How to Model and Validate Expected Credit Losses for IFRS9 and CECL A Practical Guide with Examples Worked in Excel, R, and SAS
Auteur : Bellini Tiziano
How to Model and Validate Expected Credit Losses for IFRS9 and CECL: A Practical Guide with Examples Worked in Excel, R, and SAS covers a hot topic in risk management. The IFRS9 expected credit loss accounting principle (going live in 2018) and the US CECL standard (going live in 2020) require creditors to adopt a new perspective in assessing their credit exposures. The book explores the best modeling process, including the most common statistical techniques used in estimating expected credit losses. A practical Excel-based approach encourages non-technical professionals to grasp the key concepts required to understand, challenge and validate these models.
Additionally, the reader with broader modeling experience will benefit from a more technical dissertation accompanied with cases worked in SAS and R (the software packages most commonly used by credit risk managers to develop their models).
- Offers a broad survey that explains which models work best for mortgage, small business, cards, commercial real estate, commercial loans and other credit vehicles
- Concentrates on specific aspects of the model, with each chapter building upon earlier chapters
- Provides a non-technical approach to enable readers to perform the review, validation and audit of models
2. How to Build a Probability of Default (PD) Lifetime Curve
3. Exposure at default (EAD) and Behavioural Modelling
4. Loss Given Default
5. Scenario Analysis
6. IFRS 9 Staging Allocation
7. Expected Credit Loss (ECL) vs. Credit Portfolio Modelling
Upper-division undergraduates, graduate students, and professionals working in economic modelling and statistics.
Date de parution : 01-2019
Ouvrage de 200 p.
Disponible chez l'éditeur (délai d'approvisionnement : 14 jours).
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