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    South African Journal of Economic and Management Sciences

    On-line version ISSN 2222-3436Print version ISSN 1015-8812

    Abstract

    MOODLEY, Suben; VERSTER, Tanja  and  RAUBENHEIMER, Helgard. A pragmatic macroeconomic default risk adjustment in developing countries. S. Afr. j. econ. manag. sci. [online]. 2025, vol.28, n.1, pp.1-13. ISSN 2222-3436.  https://doi.org/10.4102/sajems.v28i1.5958.

    BACKGROUND: The expected credit loss (ECL) framework of International Financial Reporting Standards Foundation (IFRS) 9 typically comprises three components: probability of default (PD), loss given default (LGD) and exposure at default (EAD). Among these, PD often lacks a systematic approach for incorporating macroeconomic dynamics, particularly in the developing economies AIM: This article proposes a novel methodology for dynamically adjusting PD using a macroeconomic scalar that integrates forward-looking information SETTING: The proposed methodology is illustrated on datasets from Kenya and Mauritius to validate its applicability METHOD: The methodology consists of five steps: (1) research and planning; (2) data preparation; (3) model development; (4) calculation of the scalar; and (5) model validation. Comparative analysis is conducted using multiple regression, generalised linear models (Logit, Probit), and machine learning techniques such as neural networks, random forests, and gradient boosting. Model performance is assessed using key summary statistics and validation metrics RESULTS: The proposed macroeconomic scalar effectively adjusted PD within the ECL model for the Kenya and Mauritius datasets. Each modelling approach contributed insights, demonstrating the scalar's ability to improve ECL predictions CONCLUSION: Integrating a macroeconomic scalar into the ECL model offers a robust method for incorporating forward-looking information, improving PD accuracy that can account for uncertainty, volatility and sparse data characteristic of developing economies CONTRIBUTION: This article provides a systematic approach for adjusting PD in ECL models using macroeconomic data offering a scalable solution. Additionally, we provide practical guidelines and step-by-step recommendations for practitioners seeking to implement macroeconomic adjustments in PD estimation

    Keywords : probability of default; PD; macro-economic PD adjustment; IFRS 9 expected credit loss; ECL; machine learning in credit risk; developing countries.

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