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A proposed benchmark model using a modularised approach to calculate IFRS 9 expected credit loss

Author

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  • Willem Daniel Schutte
  • Tanja Verster
  • Derek Doody
  • Helgard Raubenheimer
  • Peet Jacobus Coetzee
  • David McMillan

Abstract

The objective of this paper is to develop a methodology to calculate expected credit loss (ECL) using a transparent-modularised approach utilising three components: probability of default (PD), loss given default (LGD) and exposure at default (EAD). The proposed methodology is described by first providing a methodology to calculate the marginal PD, then the methodology for calculating the marginal recovery rates and resulting LGD, and lastly a methodology to calculate the EAD. These three components are combined to calculate the ECL in an empirical style. In markets where sophisticated IFRS9 models are developed, our proposed methodology can be used as in two settings: either as a benchmark to compare newly developed IFRS9 models, or, in markets where limited resources or technological sophistication exists, our methodology can be used to calculate ECL for IFRS9 purposes. This paper includes two such comparative studies to illustrate how our proposed methodology can be used as a benchmark for a newly developed IFRS9 model based on an emerging country’s unsecured and secured retail banking portfolio. This paper is, in essence, a step-by-step implementation guide of the proposed IFRS 9 methodology to calculate ECL as well as the use of such a model as a benchmark.

Suggested Citation

  • Willem Daniel Schutte & Tanja Verster & Derek Doody & Helgard Raubenheimer & Peet Jacobus Coetzee & David McMillan, 2020. "A proposed benchmark model using a modularised approach to calculate IFRS 9 expected credit loss," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1735681-173, January.
    • Handle: RePEc:taf:oaefxx:v:8:y:2020:i:1:p:1735681
    DOI: 10.1080/23322039.2020.1735681
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    Citations

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    Cited by:

    1. Frank Ranganai Matenda & Mabutho Sibanda & Eriyoti Chikodza & Victor Gumbo, 2021. "Determinants of corporate exposure at default under distressed economic and financial conditions in a developing economy: the case of Zimbabwe," Risk Management, Palgrave Macmillan, vol. 23(1), pages 123-149, June.
    2. Son Tran & Peter Verhoeven, 2021. "Kelly Criterion for Optimal Credit Allocation," JRFM, MDPI, vol. 14(9), pages 1-16, September.
    3. Douw Gerbrand Breed & Jacques Hurter & Mercy Marimo & Matheba Raletjene & Helgard Raubenheimer & Vibhu Tomar & Tanja Verster, 2023. "A Forward-Looking IFRS 9 Methodology, Focussing on the Incorporation of Macroeconomic and Macroprudential Information into Expected Credit Loss Calculation," Risks, MDPI, vol. 11(3), pages 1-16, March.
    4. Salazar, Yadira & Merello, Paloma & Zorio-Grima, Ana, 2023. "IFRS 9, banking risk and COVID-19: Evidence from Europe," Finance Research Letters, Elsevier, vol. 56(C).
    5. Morne Joubert & Tanja Verster & Helgard Raubenheimer & Willem D. Schutte, 2021. "Adapting the Default Weighted Survival Analysis Modelling Approach to Model IFRS 9 LGD," Risks, MDPI, vol. 9(6), pages 1-17, June.
    6. 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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