Javed H Siddiqi discusses risk management and the Basel Accords. The document covers: 1) An overview of risk management, including definitions of risk, the risk management process, and assessing risk tolerance. 2) A summary of the Basel I accord, including how it calculated regulatory capital requirements for credit and market risk. 3) An overview of the Basel II accord, which introduced approaches for calculating capital for operational risk and made capital requirements more risk sensitive.

5. 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.

13. What Does Capital Management Entail? Capital Management Product Pricing Financial Risk Mgt. Setting Objectives Raising Capital Strategic Planning Liability Valuation Asset Allocation Risk Management

19. Financial Risk and Basel Javed H Siddiqi

22. RIWAC Calculation RIWAC On-Balance Sheet x Counterparty Weighting Off-Balance Sheet Risk x Counterparty Weighting x Credit Conversion Factor = +

23. RIWAC Weightings 100% Non OECD Sovereigns 0% OECD 100% Corporates OECD Non OECD 100% Banks 20% On-Balance Sheet Risk N/A N/A N/A N/A N/A N/A Off Balance Sheet Risk Cont. liabilities 4% 10% 20% 20% 50% 100% 20% 50% 100% Secured LCs Issued Transactional Contingents Financial Guarantees

24. BASEL I- RIWAC Examples Corporate XYZ 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 Banks XYZ 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 Contingents XYZ 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

26. Basel I regulatory capital rules – Credit risk (2) Off-balance sheet risk weights and Basel I capital calculation for trading assets 10.0% 7.0% 6.0% 1.0% 0.0% Less than 1 year Commodity contracts Precious metals Equity derivatives FX and Gold Interest rates More than 5 years 1-5 years 1.5% 0.5% 7.5% 5.0% 10.0% 8.0% 8.0% 7.0% 15.0% 12.0% Credit Conversion Factor (%) 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 Step 5: Capital = 8% X RWA

29. Comparison Introduces approaches for Credit risk and Operational risk in addition to Market risk introduced earlier. Operational risk not considered More risk sensitivity Broad brush structure Flexibility, menu of approaches. Provides incentives for better risk management One size fits all More emphasis on banks’ internal methodologies, supervisory review and market discipline Focus on a single risk measure Basel 2 Basel I

34. Overview of Basel II Approaches (Pillar I) Approaches that can be followed in determination of Regulatory Capital under Basel II Total Regulatory Capital Operational Risk Capital Credit Risk Capital Market Risk Capital Basic Indicator Approach Standardized Approach Advanced Measurement Approach (AMA) Standardized Approach Internal Ratings Based (IRB) Foundation Advanced Standard Model Internal Model Score Card Loss Distribution Internal Modeling

38. RISK BASED SUPERVISION

39. BASEL II : CAPITAL CHARGE

41. CREDIT RISK WEIGHTS

46. Standardized Approach

47. Internal Ratings Based

48. FIRB VS. AIRB

54. Credit Risk Impact

60. Ops Risk Impact

70. Banks approach to Basel II Transformation A Journey of Seven Steps… Phase I: Gap Analysis Phase II: Implementation Roadmap Phase III: Implementation Phase IV: Compliance And Certification Approach to Basel II: Recommended Seven Steps Supervisory Certification, Parallel Run and Go Live Basel II Program Initiation Gap Analysis Implementation Roadmap Organization, Policies And Processes Redesign Data Management & IT Applications Analytics- Models, Methodologies and Validation

72. MINIMUM CAPITAL REQUREMENTS FOR BANKS (SBP Circular no 6 of 2005) 14% 12% 5 12% 10% 4 10% 9% 3 8% 8% 1 & 2 31 st Dec., 2006 and onwards 31 st Dec. 2005 Institutional Risk Assessment Framework (IRAF) Required CAR effective from IRAF Rating

87. IV. Managing Operational Risk Dashboards - Dynamic risk analysis Key Risks /Key Performance Indicators Risk & Control Self-Assesment (RCSA) Internal Reporting : Mapping of losses Four Dimensions of Operational Risks

93. Dimension Four : RCSA

96. Dimension Four : RCSA Assessment : Impact / Probability Matrix Based on a risk analysis report which reflects all (residual) risks and controls. Note : each point on the graph represents a different event or potential risk. Ex. Misleading capture screen in equity brokerage Ex. Product misspecification

100. V. Measuring the impact of ORM -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. V. Measuring the impact of ORM 0.75% 0.43% 0,51% 0.28% - BL2 – Retail Banking 243,922 140,041 165,387 91,112 - BL2 – Retail Banking 243,922 202,704 232,937 189,114 - TOTAL BL Reorganization Audit Tracking Dashboards Lessons 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 - 62,663 67,550 98,003 - BL1 – Asset Management/Private Banking BL Reorganization Audit Tracking Dashboards Lessons 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

