Introduction

In the complex financial ecosystem, credit risk is a multifaceted challenge that extends beyond the traditional assets on a bank's balance sheet. A critical, yet often underappreciated, component is liability credit risk, which assesses the risk that a firm's own liabilities, such as bonds or derivative obligations, might not be met. While asset-side credit risk focuses on the potential for losses from borrowers defaulting, liability-side risk examines the potential for a firm's own financial distress to impact its ability to honor its commitments, a core consideration in frameworks like Basel IV. This advanced training course will equip you with the specialized skills to model, measure, and manage this distinct form of credit risk.

This comprehensive program delves into the theoretical foundations and practical applications of liability credit risk modeling. You will explore advanced quantitative techniques, including the use of structural and reduced-form models, to assess the probability of a firm's default and the potential for downgrade. The course emphasizes hands-on application, enabling you to build sophisticated models that integrate market data, financial statements, and macroeconomic factors. By mastering these methodologies, you will be able to provide a more holistic view of your institution's risk profile, ensuring compliance and enhancing strategic decision-making in a volatile financial landscape.

Duration: 10 Days

Target Audience

• Financial risk modelers
• Credit risk analysts
• Quantitative analysts
• Portfolio managers
• Investment banking professionals
• Treasury and funding managers
• Regulatory compliance officers
• Fixed income traders
• Audit and assurance professionals
• Financial engineering students

Objectives

• Understand the conceptual difference between asset and liability credit risk.
• Master the application of structural models (e.g., Merton Model).
• Implement reduced-form models for default probability.
• Learn to integrate market data into risk models.
• Model the impact of credit rating changes and downgrades.
• Assess the credit risk of derivatives and CVA.
• Develop a framework for stress testing liability credit risk.
• Use quantitative tools for liability portfolio analysis.
• Understand regulatory capital implications.
• Build a comprehensive liability credit risk framework.

Course Modules

Module 1: Foundations of Credit Risk

• A review of traditional asset-side credit risk
• The core concepts of default and recovery rates
• The difference between exposure and probability of default
• The role of ratings agencies and credit scores
• The link between credit risk and market risk

Module 2: Introduction to Liability Credit Risk

• The definition and scope of liability credit risk
• The impact of a firm's own credit standing on its liabilities
• The relationship between liability risk and funding costs
• Examples of liability risk in practice
• The importance of a holistic risk view

Module 3: Structural Models

• An introduction to the Merton Model
• Using asset value and volatility to estimate default
• The relationship between equity and corporate debt
• Extending the model to include more complex liabilities
• The limitations and assumptions of structural models

Module 4: Reduced-Form Models

• An introduction to default intensity models
• Modeling default as a surprise event
• Estimating default probabilities using market data
• Calibrating models to corporate bond spreads
• The use of hazard rates and transition matrices

Module 5: Data for Modeling

• Sourcing market data for bond yields and spreads
• Gathering firm-specific financial data
• The role of macroeconomic variables
• Cleaning and preparing data for modeling
• Building a reliable and auditable data pipeline

Module 6: Modeling Credit Risk in Derivatives

• The concept of credit valuation adjustment (CVA)
• Calculating the CVA for an over-the-counter (OTC) portfolio
• The impact of collateral agreements
• Modeling counterparty credit risk
• Stress testing the CVA

Module 7: The Impact of Credit Ratings

• How ratings agencies assign and update ratings
• Modeling the probability of a ratings downgrade
• The financial consequences of a downgrade
• Integrating ratings data into risk models
• The relationship between ratings and a firm's funding profile

Module 8: Stress Testing and Scenario Analysis

• Designing relevant stress test scenarios
• Running a portfolio through a stress test
• Interpreting the results and identifying vulnerabilities
• Communicating stress test findings to stakeholders
• Using stress testing to inform strategic decisions

Module 9: Liability Portfolio Analysis

• The credit risk of a portfolio of bonds and derivatives
• The concept of diversification in liability risk
• Measuring concentration risk in the liability book
• Using portfolio management tools for risk analysis
• Building a dashboard for real-time monitoring

Module 10: Capstone Project Part 1: Design

• Defining a specific liability to model
• Mapping the data requirements and model architecture
• Outlining the key technical and analytical requirements
• Creating a detailed project plan
• Presenting the design to a mock review board

Module 11: Capstone Project Part 2: Development

• Implementing a structural or reduced-form model
• Sourcing and preparing real market data
• Calibrating the model to the data
• Validating the model's output
• Documenting the code and the modeling process

Module 12: Capstone Project Part 3: Presentation

• Presenting the final model and its findings
• Demonstrating how the model can be used for decision-making
• Discussing the model's limitations and assumptions
• Q&A and peer feedback session
• Receiving expert recommendations and insights

Module 13: Regulatory and Accounting Implications

• The requirements of Basel IV and other frameworks
• The use of liability risk models for capital calculations
• The accounting treatment of credit risk on liabilities
• The role of auditors in reviewing models
• Preparing models for regulatory scrutiny

Module 14: Emerging Trends

• The use of machine learning in credit risk
• Incorporating climate and ESG factors into models
• The impact of distributed ledger technology
• The evolving regulatory landscape
• The future of credit risk modeling

Module 15: Course Certification

• A final comprehensive assessment
• A final review of key concepts and objectives
• Issuance of a certificate of completion
• Post-course career guidance and networking
• A final Q&A with instructors

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.