Artikel
A proposed benchmark model using a modularised approach to calculate IFRS 9 expected credit loss
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.
- Language
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Englisch
- Bibliographic citation
-
Journal: Cogent Economics & Finance ; ISSN: 2332-2039 ; Volume: 8 ; Year: 2020 ; Issue: 1 ; Pages: 1-27 ; Abingdon: Taylor & Francis
- Classification
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Wirtschaft
Estimation: General
Banks; Depository Institutions; Micro Finance Institutions; Mortgages
Accounting
- Subject
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IFRS9
expected credit loss
LGD
EAD
emerging markets
impairments
- Event
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Geistige Schöpfung
- (who)
-
Schutte, Willem Daniel
Verster, Tanja
Doody, Derek
Raubenheimer, Helgard
Coetzee, Peet Jacobus
- Event
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Veröffentlichung
- (who)
-
Taylor & Francis
- (where)
-
Abingdon
- (when)
-
2020
- DOI
-
doi:10.1080/23322039.2020.1735681
- Handle
- Last update
-
10.03.2025, 11:42 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Schutte, Willem Daniel
- Verster, Tanja
- Doody, Derek
- Raubenheimer, Helgard
- Coetzee, Peet Jacobus
- Taylor & Francis
Time of origin
- 2020
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