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. Types of financial risk Financial Risks Liquidity Risk Operational Risk Regulatory Risk Human Factor Risk Market Risk Equity Risk Interest Rate Risk Currency Risk Commodity Risk Trading Risk Gap Risk Credit Risk Portfolio Concentration Risk Transaction Risk Counterparty Risk Issuer Risk

107. 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 Measure, Monitor & Manage – Value at Risk

108. Variance- covariance Matrix Multiple Portfolios Yields Duration Incremental VaR Stop Loss Portfolio Optimization VaR Features of RMD VaR Model Facility of multiple methods and portfolios in single model Return Analysis for aiding in trade-off For Identifying and isolating Risky and safe securities For picking up securities which gel well in the portfolio For aiding in cutting losses during volatile periods Helps in optimizing portfolio in the given set of constraints

118. Gap, Interest Rate Changes, and Net Interest Income No Change Decrease RSA=RSL Zero No Change Increase RSA=RSL Zero Increase Decrease RSA<RSL Negative Decrease Increase RSA<RSL Negative Decrease Decrease RSA>RSL Positive Increase Increase RSA>RSL Positive Change in Net Interest Income Change in Interest Rates Gap

122. Duration Gap, Interest Rate and Changes in Net Worth No Change Decrease Zero No Change Increase Zero Decrease Decrease Negative Increase Increase Negative Increase Decrease Positive Decrease Increase Positive Change in Net Worth Change in interest Rate Duration Gap

123. History

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

127. Short-Term Rating Grade Mapping and Risk Weight 4 3 2 1 External grade (short term claim on banks and corporate) 150% Other Other S4 100% A-3 A-3 S3 50% A-2 A-2 S2 20% A-1 A-1 S1 Risk Weight JCR-VIS PACRA SBP Rating Grade

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 Portfolio Credit Risk Attributes Relationship to other assets within the portfolio Exposure size relative to the portfolio Default Correlation Relative Concentration

143. Best Practices for Credit 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

148. ONE DIMENSIONAL R RMD’s modified TWO DIMENSIONAL approach Rating reflects Expected Loss CONCEPTUALLY SOUND INTERNAL RATING MODEL – CAPTURES PD, LGD SEPARATELY 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.

151. Types of Rating System: An Example RISK FACTORS SCORE RELATIVE IMPORTANCE Subjective factors 1. Management 32% Strong 100 Weak 0 2. Entry barrier 25% High 100 Low 0 Objective factors 3. Gearing 34.5% <=50% 100 > 50% 0 4. Earnings growth 8.5% >= 10% 100 < 10% 0 Risk factors & scores determined by judgements Relative importance determined by models

176. ‘ 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. I t 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

177. PORTFOLIO CREDIT VaR Expected (EL) Priced into the product (risk-based pricing) Unexpected (UL) Covered by capital reserves (economic capital) Probability Loss (L) Credit Capital models the loss to the value of the portfolio due to changes in credit quality over a time frame

178. ARE CORRELATIONS IMPORTANT 99.99% 99.67% 99.35% 99.03% 98.71% 98.39% 98.07% 97.75% 97.43% 97.11% 96.79% 96.47% 96.15% 95.83% 95.51% 95.19% Correlation Probability of Default Confidence level Large impact of correlations RELATIVE CONTRIBUTION OF CORRELATIONS AND PROBABILITY OF DEFAULT IN CREDIT VaR CREDIT VaR Source: S&P 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

179. Corr(X,Y)=ρ xy =Cov(X,Y)/std(X)std(Y) 2.07 1.99 4.33 2.21 1.48 0.22 1.67 1.30 1.78 0.67 0.05 1.31 2.39 Utility 1.99 3.85 5.63 4.78 3.40 1.08 2.82 2.61 3.29 1.03 -0.28 2.56 3.56 Trans 4.33 5.63 16.72 -1.14 3.51 0.50 4.63 5.21 3.85 -0.04 -0.44 2.49 7.04 Telecom 2.21 4.78 -1.14 13.15 9.39 0.46 3.83 0.91 7.32 6.27 -0.20 6.03 2.40 Real Est. 1.48 3.40 3.51 9.39 4.07 0.10 2.45 2.12 3.64 1.88 -1.63 2.01 2.06 Leisure 0.22 1.08 0.50 0.46 0.10 96.00 0.47 0.41 0.41 -0.03 0.75 0.52 0.67 Insur 1.67 2.82 4.63 3.83 2.45 0.47 3.01 2.34 2.78 0.73 0.75 1.69 3.11 High tech 1.30 2.61 5.21 0.91 2.12 0.41 2.34 3.50 2.09 0.52 0.94 1.60 3.65 Chem 1.78 3.29 3.85 7.32 3.64 0.41 2.78 2.09 3.81 1.54 -0.49 2.36 2.68 Build 0.67 1.03 -0.04 6.27 1.88 -0.03 0.73 0.52 1.54 1.39 -0.50 0.83 0.67 Finan 0.05 -0.28 -0.44 0.20 -1.63 0.75 0.75 0.94 -0.49 -0.50 4.74 -1.41 1.57 Energ 1.31 2.56 2.49 6.03 2.01 0.52 1.69 1.60 2.36 0.83 -1.41 2.51 1.84 Cons 2.39 3.56 7.04 2.40 2.06 0.67 3.11 3.65 2.68 0.67 1.57 1.84 4.81 Auto Utility Trans Tele R.E. Leisure Insur Hi tech Chem Build Finan Energ Cons Auto 3-Year Default Correlations

