Estimating Economic Capital for Credit Risk in Asia Pacific Conference

Estimating Economic Capital for Credit Risk BIS Asia Pacific Conference March 11, 2008

Agenda • Current State of the Art in Asia Pacific • Credit Economic Capital Components • Rating Agency Perspective • Six Most Commonly Asked Questions • Challenges and Issues

Different Types of Capital Tier 1capital is core capital, this includes equity capital and disclosed reserves. Equity capital includes instruments that can't be redeemed at the option of the holder. Tier 2 capital is secondary bank capital that includes items such as undisclosed reserves, general loss reserves, subordinated term debt, and more. Risk-based / economic capital measures how much you need, not how much you have • To ensure that the business can continue irrespective of unexpected events leading to losses • To reassure investors, depositors and regulators

2007 Algorithmics’ Survey Focused interviews • Heads, Risk Analytics • Heads, Group Portfolio Risk • In-Charge Economic Capital • In-charge, Basel II Project Respondent banks • Non-clients • Designated by their Regulators as “Best Practice” Interviews • Conducted by at least two Algorithmics representatives, where possible • Conducted on client site, where possible Supplementary internal Algorithmics information

Key Findings – North America & Europe Two distinct process in operation • Economic capital management (ECM) • Portfolio credit risk management (PCRM) Typically managed by two distinct groups in larger/more complex institutions • Different focus • Different pre-occupations • Different backgrounds, profiles and skill sets Typically managed by different sub-committees within the same group in smaller/less complex institutions

Key Findings – APAC Capturing all risks across all books is not fully addressed A typical institution is in “regulatory compliance” rather than “risk-aware management” mind-set • Risk management and risk-adjusted performance management are not part of day-to-day operations • Pillar 2 “Use Test” issues – Senior Management suspicions Greater need and emphasis in APAC on: • Stress testing – given little/no data for inputs • Macro-economic scenario building – given higher volatility • Aggregation analytics – given different sub-portfolios/asset classes

Key Messages Historically most top banks have focused more on portfolio management rather than on capital / ERM management: • Simplified approach – Risks easier to analyze are over-analyzed • Siloed approach – Double counting / ignoring risks across silos • Incomplete approach – Need validation • Limited approach – Limited Senior Management use of results The implementation of Pillar 2 and ICAAP is initiating a shift in practice towards Capital Management

Credit Economic Capital Inputs Probabilities of Default (PD) or Rating & Transition Matrix Loss Given Default (LGD) Exposure description (currency, size, dependence and maturity) Obligor’s description (asset class, sector, country, link to other obligors) Risk factors affecting PDs, LGDs, Exposures

General Framework for Credit Economic Capital

Step 1

Step 2

Step 3

Step 4

Step 5

Reconciling Credit Capital Requirements • 1. Risk factors and scenarios (“states of the world”) • Credit; Joint Market/Credit; Single Step; Multi Step; Statistical Scenarios; Stress Scenarios • 2. Joint default/migration model • Default; Migration; Counterparty vs Sector • 3. Obligor exposures, recoveries and losses in a scenario • Notional; MtM; Stochastic; Netting; Collateral • 4. Conditional portfolio loss distribution in a scenario • Sampling; FFT, Central Limit Theorem, Law of Large Numbers • 5. Aggregation of losses in all scenarios • Absolute/Incremental/Marginal Contributions; Many Statistics; Slicing & Dicing

add.. Idiosyncratic Risk add .. Calibrated Loadings add.. Multiple Factors Systemic Default Risk add.. Systemic Migration Risk Reconciling Credit Risk Capital Requirements BIS II Pillar I Full model BIS II Formula Pillar I 16,449.95 24,129.89 Error: -1.0% 0.2%

Rating Agency Perspective On Credit Economic Capital Model

Agenda • Current State of the Art in Asia Pacific • Credit Economic Capital Components • Rating Agency Perspective On Credit Economic Capital Model • Six Most Commonly Asked Questions • Challenges and Issues

What Rating Agencies look for Fitch believes that credit risk models form a very important part of risk management and are a vital input into the pricing of products and services. The understanding of risk on an aggregate basis and an assessment of how these risks associated with single borrowers interact with each other is very difficult to do in the absence of some kind of risk model. Source: How much Credit in Credit Risk Models?, p2, Criteria Report, May 2007, Fitch.

