Introduction

In today's intricate and volatile financial landscape, effective Advanced Credit Risk Management is no longer just a regulatory requirement but a critical differentiator for financial institutions seeking sustainable growth and resilience. As economic conditions fluctuate, interest rates shift, and new technologies emerge, the ability to precisely identify, measure, monitor, and mitigate credit risk across diverse portfolios becomes paramount. Moving beyond traditional assessment methods, advanced techniques leverage sophisticated analytical models, robust data infrastructure, and forward-looking stress testing to provide a deeper, more nuanced understanding of potential defaults and losses. This proactive and comprehensive approach enables banks, investment firms, and specialized lenders to optimize capital allocation, enhance pricing strategies, and navigate unforeseen market shocks with greater confidence. Without mastering Advanced Credit Risk Management, financial institutions risk accumulating excessive non-performing assets, facing severe capital constraints, and ultimately jeopardizing their stability and profitability in a competitive global market, underscoring the vital need for specialized expertise in this critical domain. This comprehensive training course focuses on equipping professionals with the expertise to master Advanced Credit Risk Management.

This training course is meticulously designed to empower risk managers, credit analysts, portfolio managers, quantitative analysts, senior management, and compliance officers within financial institutions with the theoretical understanding and practical skills necessary to implement and refine Advanced Credit Risk Management frameworks. Participants will gain a comprehensive understanding of advanced credit risk modeling techniques, learn about portfolio credit risk measurement, explore stress testing and scenario analysis methodologies, and acquire hands-on experience in utilizing sophisticated tools for capital allocation and risk-adjusted performance measurement. The course will delve into topics such as Probability of Default (PD) modeling, Loss Given Default (LGD) and Exposure at Default (EAD) estimation, correlation modeling, regulatory capital frameworks (e.g., Basel Accords), credit derivatives, and the crucial aspects of model validation and governance. By mastering the principles and practical application of Advanced Credit Risk Management, participants will be prepared to drive more informed lending decisions, optimize risk-return trade-offs, ensure regulatory compliance, and contribute significantly to the financial strength and strategic positioning of their organizations.

Duration: 5 Days

Target Audience

• Credit Risk Managers and Directors
• Senior Credit Analysts and Underwriters
• Portfolio Managers (Lending, Fixed Income)
• Quantitative Analysts (Quants)
• Risk Model Developers and Validators
• Financial Analysts and Strategists
• Regulatory Compliance Officers
• Internal Auditors (Specializing in Risk)
• Senior Management (Banking, Investment Firms, Large MFIs/SACCOs)
• Consultants in Financial Risk Management

Objectives

• Understand the advanced concepts and methodologies of credit risk measurement and management.
• Learn to develop and apply sophisticated Probability of Default (PD) models.
• Acquire skills in estimating Loss Given Default (LGD) and Exposure at Default (EAD).
• Comprehend techniques for measuring and managing portfolio credit risk, including correlation.
• Explore strategies for conducting robust stress testing and scenario analysis.
• Understand the implications of regulatory capital frameworks (e.g., Basel) for credit risk.
• Gain insights into credit derivatives and structured finance from a risk perspective.
• Develop a practical understanding of model validation, governance, and ethical considerations in advanced credit risk.

Course Content

Module 1: Foundations of Advanced Credit Risk

• Review of basic credit risk concepts and the "5 Cs".
• The advanced credit risk landscape: economic cycles, regulatory evolution, data science.
• Components of credit risk: Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD).
• Role of advanced analytics and quantitative models in credit risk.
• Enterprise Risk Management (ERM) framework and credit risk integration.

Module 2: Probability of Default (PD) Modeling

• Quantitative approaches to PD modeling: statistical and machine learning methods.
• Logistic Regression for PD estimation.
• Scorecard development and calibration.
• Rating systems (internal vs. external) and mapping.
• Data requirements and challenges for PD models.

Module 3: Loss Given Default (LGD) and Exposure at Default (EAD) Estimation

• Definition and importance of LGD and EAD.
• Methodologies for LGD estimation: workout LGD, market LGD.
• Key drivers of LGD: collateral, recovery processes, legal frameworks.
• EAD modeling for different product types (revolvers, commitments).
• Practical considerations and data limitations in LGD/EAD modeling.

Module 4: Portfolio Credit Risk Measurement

• Aggregating individual credit risks to portfolio level.
• Understanding credit correlation and its impact on portfolio risk.
• Credit Value at Risk (CVaR) and Expected Shortfall (ES).
• Diversification benefits and concentration risk.
• Introduction to portfolio credit risk models (e.g., CreditMetrics, CreditRisk+ - conceptual).

Module 5: Stress Testing and Scenario Analysis

• Purpose and benefits of stress testing for credit risk.
• Designing stress scenarios: macro-economic shocks, industry-specific events.
• Methodologies for stress testing credit portfolios.
• Interpreting stress test results and their implications for capital and strategy.
• Reverse stress testing.

Module 6: Regulatory Capital Frameworks (Basel Accords)

• Overview of Basel I, II, and III Accords for credit risk.
• Standardized Approach vs. Internal Ratings-Based (IRB) Approach.
• Pillar 1: Minimum Capital Requirements (RWA calculation).
• Pillar 2: Supervisory Review Process.
• Pillar 3: Market Discipline and Disclosure Requirements.

Module 7: Credit Derivatives and Structured Credit Products

• Introduction to credit derivatives: Credit Default Swaps (CDS), Total Return Swaps (TRS).
• Applications of credit derivatives in managing and hedging credit risk.
• Understanding Collateralized Debt Obligations (CDOs) and their credit risk profile.
• Securitization of loan portfolios.
• Risks and benefits of structured credit products.

Module 8: Model Validation, Governance, and Emerging Trends

• Importance of independent model validation.
• Model risk management framework: development, implementation, review.
• Data governance for credit risk models.
• Ethical considerations in credit risk modeling: bias, fairness, transparency.
• Emerging trends: AI/Machine Learning in credit risk, climate risk in credit, IFRS 9 implications.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 10 working days before commencement of the training.