Building an Internal Rating System : Conceptual Framework

1. Building an Internal Rating System : Conceptual Framework Michael Peng

2. Agenda Key attributes of an Internal Rating System Expected Loss Framework Rating and PDs Exposure and Facility tracking Loss Given Default Case Study – Rating Management System Concluding Comments

3. What is an Internal Rating System ? 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.

4. 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) CORPORATE/ BANK/ SOVEREIGN EXPOSURES RETAIL EXPOSURES • 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 • Each retail exposure must be assigned to a particular pool • The pools should provide for meaningful differentiation of risk, grouping of sufficiently homogenous exposures and allow for accurate and consistent estimation of loss characteristics at pool level How is IR related to Basel II?

5. 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.

6. 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.

7. Foundation IRB Vs Advanced IRB Approach

8. Migration Matrix Probability of Default (PD) Portfolio Monitoring Provisioning Pricing Profit Management Capital Allocation An Overview of credit risk measurement under BIS II Framework Internal Rating System Qualitative Evaluation Internal Rating Quantitative Evaluation Reporting to the Board Financial Data Stress Testing Loss Given Default (LGD) Risk Components Calculation of Credit Risk Amount Expected Loss (EL) Unexpected Loss (UL) Exposure at Default (EAD) Correlation Quantification of Credit Risk Internal Use Source: BoJ Sep 2005

9. A Simple Look on Pillar 1 IRB Tasks Estimation of Risk Components Architecture of an Internal Rating System, Internal Use Risk estimates (i.e., PD, LGD, EAD) predictive and accurate? “Use Test”*: Pricing, Portfolio Monitoring, Credit Risk Quantification? Quantitative Rating Model Qualitative Evaluation Validation Work * 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. Source: BoJ Sep 2005

10. Overview of a Rating Management System Audit Trail Ratings summary Facility/ Exposure details Collateral and LGD details Quantitative inputs Qualitative inputs

11. Internal ratings System (RMS): User Interface Bank’s own internal view Rating Templates Qualitative assessment Quantitative Assessment External Ratings External Models Peer comparison

12. 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

13. 2. Expected Loss Framework • Each prospective or existing loan facility must undergo three consecutive stages to determine expected loss. Stage 1 Stage 3 Stage 2 Exposure at Default Expected Loss Rating (PD) x x Loss Given Default = Corporates Banks Insurance Project Finance SME Data Collateral Haircut Policy Seniority Maturity etc

14. 3. Ratings and Pds Across different asset classes Low volume of data + High Exposure RATING TEMPLATES ARE SUITABLE Typical Loan Book 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 High volume of data + Low Exposure MODELS ARE SUITABLE

15. 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.

16. European Bank Credit factors Weights Evaluation of Qualitative Factors Large corporates and specialised lendingSample template – Insurance Companies

17. Large corporates and specialised lendingSample template – Insurance Companies Clear and consistent rating criteria

18. European Bank Evaluation of Quantitative Factors Large corporates and specialised lendingSample template – Insurance Companies

19. Large corporates and specialised lendingSample template – Insurance Companies Quantitative Assessment Based on S&P’s Experience Benchmarks are provided per sector and market

20. Large corporates and specialised lendingSample template – Insurance Companies Backtesting and Mapping to External Indicators of PD Backtest model results versus S&P ratings or estimates Compare results and map the scales Internal Rating Scale S&P 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

21. 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.

22. PIT Rating vs TTC Rating

23. 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

24. 5. LGD and Definition of default • The definition of default is not the same in all countries, often bank behaviour is linked to national legal specificities US BASEL II UK FRANCE GERMANY ITALY Bankruptcy 90 days credit obligation default Debt restructuring Credit obligation default

25. Retail Average Oil & Gas Healthcare Television Real Estate Automotive Comp. & Elec Metals & Mining Transportation Printing & Pub. Food & Beverage Gaming & Hotel Textile & Apparel Services & Leasing Building Materials Retail Food & Drug Manu. & Machinery 5. LGD – Loss Given Default - LGD Behaviour in the US • Average Overall Recovery By Industry, some differences Industries with 9+ Observations 70 60 50 Recovery (%) 40 30 20 10 0

26. LGD Behaviour LGD Behaviour by debt Structure and Industry Overall - No Clear pattern!! • Need More data • Clear definitions • Need to pool data

27. Loss Given Default Loss Given Default: LGD information is scarce and complicated

28. Expected Loss

29. Concluding Comments To build an internal rating system for Basel II you need: • Consistent rating methodology across asset classes • Use an expected loss framework • Data to calibrate Pd and LGD inputs • Logical and transparent workflow desk-top application • Appropriate back-testing and validation. Standard & Poor’s Risk Solutions

30. BIS II – IRB Advanced From Pillar 1 to Pillar 2 From Expected Loss to Economic Capital Business Processes • Risk Appetite • Capital Allocation • Active Portfolio Mgmt. • Mitigation Strategies • Risk Averse Pricing • RAPM & VaR limits • EcoCap Optimisation Correlations Portfolio Approach • Regulatory Capital Requirement • Risk-Adjusted Pricing • Provisioning Policies • Limits Based on EL • Early Warnings Internal Rating Approach • Regulatory Capital Requirement • Risk-Adjusted Pricing • Provisioning Policies • Limits Based on EL • Early Warnings Diversification BIS II – IRB Foundation BIS II – Standard Approach • Regulatory Capital Requirement Inputs • External PD • Supervisory LGD • Supervisory EAD • Internal Estimate PD • Supervisory LGD • Supervisory EAD • Internal Estimate PD • Internal Estimate LGD • Internal estimate EAD • IRB Parameters • Macroeconomic Forecasts

31. 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 * LGD If 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.

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.

33. Note 3:EL Vs UL