Course Overview

Credit risk guarantee institutions operate in complex financial environments where strong risk management and effective monitoring systems are essential for sustainability and regulatory compliance. Weak frameworks can expose institutions to significant losses and undermine market confidence.

The Enterprise Risk Management and Monitoring & Evaluation (M&E) for Credit Risk Guarantee Projects programme provides a structured and practical approach to managing credit and enterprise risks. Participants will explore quantitative credit risk modelling, regulatory frameworks, stress testing, portfolio risk analysis, and monitoring systems.

The programme combines theoretical knowledge with practical application, enabling participants to measure, manage, and monitor credit risk effectively, design robust ERM frameworks, and support informed decision-making within credit guarantee and financial institutions.

Agenda

Day — 1 Understanding Enterprise & Credit Risk

• Defining credit risk and enterprise risk and their importance in credit guarantee institutions
• Understanding risk appetite and identifying different types of risk exposures
• Exploring components of Enterprise Risk Management (ERM) frameworks and risk architecture
• Analysing macroeconomic, institutional, and borrower-level factors affecting credit risk
• Understanding credit guarantee programmes and risk-sharing mechanisms
• Exercise: Mapping sources of credit risk across a sample balance sheet

Day — 2 Quantitative Foundations of Credit Risk

• Understanding core credit risk parameters:
  • Probability of Default (PD)
  • Loss Given Default (LGD)
  • Exposure at Default (EAD)
• Explaining the concepts of expected loss and unexpected loss in risk measurement
• Analysing portfolio credit risk, including correlation and diversification effects
• Understanding credit migration and the role of transition matrices in assessing risk changes
• Exploring internal and external data sources used in credit risk modelling
• Practical exercise: Estimating exposure levels, loss severity, and default probabilities

Day — 3 Credit Ratings & Internal Risk Models

• Comparing external credit ratings with internal credit scoring systems
• Understanding methodologies used by major rating agencies and their implications
• Designing internal scoring models using:
  • Financial indicators
  • Non-financial indicators
• Identifying biases, data limitations, and model risks in credit scoring
• Applying validation techniques and back-testing to ensure model accuracy and reliability

Day — 4 Regulatory & Accounting Standards

• Differentiating between banking book and trading book exposures
• Understanding capital requirements under Basel III and Basel IV frameworks
• Exploring Expected Credit Loss (ECL) concepts and provisioning requirements under IFRS 9
• Analysing the treatment of off-balance sheet exposures in credit guarantee structures
• Understanding the role of capital and liquidity buffers in financial stability
• Examining the impact of evolving capital and liquidity regulations on institutions
• Exercise: Estimating expected credit losses for a sample portfolio under IFRS 9

Day — 5 Counterparty Credit Risk & Derivatives

• Defining counterparty credit risk (CCR) and its key characteristics
• Understanding valuation adjustments:
  • Credit Valuation Adjustment (CVA)
  • Debt Valuation Adjustment (DVA)
• Analysing Wrong Way Risk (WWR) and its impact on exposure
• Exploring key counterparty risk metrics:
  • Expected Exposure (EE)
  • Expected Positive Exposure (EPE)
  • Potential Future Exposure (PFE)
• Understanding collateral management and ISDA/CSA documentation
• Assessing the role of netting and margining in reducing counterparty risk
• Exercise: Estimating potential exposure and evaluating CVA for a derivative portfolio

Day — 6 Building Quantitative Credit Risk Models

• Exploring key credit risk modelling frameworks:
  • CreditMetrics
  • CreditRisk+
  • KMV-Merton
• Understanding firm value models and the concept of distance to default
• Applying simulation and stochastic modelling techniques to estimate default probabilities
• Using copula methods to assess joint default risks within portfolios
• Analysing credit portfolio optimisation and recovery rate estimation
• Understanding Credit Value at Risk (CVaR) and its role in portfolio risk management
• Applying model calibration, back-testing, and validation techniques
• Exercise: Building a simplified CreditMetrics model to estimate portfolio risk

Day — 7 Sovereign & Institutional Credit Risk

• Defining sovereign risk and distinguishing it from corporate credit risk
• Analysing key macroeconomic indicators influencing sovereign creditworthiness:
  • Debt-to-GDP ratio
  • Fiscal balance
  • Foreign exchange reserves
• Understanding the sovereign–bank nexus and contagion risks within financial systems
• Reviewing sovereign credit default swaps (CDS) and their role in risk assessment
• Exploring debt restructuring tools and mitigation strategies:
  • Bailouts
  • Collective Action Clauses (CACs)
• Assessing implications for national and regional credit guarantee schemes
• Case study: Evaluating the market impact of a sovereign credit rating downgrade

Day — 8 Stress Testing & Scenario Analysis

• Understanding the objectives and principles of stress testing in risk management
• Exploring top-down and bottom-up stress testing frameworks
• Applying scenario analysis to assess portfolio resilience under adverse conditions
• Designing macroeconomic and sensitivity-based stress scenarios
• Using simulation techniques such as Monte Carlo and bootstrapping for portfolio testing
• Evaluating stress testing models through back-testing and performance assessment
• Exercise: Developing a stress-testing scenario for a corporate loan portfolio

Day — 9 Reading Market Data & Credit Risk Indicators

• Understanding yield curves and term structure movements
• Analysing credit spreads and their relationship with credit risk
• Interpreting bond spreads and swap spreads as indicators of market conditions
• Understanding Credit Default Swaps (CDS) and Option-Adjusted Spreads (OAS)
• Identifying signals of investor confidence and market sentiment
• Using market-based indicators for early warning of credit deterioration
• Case study: Analysing CDS and spread data for selected sovereigns or corporates

Day — 10 Managing & Monitoring Credit Risk

• Applying strategies for credit risk mitigation and portfolio diversification
• Using hedging instruments to manage exposure:
  • Guarantees
  • Insurance
  • Derivatives
• Measuring performance using risk-adjusted metrics
• Implementing monitoring and evaluation (M&E) techniques for credit risk
• Designing dashboards and reporting frameworks for effective risk tracking
• Establishing governance structures for strong credit risk oversight
• Case study: Designing a credit risk management and M&E plan for a credit guarantee institution
• Course evaluation and key lessons learned

Learning Outcomes

By enrolling in this Enterprise Risk Management and M&E for Credit Risk Guarantee Projects programme, you will be able to:

• Apply enterprise and credit risk principles to identify, measure, and manage risks
• Quantify and interpret credit risk parameters to assess potential losses
• Develop and evaluate internal credit rating and scoring systems
• Understand the impact of Basel III/IV and IFRS 9 on capital and provisioning
• Use modern tools to manage credit risk across counterparties and financial instruments
• Build and validate quantitative credit risk models for portfolio analysis
• Conduct stress testing and scenario analysis to assess financial resilience
• Use monitoring and evaluation tools, dashboards, and performance indicators to track risk performance

Who Should Attend

This programme is suitable for professionals working in risk management and financial institutions, including:

• Risk Managers and ERM Specialists
• Credit Risk Analysts and Managers
• Professionals working in credit guarantee institutions
• Financial Regulators and Supervisors
• Banking and Financial Services Professionals
• Monitoring and Evaluation (M&E) Specialists