180. RMD’s approach ‘CREDIT CAPITAL’ Overall Architecture STEP 1 From the historical correlation data of industries, the firm-to-firm correlations are found. STEP 2 Calculate 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 4 Using 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. Average variability explained by each industry Industry Correlation Step 1 Tenor of Evaluation, Current Rating Correlations Transition rates Step 2 Return Thresholds Simulated Credit Scenarios Step 3 Monte Carlo simulation Migration Portfolio Loss Distribution Spot & Forward Curve for each grade Recovery Rates Valuation Step 4 Exposure Default

181. Credit Risk - Raroc

186. 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 RAROC - Definition & Hypotheses

193. RAROC 22% EVA 310 Risk-adjusted Net income 1750 Capital Charge 1440 Risk-adjusted After tax income 1.75% Average Lending assets 100 000 Total capital 8000 Cost of capital 18% Risk-adjusted Net income 2.20% Net Tax 0.45% Total capital 8.0 % Average Lending assets 100 000 Risk-adjusted income 5.60 % Costs 3.40 % Credit Risk Capital 4.40 % Market Risk Capital 1.60 % Operational Risk Capital 2.00 % Income 6.10 % Expected Loss 0.50 % RAROC Profitability Tree – an illustration

196. Interest Rate Risk Spread Risk Default Risk Credit Default Swap Credit Spread Swap Total Return Swap Basket Credit Swap Securi Securitization tization Credit Portfolio Risks Different Hedging Techniques . . . as we go along, the extensive use of credit derivatives would become imminent 9. Use Hedging techniques

200. INTERNAL EXPOSURE LIMIT PER PARTY 2% of tier-1 4:5 2.5% of tier-1 4:4 5% of tier-1 4:3 10% of tier-1 4:2 15% of tier-1 4:1 Risk Rated “4” 2.5% of tier-1 3:4 5% of tier-1 3:4 10% of tier-1 3:3 15% of tier-1 3:2 22% of tier-1 3:1 Risk Rated “3” 5% of tier-1 2:5 10% of tier-1 2:3 15% of tier-1 1:2 20% of tier-1 2:2 25% of tier-1 2:1 Risk Rated “2” 10% of tier-1 1:5 15% of tier-1 1:4 20% of tier-1 1:3 25% of tier-1 1:2 30% of tier-1 1:1 Risk Rated “1” Risk Rated “5” Risk Rated “4” Risk Rated “3” Risk Rated “2” Risk Rated “1” Risk Rating of the Industry

201. INTERNAL EXPOSURE LIMIT PER GROUP 2% of Tier -1 Capital 4:5 2.5% of Tier -1 Capital 4:4 5% of Tier -1 Capital 4:3 10% of Tier -1 Capital 4:2 20% of Tier -1 Capital 4:1 Risk Rated “4” 2.5% of Tier -1 Capital 3:5 5% of Tier -1 Capital 3:4 10% of Tier -1 Capital 3:3 20% of Tier -1 Capital 3:2 30% of Tier -1 Capital 3:1 Risk Rated “3” 5% of Tier -1 Capital 2:5 10% of Tier -1 Capital 2:4 20% of Tier -1 Capital 2:3 30% of Tier -1 Capital 2:2 45% of Tier -1 Capital 2:1 Risk Rated “2” 10% of Tier -1 Capital 1:5 20% of Tier -1 Capital 1:4 30% of Tier -1 Capital 1:3 45% of Tier -1 Capital 1:2 50% of Tier -1 Capital 1:1 Risk Rated “1” Risk Rating (Group) Risk Rating “5” Risk Rating “4” Risk Rating “3” Risk Rating “2” Risk Rating “1” Risk Rating Industry

203. Sample Credit Rating Transition Matrix ( Probability of migrating to another rating within one year as a percentage) Credit Rating One year in the future 18.60 39.97 24.86 12.34 2.06 1.85 0.25 0.06 CCC 5.58 10.13 63.89 2.31 8.29 9.25 0.36 0.21 B 1.32 4.14 8.05 74.68 5.53 3.29 2.91 0.08 BB 0.07 0.16 0.32 6.51 84.21 5.00 1.89 1.84 BBB 0.03 0.06 0.13 1.48 7.40 89.05 1.59 0.27 A 0.02 0.05 0.13 1.11 2.16 7.47 88.23 0.84 AA 0.02 0.02 0.10 0.12 0.63 0.45 10.93 87.74 AAA Default CCC B BB BBB A AA AAA C U R R E N T CREDIT R A T I N G

207. Thanks for your attention . . .