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A methodological approach to developing and validating IFRS 9 -LGD parameters Cover

A methodological approach to developing and validating IFRS 9 -LGD parameters

Open Access
|Dec 2021

Abstract

Since the introduction of the advanced internal rating based approach through the Basel framework, financial institutions and regulators have been dealing with the increased complexity of Loss Given Default models. The development and validation of the parameters has become more formalized and standardized as more prescriptive regulations and guidelines have been published by the European Parliament, European Central Bank and European Banking Authority. Furthermore, following the introduction of IFRS 9 in January 2018 even more emphasis is put on the development and validation as the standard poses new challenges to the way models are designed, developed, validated and increased complexity through the introduction of the lifetime and forward-looking adjustments. This paper address the challenges faced by banks and regulators when assessing and validation the IFRS 9 - Loss Given Default parameters and framework. Moreover, it describes a non-exhaustive list of tests that can be performed to establishing the accuracy, discrimination power and stability of the Loss Given Default outputs. It is important that the framework built around the modeling, development and validation process allows models to be easily integrated in the management framework in a flexible manner that can facilitate any changes that must be brought to the models. Hence, this paper outlines a non-exhaustive list of quantitative validation tests considered would satisfy the requirements of the IFRS 9 standard.

Language: English
Page range: 683 - 694
Published on: Dec 31, 2021
Published by: The Bucharest University of Economic Studies
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year

© 2021 Luminita-Georgiana Achim, Elena Mitoi, Ioan-Codrut Turlea, published by The Bucharest University of Economic Studies
This work is licensed under the Creative Commons Attribution 4.0 License.