IFRS9 Expected Credit Loss Model Development and Validation

📚 Course Title: IFRS9 Expected Credit Loss Model Development and Validation

🚀 Course Headline: Dive into the World of IFRS9 with R Programming! Master the Art of Modeling and Validating Expected Credit Losses.

About This Course:

Embark on a comprehensive journey through the complex realm of provisioning under the International Financial Reporting Standards (IFRS) with a focus on IFRS 9. This course is designed for finance professionals, accountants, and analysts who wish to understand and master the Expected Credit Loss (ECL) model development and validation process specifically using R programming.

Course Overview:

🚀 Introduction to Provisioning and IFRS9:

• Understand the evolution of provisioning practices.
• Grasp the principles behind IFRS 9, the latest standard for accounting for financial instruments.
• Explore the shift from an incurred loss model to a forward-looking expected credit loss model.

📊 Deep Dive into Stage Allocation Process:

• Learn the ins and outs of IFRS 9's stage allocation process.
• Determine the appropriate accounting treatment for financial assets at each stage.

🔍 Frameworks Behind PD, LGD, and EAD:

• Get to grips with the Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD).
• Understand how these parameters align with IFRS 9 requirements.

💡 Hands-On R Programming:

• Engage in practical exercises using R programming to estimate the Expected Credit Loss (ECL).
• Model ECL for one-year horizons and over a lifetime horizon.
• Classify credits into stage 1, stage 2, and stage 3 based on the changes in credit risk.

📈 Modeling ECL from Scratch:

• Learn the different modeling techniques for estimating ECL.
• Explore both Generalized Linear Models (GLMs) and Machine Learning (ML) approaches with a step-by-step guide using R.

🔐 Understanding the Impact of ECL on Regulatory Capital:

• Analyze how ECL affects regulatory capital and ratios.
• Assess the implications for banks and financial institutions.

✅ Scarce Data Modeling Techniques:

• Address challenges in low default portfolios and scarce data sets.
• Develop strategies to handle limited information effectively.

🎓 Model Validation and Sensitivity Analysis:

• Master the validation process of your ECL models.
• Conduct sensitivity analysis to understand model robustness and potential areas for improvement.

Learning Outcomes:

By the end of this course, you will be equipped with the knowledge and tools necessary to:

• Develop a comprehensive understanding of IFRS 9 and its principles.
• Apply practical ECL modeling techniques using R programming.
• Validate your models effectively and interpret results accurately.
• Understand the impact of ECL on financial statements and comply with regulatory requirements.

Why Take This Course?

• Practical Application: Learn by doing with hands-on exercises in R.
• Expert Guidance: Benefit from Subhashish Ray's deep expertise in IFRS 9, modeling, and R programming.
• Real-World Relevance: Gain insights that are directly applicable to your job role in finance or accounting.
• Community Engagement: Join a community of like-minded professionals and expand your professional network.

🚀 Take the Next Step: Enhance your skills, stay ahead of the curve, and contribute to the success of your organization by mastering IFRS 9 ECL modeling with R programming. Enroll in this course today!

Whether you're looking to solidify your current expertise or expand into new areas, this course is tailored to help you achieve your professional goals. Join us and transform your understanding of financial modeling with IFRS 9! 🌟