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

Author

Listed:
  • Achim Luminita-Georgiana

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Mitoi Elena

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Turlea Ioan-Codrut

    (Bucharest University of Economic Studies, Bucharest, Romania)

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.

Suggested Citation

  • Achim Luminita-Georgiana & Mitoi Elena & Turlea Ioan-Codrut, 2021. "A methodological approach to developing and validating IFRS 9 -LGD parameters," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 15(1), pages 683-694, December.
  • Handle: RePEc:vrs:poicbe:v:15:y:2021:i:1:p:683-694:n:6
    DOI: 10.2478/picbe-2021-0064
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    References listed on IDEAS

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    1. Patrick Bolton & Xavier Freixas & Joel Shapiro, 2012. "The Credit Ratings Game," Journal of Finance, American Finance Association, vol. 67(1), pages 85-112, February.
    2. Michel Magnan & Garen Markarian, 2011. "Accounting, Governance and the Crisis: Is Risk the Missing Link?," European Accounting Review, Taylor & Francis Journals, vol. 20(2), pages 215-231.
    3. Julien Azzaz & Stéphane Loisel & Pierre-E. Thérond, 2015. "Some characteristics of an equity security next-year impairment," Review of Quantitative Finance and Accounting, Springer, vol. 45(1), pages 111-135, July.
    4. Pool, Sebastiaan & de Haan, Leo & Jacobs, Jan P.A.M., 2015. "Loan loss provisioning, bank credit and the real economy," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 124-136.
    5. Cheng, Mei & Neamtiu, Monica, 2009. "An empirical analysis of changes in credit rating properties: Timeliness, accuracy and volatility," Journal of Accounting and Economics, Elsevier, vol. 47(1-2), pages 108-130, March.
    6. Yang, Bill Huajian, 2017. "Point-in-time PD term structure models for multi-period scenario loss projection: Methodologies and implementations for IFRS 9 ECL and CCAR stress testing," MPRA Paper 76271, University Library of Munich, Germany.
    7. Wolfgang Reitgruber, 2014. "Methodological thoughts on expected loss estimates for IFRS 9 impairment: hidden reserves, cyclical loss predictions and LGD backtesting," Papers 1411.4265, arXiv.org, revised Aug 2015.
    8. Mary Barth & Wayne Landsman, 2010. "How did Financial Reporting Contribute to the Financial Crisis?," European Accounting Review, Taylor & Francis Journals, vol. 19(3), pages 399-423.
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