A Forward-Looking IFRS 9 Methodology, Focussing on the Incorporation of Macroeconomic and Macroprudential Information into Expected Credit Loss Calculation

Douw Gerbrand Breed, Jacques Hurter, Mercy Marimo, Matheba Raletjene, Helgard Raubenheimer (), Vibhu Tomar and Tanja Verster
Additional contact information
Douw Gerbrand Breed: Centre for Business Mathematics and Informatics, North-West University, Private Bag X6001, Potchefstroom 2520, South Africa
Jacques Hurter: Independent Researcher, 116 Cockspur Road, Roodepoort 1709, South Africa
Mercy Marimo: Independent Researcher, P.O. Box 613 Heliopolis, Cairo 11757, Egypt
Matheba Raletjene: Independent Researcher, 108 Bateleur Str., Midrand 1628, South Africa
Helgard Raubenheimer: Centre for Business Mathematics and Informatics, North-West University, Private Bag X6001, Potchefstroom 2520, South Africa
Vibhu Tomar: Independent Researcher, DLF Cyber City, Gurgaon 122002, India
Tanja Verster: Centre for Business Mathematics and Informatics, North-West University, Private Bag X6001, Potchefstroom 2520, South Africa

Risks, 2023, vol. 11, issue 3, 1-16

Abstract: The International Financial Reporting Standard (IFRS) 9 relates to the recognition of an entity’s financial asset/liability in its financial statement, and includes an expected credit loss (ECL) framework for recognising impairment. The quantification of ECL is often broken down into its three components, namely, the probability of default (PD), loss given default (LGD), and exposure at default (EAD). The IFRS 9 standard requires that the ECL model accommodates the influence of the current and the forecasted macroeconomic conditions on credit loss. This enables a determination of forward-looking estimates on impairments. This paper proposes a methodology based on principal component regression (PCR) to adjust IFRS 9 PD term structures for macroeconomic forecasts. We propose that a credit risk index (CRI) is derived from historic defaults to approximate the default behaviour of the portfolio. PCR is used to model the CRI with the macroeconomic variables as the set of explanatory variables. A novice all-subset variable selection is proposed, incorporating business decisions. We demonstrate the method’s advantages on a real-world banking data set, and compare it to several other techniques. The proposed methodology is on portfolio-level with the recommendation to derive a macroeconomic scalar for each different risk segment of the portfolio. The proposed scalar is intended to adjust loan-level PDs for forward-looking information.

Keywords: probability of default; IFRS 9; expected credit loss; macroeconomic; macroprudential; PCR (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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