IDEAS home Printed from https://ideas.repec.org/a/taf/oaefxx/v8y2020i1p1735681.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23322039.2020.1735681
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/23322039.2020.1735681?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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.
    4. 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.
    5. 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.
    6. 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).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:oaefxx:v:8:y:2020:i:1:p:1735681. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/OAEF20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.