1. CRITICAL SUCCESS FACTORS IN IMA IMPLEMENTATION PHILIPPE CARREL Mumbai, July 21 st 2010 Risk Intelligence: The 21 st Century Frontier of Market Efficiency

2. THE ROAD TO SYSTEMATIC RISKS Number of crisis over time appears to be rising 370 years of cyclical crises always resulted from decoupling the perception of current risk versus future value

3. REGULATIONS AIM AT DE-RISKING VITAL ACTIVITIES Systematic risks through countercyclical prudential supervisory measures. BCBS 164 on strengthening resilience contains proposals for capital buffers to contain leverage and exposure Idiosyncratic risk stabilised through adjusted through risk adjusted capital reserves

4. IDIOSYNCRATIC RISK MANAGEMENT IS TO BALANCE THE CREATION OF VALUE WITH EXPOSURE TO RISK FACTORS Risk is a measure of sensitivity to factors of exposure under scenarios Managing risk is to align the firm’s exposure to the risk factors with its appetite for it

5. Market Risks (VaR) Credit Risks (CVaR, PFE) Markets Portfolios Economy Growth Country Operations MANAGED IN SILOS, RISK IS NECESSARILY AGGREGATED BY MODELS Banking BooksTrading Books Market Risks (ALM) Credit Risks (EL=PDx [ 1-LGD ] ) Collateral Market Risks (Haircut) Credit Risks (EAD) Operational Risks (PE x LGE) or OpVaR Net RWA Markets Portfolios Economy Growth Country Operations Markets Portfolios Economy Growth Country Operations ),()(),,(jiELVaRjiUL  Aggregated Loss Distribution EL

6. A FOCUS ON LOW IMPACT HIGH FREQUENCY EVENTS REDUCES CAPITAL CHARGE… Probability of Loss Event Expected Losses VaRCatastrophic Scenario Loss Impact But increases exposure to tail risks… Repetitive tail events Stressed VaR Outside the scope of B II Scope of Basle II Expected losses Outside the scope of Basle II..and to system externalities. Interval of confidence

7. CREATE A CULTURE OF RISK MANAGEMENT – KEEP IT ALIVE Risk Intelligence No financial instrument is inherently risky Valuation and aggregation methodology (covariance) depend on the nature of tail events Crashes follow booms, but the future is not like the past Restore the balance Capital Efficiency / Risk to align Corporate Governance and Risk Appetite Support Regulatory Compliance with information on market behaviour in addition to statistical analysis

8. Banking BooksTrading Books Markets Portfolios Economy Growth Country Operations Markets Portfolios Economy Growth Country Operations Markets Portfolios Economy Growth Country Operations ValuationsCounterparties RECONNECT SENSES TO CREATE A DNA BACKBONE Risk Factors

9. RECONNECT THE BRAINS WITH THE NERVOUS SYSTEM Portfolio view of firmwide risks, limits and triggers Business Line Risk Mgr Product Risk Mgr Regional Risk Mgr Net Exposure Sensitivity Max Loss Portfolio Limits Sensitivity Limits Concentration Limits P/L Limits

10. CAPITAL & LIQUIDITY SHOULD BE DRIVEN BY RISK INTELLIGENCE NOT ONLY RWA Global Risk Infrastructure Framework Market Intelligence Portfolio Intelligence Intelligent Data RISK FACTORS Cross-silo exposure from: business lines products regions Multiple vendor feed Internal pricing feed Reference data Counterparty data Ratings Scenario Simulations Risk Intelligence Liquidity Risk Capital & Liquidity Strategy Exposure Sensitivity Max Loss Reverse Stress Test Gaps Concentrations Contingencies Enterprise Risk Management Monitor 1 2 3 4 5 8 7 6 5 CREATING A RISK INTELLIGENT GOVERNANCE AND COMPLIANCE FRAMEWORK

11. Enterprise-wide aggregation (by risk factor) Sensitivity analysis (portfolio and entity level) Stress testing Effective counterparty exposure Expected Positive Exposure (EPEs) Credit Value Adjustments (CVAs) GOVERNANCE DRIVEN Liquidity Risk Management Stress test ALM & gap analyses Counterparty driven gap analyses Collateral liquidity Valuations of OBS exposure CREATING RISK INTELLIGENCE Limit & Collateral Management Net counterparty exposure Risk concentration and sensitivity limits Leverage ratios and OBS COMPLIANCE DRIVEN