Qualitative issues Board and Managerial Oversight of Credit Risk Models • Board and senior management should understand and endorse the use of credit models • Model should be integrated into the active management of the company • Reports based on the models should be used to assign and track risk tolerance and associated capital levels • Management should receive regular reports • Board should require and be apprised of independent validation of models • Model developers should not be end users; if not possible a third party should validate

Qualitative issues Clearly Articulated Understanding of and Insight into Models • Management should be well versed in models. They should be able to account for contrasts between model outputs vs. accounting and previous regulatory frameworks. • Details concerning model construction, implementation and validation should be readily available • This equates to a high degree of transparency, which is favorable Integration • Models should have been employed over a period of time and have a proven track record • Management teams that have a history of making decisions and managing their business using model output will get more weight from the Agency

Qualitative issues Quality of Model Development Suitability for Task • Is there a strong fit between the capabilities, assumptions and the properties of the portfolio? • Is the modeling approach appropriate for the portfolio? Model Input Quality • Are major model inputs being measured accurately? • Where there are compromises, are there monitoring procedures that provide feedback for future improvement?

Qualitative issues Quality of Model Development Model Specification and Validation • Has the model been specified so that ongoing validation is possible? • Is the sensitivity of final capital numbers to modeling assumptions understood well? The lack of sufficient historical data usually limits the ability to back-test model components satisfactorily. Comprehensiveness • Is there a good understanding of what risks are being considered that have been ignored by the portfolio credit risk analysis? • For example, have concentration risk or value migration risk been considered? Are they important in this analysis?

Qualitative issues Validation • Is there a clearly documented process and methodology for validating the portfolio credit risk tool? • Have the results from the validation procedures identified areas where the model works satisfactorily and where it is not to be used? • Have weaknesses been uncovered that need to be considered when interpreting risk measurement output? • Are procedures in place to continuously improve on such weaknesses? Ongoing Model Review • Are models subject to regular periodic audits, ongoing backtesting and benchmarking? • Are change control procedures in place to ensure that only authorized changes are made to protect the integrity of the model and output?

Quantitative issues Main Drivers of Credit Portfolio Risk Models • Definition of default • PD • LGD • EAD • Maturity • Correlation • Valuation methodology • How is valuation performed – at loan horizon or are loan values present values? • How are coupon frequencies taken into account? • Are losses due to default and value changes due to rating migrations taken into account, or just default losses? • Are cycle sensitivities part of the modeling approach?

Quantitative issues Main Drivers of Credit Portfolio Risk Models • Is the quantitative impact of changes in all of these variables on risk/capital output able to be explained? Example:

Loan portfolio characteristics

Changing PDs

Changing LGDs & correlation

Impact of Pillar 2 Total capital charge Capital planning Final amount will depend on quantitative and qualitative factors Stress and solvency tests Pillar 2 Risk and controls Credit risk Minimum capital charge Individual capital for organisation will be somewhere along here Pillar 1 Market risk Operational risk Source: Fitch

Universal Bank Total capital charge 35,682 Capital planning cushion: 1,000 Interest rate risk: 1,500 Final amount will depend on quantitative and qualitative factors Business risk: 1,100 Pillar 2 Concentration risk: 1,000 Stress tests: 1,000 Other Risks: 500 Credit risk: 24,382 Minimum capital charge Individual capital for organisation will be somewhere along here Pillar 1 Market risk: 3,000 Operational risk: 2,200 Source: Fitch

Mortgage Bank Total capital charge 2,162 Capital planning cushion: 100 Interest rate risk: 100 Final amount will depend on quantitative and qualitative factors Business risk: 75 Pillar 2 Concentration risk: 200 Credit risk stress tests: 150 Pension risk: 100 Credit risk: 937 Minimum capital charge Individual capital for organisation will be somewhere along here Pillar 1 Market risk: 300 Operational risk: 200 Source: Fitch

1. What Risks Should be Included? Credit Risk General Credit Risk Counterparty Credit Risk Default Risk Rollover Risk Migration Risk General Wrong Way Risk Concentration Risk Specific Wrong Way Risk Correlation Risk Country Risk Settlement Risk Definition from “Principles for the Management of Credit Risk”July 1999 and Basel II document, Annex 4, 2A, 2G.

