n

Regulatory Capital Requirement

Risk-Adjusted PricingProvisioning PoliciesLimits Based on ELEarly Warnings

From Expected Loss to Economic Capital

From Pillar 1 to Pillar 2

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Note1: Expected Loss (EL)

• Expected Loss is the bank’s cost of doing business. Expected loss has to be provided

for. • The Expected Loss (in currency amounts)

EL = PD * EAD * LGDIf expressed as a percentage figure of the EAD

EL = PD * LGD.• The bank should also proactively incorporate an expected loss rate in the estimation

of the total spread to be charged on the loan. • Expected loss is not a measure of risk as it is anticipated.

04/19/23 32

Note 2: Unexpected Loss (UL)

• Regardless of how prudent a bank is in managing its day-to-day business activities, there are market conditions that can cause uncertainty in the amount of loss in portfolio value.

• This uncertainty, or more appropriately the volatility of loss, is the unexpected loss. Unexpected losses are triggered by the occurrence of higher default rates as a result of unexpected credit migrations.

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Expected V/s Unexpected Losses

1.21%0.44%

1.41%1.96%

4.58%

7.53%

3.52%

0.27%

3.32%3.93%

2.30%2.21%

0.56%0.42%0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

8.00%

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Time (Year)

Lo

an lo

sses

Unexpected loss

Expected loss

Note 3:EL Vs UL