Introduction
The International Financial Reporting Standard 9 (IFRS 9) is a critical accounting standard that governs the classification, measurement, and impairment of financial instruments. It has become especially vital for central banks to grasp the Expected Credit Loss (ECL) model in order to assess and manage credit risks with precision. The IFRS 9 standard plays a key role in how credit risk models are developed and implemented within central bank risk management frameworks.
This course is designed to equip central bank professionals with the knowledge and skills required to effectively build IFRS 9 ECL models from scratch, using real-world data. Participants will gain a comprehensive understanding of IFRS 9 and its implications on credit risk management and financial stability in central banks' operations.
Course Objectives
By the end of this course, participants will be able to:
- Understand IFRS 9 and its significance for central banks, including the impact on financial reporting and compliance with global regulations.
- Comprehend the Expected Credit Losses (ECL) model, including the three stages of credit impairment and its regulatory context.
- Prepare and assess the quality of data required for ECL modeling, addressing potential data gaps and ensuring compliance with privacy and security regulations.
- Apply key ECL modeling techniques, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models to build effective credit risk models.
- Calibrate and validate ECL models through backtesting, stress testing, and proper model governance.
- Integrate ECL models into central bank risk management frameworks to enhance credit risk management.
- Analyze real-world case studies of successful IFRS 9 ECL model implementations and their impact on financial stability.
Course Outlines
Day 1: Introduction to IFRS 9 and Expected Credit Losses (ECL)
- Overview of IFRS 9 and its significance for central banks.
- Key concepts of the Expected Credit Losses (ECL) model and its regulatory context.
- Understanding the three stages of credit impairment in the IFRS 9 framework.
- The global impact and adoption of IFRS 9, and the importance of compliance for central banks.
Day 2: Data Preparation and Quality Assessment
- Identifying relevant data sources for building ECL models.
- Techniques for data cleaning, transformation, and validation.
- Evaluating data quality and addressing data gaps to ensure IFRS 9 compliance.
- Ensuring adherence to data privacy and security regulations for accurate credit risk models.
Day 3: ECL Modeling Techniques and Approaches
- Fundamental methodologies for building ECL models.
- Using Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models to assess credit risk.
- Estimation of transition matrices and incorporating macroeconomic factors into ECL modeling.
- How to incorporate forward-looking information in the ECL models to meet IFRS 9 impairment requirements.
Day 4: Model Calibration and Validation
- Techniques for calibrating and validating ECL models with practical data.
- Methods of backtesting and stress testing to ensure model accuracy and robustness.
- Model governance and documentation, ensuring transparency and compliance.
- Effective communication with stakeholders about ECL model performance and its impact on credit risk models.
Day 5: Implementing IFRS 9 ECL Models in Central Banks
- Integration of ECL models into central banks' risk management frameworks.
- Understanding the implications of ECL on capital adequacy and financial stability in central banks.
- Leveraging ECL insights to enhance decision-making in credit risk management.
- Case studies and real-world examples of successful IFRS 9 ECL model implementations and lessons learned.
Why Attend this Course: Wins & Losses!
- Develop a solid understanding of IFRS 9 and its critical role in credit risk management for central banks.
- Learn how to build, calibrate, and validate ECL models using real-world data to comply with IFRS 9 impairment requirements.
- Gain hands-on experience in data preparation, modeling techniques, and stress testing that will directly enhance your organization's credit risk management strategy.
- Understand how to integrate ECL models into the overall risk management framework of central banks for more informed decision-making and improved financial stability.
- Learn from real-world case studies on how successful ECL model implementations have impacted the financial health of central banks.
Conclusion
As IFRS 9 becomes increasingly important for central banks worldwide, understanding and implementing the Expected Credit Loss (ECL) model is critical for ensuring financial stability and compliance with global standards. This course provides the necessary tools and techniques to build robust ECL models, calibrate them accurately, and integrate them into central bank risk management practices.
By attending this course, participants will be equipped with the knowledge to make informed decisions in credit risk management, improve the accuracy of financial reporting, and enhance the overall stability of their organizations.
