Course Information

Introduction

Objectives

Who Should Attend?

Training Method

Program Support

Daily Agenda

Week 1

Day 1: Quantitative Risk Model Building

Identifying risk factors and data requirements
A. Mapping market, credit, and operational risk exposures
B. Sourcing and validating historical data for model calibration
C. Ensuring data quality and addressing missing data issues
Building market risk models
A. Calculating Value at Risk (VaR) using historical, variance-covariance, and Monte Carlo methods
B. Modeling interest rate and foreign exchange risk exposures
C. Incorporating correlation structures between different asset classes
Building credit risk models
A. Estimating Probability of Default (PD) and Loss Given Default (LGD)
B. Modeling Expected Loss (EL) and Unexpected Loss (UL)
C. Applying credit scoring and rating migration techniques

Day 2: Model Validation and Backtesting

Establishing validation frameworks
A. Defining the scope and objectives of the model validation process
B. Reviewing model documentation and theoretical soundness
C. Assessing the appropriateness of model assumptions and limitations
Conducting backtesting
A. Comparing model predictions against actual historical outcomes
B. Calculating exception rates and assessing statistical significance
C. Identifying and diagnosing the root causes of model failures
Performance metrics and stress testing
A. Evaluating model accuracy, stability, and discriminatory power
B. Applying stress tests to assess model performance under adverse conditions
C. Documenting validation findings and recommending model enhancements

Day 3: Risk Measures and Capital Assessment

Calculating advanced risk measures
A. Computing Expected Shortfall (ES) and Conditional VaR (CVaR)
B. Calculating stressed VaR to capture tail risk events
C. Measuring liquidity risk and funding cost exposures
Translating risk to capital requirements
A. Mapping risk measures to regulatory capital frameworks (e.g., Basel III/IV)
B. Calculating economic capital based on internal risk models
C. Assessing the impact of risk models on return on equity (ROE)
Limit setting and monitoring
A. Establishing risk limits based on risk appetite and capital capacity
B. Designing monitoring routines to track limit utilization
C. Implementing escalation procedures for limit breaches

Day 4: Model Risk Management and Governance

Establishing model governance
A. Defining roles and responsibilities for model development and validation
B. Creating a model inventory and classification system
C. Implementing version control and change management procedures
Managing model risk
A. Identifying and assessing model risk across the organization
B. Developing mitigation strategies for high-risk models
C. Integrating model risk into the enterprise risk management framework
Regulatory compliance and documentation
A. Ensuring models meet current regulatory expectations and guidelines
B. Preparing comprehensive documentation for regulatory review
C. Conducting internal audits of model risk management practices

Day 5: Stakeholder Reporting and Actionable Insights

Designing risk reports
A. Structuring reports for different audiences (board, risk committee, business units)
B. Selecting appropriate visualizations for complex risk data
C. Ensuring reports are clear, concise, and actionable
Communicating model limitations
A. Clearly articulating the assumptions and constraints of risk models
B. Explaining the impact of model uncertainty on decision-making
C. Providing context for risk metrics to avoid misinterpretation
Driving business decisions
A. Translating risk model outputs into strategic recommendations
B. Advising business units on risk-adjusted pricing and capital allocation
C. Presenting model results and limitations to senior stakeholders