Training Course: IFRS 9 – Expected Credit Loss (ECL) Modeling

Introduction

The adoption of IFRS 9 has transformed how financial institutions handle credit loss provisioning through the Expected Credit Loss (ECL) model. This forward-looking approach requires a deep understanding of ECL principles, methodologies, and regulatory compliance. This comprehensive training course will provide participants with the skills and knowledge necessary to apply ECL modeling, implement it effectively, and ensure compliance with IFRS 9 standards. Participants will gain both theoretical understanding and practical application through real-world financial instruments.

Course Objectives

By the end of this course, participants will be able to:

• Understand the key principles and framework of IFRS 9, especially in relation to the Expected Credit Loss (ECL) model.
• Apply appropriate methodologies for calculating ECL, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD).
• Develop and validate ECL models aligned with IFRS 9 requirements.
• Interpret and analyze ECL outcomes for financial reporting and decision-making.
• Ensure compliance with regulatory expectations and internal audit standards.

Course Outlines

Day 1: Foundations of IFRS 9 and Credit Risk

• Overview of IFRS 9 and comparison with IAS 39.
• Classification and measurement of financial instruments.
• Introduction to credit risk and impairment requirements.
• Definition of ECL and rationale for a forward-looking model.
• Staging criteria: 12-month ECL vs. lifetime ECL.

Day 2: ECL Components and Modeling Basics

• Components of ECL: PD, LGD, EAD.
• Approaches to modeling Probability of Default (PD).
• Loss Given Default (LGD) estimation techniques.
• Exposure at Default (EAD) modeling approaches.
• Data sourcing and quality assessment for modeling.

Day 3: ECL Calculation and Implementation

• ECL formula and scenario-weighted approach.
• Discounting of expected cash flows and the time value of money.
• Use of macroeconomic variables and forward-looking information.
• Model validation, calibration, and back-testing.
• Incorporating overlays and expert judgment.

Day 4: Practical Applications and Case Studies

• Segmenting portfolios for ECL modeling.
• Retail vs. corporate exposures: Modeling differences.
• Case study: Developing an end-to-end ECL model.
• Hands-on ECL model building using Excel/Python (optional).
• Review of financial disclosures and audit trails.

Day 5: Governance, Challenges, and Regulatory Expectations

• Model governance and documentation best practices.
• Addressing model risk and validation findings.
• Key audit considerations and internal controls.
• Regulatory expectations (e.g., Basel, ECB, IFRS IC).
• Wrap-up: Lessons learned and future ECL developments.

Why Attend this Course: Wins & Losses!

• In-depth Knowledge: Gain a deep understanding of IFRS 9, focusing on ECL models and their application.
• Practical Application: Learn to build, validate, and implement ECL models using real-world scenarios and tools like Excel and Python.
• Regulatory Compliance: Equip yourself with the knowledge to ensure compliance with regulatory requirements, mitigating risks of non-compliance.
• Industry-Relevant Skills: Develop essential skills in credit risk management, financial reporting, and decision-making.

Conclusion

By the end of this course, participants will have a comprehensive understanding of the IFRS 9 framework and the skills necessary to apply ECL modeling effectively. This course will empower professionals to develop, validate, and implement ECL models, ensuring compliance with IFRS 9 standards and enhancing their organization's credit risk management processes.

Whether you are working in financial institutions, auditing firms, or regulatory bodies, this course will provide the necessary tools to navigate the complex landscape of credit risk under IFRS 9.