Illustration – Risks Included in Nedbank’s Risk Capital Framework Source: 2006 Risk and Capital Management report

2. Why Choose a One Year Horizon? Bond holders have investment horizons longer than one year Shareholders have annual shareholder meetings Bank managers have yearly performance targets – economic capital is a management tool for: • Capital Adequacy • Concentration Risk • Basel II Compliance • External Communications • RAPM Other possibilities: • Time needed to liquidate positions. Issue: is it possible to stop risk for the remainder of the period when the capital allocated has already been consumed by losses? • Time needed to recapitalize • To maturity of transactions (Project Finance lending) / Planning horizon • Over average length of obligor relationship (e.g. Japan)

3. What is the Right Confidence Interval? 99.9% – The Basel II Standard To reflect your desired rating (e.g., AAA 99.99% – 1 in 10,000 AAA-rated banks has defaulted. There are less than 100 rated AAA banks) To reflect your risk profile – Concentration Risk often appears in extreme conditions To reflect your risk appetite (e.g., board members sit approximately ten years: 90%) In practice banks use different confidence levels for different purposes. For example: • Estimation of Capital at risk (to sustain extreme events): 99.97% • Allocation of capital to businesses taking their one year earnings volatility into account: 99%

3. What is the Right Confidence Interval? In practice banks consider the computation cost of increasing confidence levels (for example, Citibank) and the volatility of their input risk estimates. Estimation of Capital at risk (to sustain extreme events): 99.97% • Allocation of capital to businesses taking their one year earnings volatility into account: 99% • Issue of different risks with different confidence level. Operational risk at 99% leads to ignoring low frequency large losses Convenience of using 99.9% to compare economic and regulatory capital

Evaluating Risk Contribution Across Quantiles • Management trigger points (red, orange, yellow, green) depend on objectives • Some high contributors only appear at high confidence level

4. What is the Correlation Model? Correlation / Diversification risk is of great concern to Regulators: • Are new risks occurring in times of stress? (model, liquidity, operational risks…) • Are correlations between systemic and idiosyncratic risks adequately captured? • Correlations can cause concentration risks BIS Dec 2007 conference on the integration of market and credit risks • Blurring of risk silos: correlations between different risk types As a starting point many banks simply add risks up. This is not necessarily conservative. Refer to Till Schuermann paper. Among sophisticated banks, risks are captured through common risk factors, and risks are aggregated through copulas and scenarios Consensus seems to be to add a capital buffer beyond economic capital to cover other elements (stress-testing, target rating…)

5.How Can Economic Capital Results be Made Usable for Senior Management? Consensus seems to be to develop economic capital frameworks that measure the impact of active management strategies UK FSA made the availability of marginal capital drill-downs down to obligor level if necessary a tell-tale of the usefulness of the economic capital information produced for Senior Management Do risk capital contribution reports “make sense” to Senior Management? When do risk contributions need to add up? • Comparisons for planning and budgeting • Risk reports to Senior Management and outsiders • Regulators are used to additive contributions: Basel II creates additive capital through its construction

Different Applications / Different Measures

6. Can Pillar 2 be Lower than Pillar 1? International Bank Source: Andrew Jennings, Citigroup

6. Can Pillar 2 be Lower than Pillar 1? Domestically-Focused Bank

6. Can Pillar 2 be Lower than Pillar 1? Ratio 1 = Economic Credit Capital / Total Regulatory Credit Capital Ratio 2 = Economic Credit Capital / Tier 1 Regulatory Credit Capital* Ratio 3 = Economic Operational Risk Capital / Total Regulatory Operational Risk Capital Ratio 4 = Economic Operational Risk Capital / Tier 1 Regulatory Operational Risk Capital

Financial Institution Banking Book Trading Book Commercial large Retail Commercial medium/small Derivatives Counterparties Sovereign Bond Issuers Lines of credit Mortgages Credit card Private Firms Corporates (Public and Private) Corporate Bond Issuers Sectors Sectors Sectors Sectors Credit Derivatives Capturing Credit Risks Across All Books Consistently

Banking Book Trading Book Commercial large Retail Commercial medium/small Lines of credit Mortgages Credit card Taking Each Book’s Risk Profile Into Account Financial Institution Risk Horizon Consolidation Level • CP analysis • DND for derivatives • Full Migration for Bonds • Integrated Market & Credit (Stochastic Exposures) • Netting & Collateral • Impact of Credit Derivatives • CP/Sector analysis • DND or Full Migration • MtM Exposures • CP analysis • Full Migration • Integrated Market & Credit (Stochastic Exposures) or MtM • Sector analysis • DND • Notional CLT Sampling Sampling LLN FFT

Specific risk Specific Credit } I Systemic Credit } S Market Factors } M Total Scenarios = MSI Interrelations Between Market and Credit Risks Integrating Market & Credit Loss distributions can be decomposed into i) Systemic risks and ii) Specific risks Losses = f(Exposures, PDs) Exposures = f(market factors) CreditWorthiness(PDs) = f(credit factors, specific factors) Systemic risk This revolves around 3-tier simulation:

Estimating Economic Capital for Credit Risk in Asia Pacific Conference