Building, Backtesting & Stress Testing Internal Risk Frameworks

In this 4 Day Course Participants will Learn: The essential features for market, credit and operational risk, internal modeling frameworks—practically and in light of the Basel requirements Individual and portfolio, enterprise-wide risk assessment for market, credit and operational risk exposure Integrated, portfolio risk exposure Validation of data sources and data quality; proper considerations in the construction of a data mart and the use of systems to deploy models on that data mart The appropriate architecture for model deployment Backtesting and validation methods in light of Basel II considerations and the latest, Basel III amendments Stress Testing in light of Basel III Portfolio stress testing Who should Attend Risk managers CFOs and CROs Treasury professionals Audit and IT personnel Basel team members
Day 1 Introduction Developing a risk assessment framework -Market, Credit and Operational Risks -Definitions and methods of assessment -Basel II/III-related criteria for assessing risks -Internal modeling approaches reviewed: -The Internal Measurement Approach (IMA) for Market Risk -The Standardized and Internal Ratings Based (IRB) Approaches for Credit Risk -The Standardized and Advanced Measurement Approaches (AMA) for Operational Risk -Integrating the approaches: Portfolio VaR -Individual stress testing illustrated -Integrated Stress Testing -Provisioning and Capital Allocation -Basel II and Basel III compared -Validation and Backtesting under Basel II and Basel III Internal Risk Modeling Market Risk Modeling -Internal Models Approach (IMA) -Examples of Tail Loss Models -Value-at-Risk -Expected Shortfall Day 2 Validation and Backtesting of IMA under Basel III -Backtesting Process -Clean vs Dirty P/L: That is, how to value returns -Binomial test -Traffic light approach – assumptions -Pitfalls of using traffic lights approach Stress Testing the Market Risk Modeling System Day 3 Credit Risk Modeling -The Standardized Approach (SA) -The Internal Ratings Based (IRB) Approach -Establishing a ratings scale -Estimating associated risk components (i.e., Probability of Default (PD), Loss Given Default (LGD) and Exposure at Default (EAD)) with the scale -Internal Measurement Models -Credit Valuation Adjustment (CVA) Risk -Counterparty Credit Risk models -Effective Expected Exposure -Effective Expected Positive Exposure -Wrong-Way risk Validation of the Customer Rating System -Validation of how scorecards/scoring models are implemented and applied -Database Validation: Assessing data limitations -In-sample Scorecard/Scoring model selection -Model-Risk Assessment -Out-of-Sample Scorecard/Scoring Model Validation -Testing Sample construction -Error rate estimation -Discrimination tests -ROC Plots and Area Under the ROC (AUROC) accuracy ratios -Cumulative Accuracy Profile (CAP) curves and Area under the cap (AR) accuracy ratios -Meaning, use and misuse of these measures -Comparing models using the tests Day 4 Facility ratings validation Loss Given Default (LGD) -Multi-sample tests for discerning differences in recovery rates -Backtesting LGD with confidence intervals Exposure at Default (EAD) Validation -Backtesting suggestions Stress testing the credit modeling system Operational Risk Approaches -Basic Indicator Approach -The Standardized Approach (TSA) -Key Risk Indicators KRIs -Utilizing Key Risk Indicators -Control self-assessment exercises (CSAs) -Utilizing KRIs in scorecards for management -The Advanced Measurement Approach (AMA) -The Loss Distribution Approach -Simulation -Backtesting and Stress testing Tail Loss Models Summary and Conclusions