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Development of Rating Models under IFRS 9

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  • Ioan-Codruț ȚURLEA

    (Bucharest University of Economic Studies)

Abstract

Before the release of the IFRS 9 standard Financial Instruments in 2014, the development of a rank ordering mechanism was mostly known through the Basel capital accords requirements for the computation of regulatory capital, as well as the economic capital models used for the estimation of internal capital needs. Most institutions would have been relying on application scorecards for ranking clients at application and assess their suitability to be granted a loan in line with their own risk tolerance. However, only a small number of institutions would have relied on behavioral scorecards. Both the Basel III Internal Rating Based Approach (IRBA) and IFRS 9 are principle based and offer their users a variety of modelling approaches. Hence, financial institutions are allowed to implement their own rating models. However, under IRBA the rating system must meet specific minimum requirements which are not required under IFRS 9. The article focuses on highlighting a variety of rating methods and systems applicable under the IFRS 9 framework. Hence, it presents a series of statistical and non-statistical models for building and estimating the rating system. Furthermore, the benefits and drawbacks are presented for each approach. The paper concludes with an analysis of the models under the IFRS 9 framework.

Suggested Citation

  • Ioan-Codruț ȚURLEA, 2021. "Development of Rating Models under IFRS 9," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), vol. 2(7), pages 64-72, July.
  • Handle: RePEc:ahd:journl:v:2:y:2021:i:7:p:64-72
    DOI: 10.37945/cbr.2021.07.07
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    References listed on IDEAS

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    1. Zoltán Novotny-Farkas, 2016. "The Interaction of the IFRS 9 Expected Loss Approach with Supervisory Rules and Implications for Financial Stability," Accounting in Europe, Taylor & Francis Journals, vol. 13(2), pages 197-227, May.
    2. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    3. 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.
    4. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    5. Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 225-238.
    6. Gunther Gebhardt & Zoltan Novotny-Farkas, 2011. "Mandatory IFRS Adoption and Accounting Quality of European Banks," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(3-4), pages 289-333, April.
    7. Christopher Nobes, 2013. "The continued survival of international differences under IFRS," Accounting and Business Research, Taylor & Francis Journals, vol. 43(2), pages 83-111, April.
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    Cited by:

    1. Douw Gerbrand Breed & Niel van Jaarsveld & Carsten Gerken & Tanja Verster & Helgard Raubenheimer, 2021. "Development of an Impairment Point in Time Probability of Default Model for Revolving Retail Credit Products: South African Case Study," Risks, MDPI, vol. 9(11), pages 1-22, November.

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    More about this item

    Keywords

    IFRS 9; Basel approach; credit risk; assessment; strategy;
    All these keywords.

    JEL classification:

    • M40 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - General
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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