12. THE FALLACY OF MODERN FINANCE THEORY Modern finance theory leads to Measuring expected return as a function of volatility (CAPM) Diversifying risks through expectations of low covariance Expressing tail event probabilities as a frequency of occurrence The act of (collectively) observing an area of financial safety makes it risky A. Persaud. Dec 2002

13. COVARIANCE RELIES ON INVESTORS’ BEHAVIOUR NOT ON HISTORICAL DATA Variables are wrongly assumed to be independent

14. SPIRIT OF BASLE III (BCBS 164 on Strengthening Resilience) Quality and consistency of capital base T1 Equity only T2 5 year minimum maturity, hybrids phased out T3 abolished Enhanced risk coverage Stressed VaR (includes periods of stress) Credit Value Adjustment (CVA) to represent counterparty risk in market exposure Push on centralised clearing counterparties Wrong-Way risk Leverage ratio Ratio added to Pillar1 calculated with credit conversion factors Focus on off-balance sheet items Counter-cyclical measures Probability of Default (PD) and Exposure At Default (EAD) computed over long term Expected Loss (EL) to replace IAS39 Capital buffers to limit excess credit and leverage Global Liquidity Standard (BCBS 165)

15. GOVERNANCE DRIVEN CREATING A RISK INTELLIGENT INDUSTRY COMPLIANCE DRIVEN Counterparty Risks Concentrations and leverage Collateral and margin management (reflect concentrations) Liquidity Dynamic gap analysis under scenarios Concentrations on funding sources Stress tests of exposure and collateral Market Risks Concentrations, root risk and indirect exposure Credit and liquidity risk priced in market risk Mark-to-volitilty, mark-to-liquidity Volatility and correlations Potential reverse impact of volatility and concentrations on correlations correlation and market depth

16. ENHANCE TRANSPARENCY Attach risk-ratings to ALL instruments including OTC and funds Rate financial risks, volatility, liquidity, transparency Adapt valuation frequency to risk ratings (Mark-to-Risk)

17. MONITOR BEHAVIOURS Attach risk-ratings to ALL instruments including OTC and funds Rate financial risks, volatility, liquidity, transparency Adapt valuation frequency to risk ratings (Mark-to-Risk)

18. RISK & LIQUIDITY CONCENTRATION BENCHMARKS

19. AGGREGATED TERM STRUCTURE OF MISMATCHES IN FOREIGN CURRENCIES Banks contribute foreign exchange claims in US$m by 1-Currency 2-Instrument type (fxswap, loan type, asset, liability) 3-Tenor (time bucket) 4-Volatility time bucket (if applicable) 5-Strike bucket (if applicable) Thomson Reuters Term Structure of Asset/Liabilities by currency Regulators input scenario 1-Interest rates 2-Exchange rate 3-Volatility 4-Correlation o Aggregated views foreign exchange claims by time bucket o Gap analysis (Asset/Liability mismatch) o Sensitivity analysis (under scenarios) o Volatility concentration matrices o Strike/Barriers concentration matrices o Central bank gets view of potential bubbles o Regulators can anticipate on funding issues per currency and instrument o Aggregated risk view in GBP o Banks can benchmark their funding risk against industry view. 1 2 3 Allow an assessment of firms’ currency liquidity risks and their potential vulnerabilities to a drying up of certain currency swap markets

20. VARIABLE CAPITAL ADEQUACY RATIOS & CROSS-SYSTEM SIMULATIONS Combine modeling, human judgment and consensus based consultation Adjust regulatory policies according to risk intelligence Anticipate bubbles and eradicate systemic risk

21. Regulators’ insights depend on risk intelligence. Single desk / portfolio Unsophisticated Data Management Collection Risk Aggregation Portfolio view of firm-wide risk Dynamic aggregation of contextualized risk Multi desk / portfolio Static post-trade risk aggregation 21 Risk Intelligence is the New Efficient Frontier Risk Intelligence Risk measurements Value Balancing shareholder value versus risk exposure depends on the firm’s assessment of its aggregate sensitivity to risk factors under changing conditions and on its ability to act upon it. Equity Prices Public Company Fundamentals Pricing & Reference data Valuation Risk Information Data Evaluated Pricing Risk Benchmarks Risk Indices Risk Ratings Insights Analysis Stress Tests & Reverse Beta Duration Monte Carlo VaR Potential Future Exposure VaR Binomial Model Stress and Scenario Testing Post Trade Analytics

22. CRITICAL SUCCESS FACTORS IN IMA IMPLEMENTATION PHILIPPE CARREL Mumbai, July 21 st 2010 Risk Intelligence: The 21 st Century Frontier of Market Efficiency