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RESEARCH CENTER FOR INDUSTRIAL DEVELOPMENT PROBLEMS of NAS of Ukraine (KHARKIV, UKRAINE)

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Liburkina L. M.

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The Theoretical and Methodological Foundations of Credit Risk Modelling: A Trade-off Between Mathematical Accuracy, Regulatory Compliance, and Financial Inclusion
Anisimova L. A., Voronov V. I.

Anisimova, Liudmyla A., and Voronov, Volodymyr I. (2026) “The Theoretical and Methodological Foundations of Credit Risk Modelling: A Trade-off Between Mathematical Accuracy, Regulatory Compliance, and Financial Inclusion.” Business Inform 7:169–179.
https://doi.org/10.32983/2222-4459-2026-7-169-179

Section: Information Technologies in the Economy

Article is written in Ukrainian
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UDC 336.717.061.1:330.131.7

Abstract:
The relevance of the problem arises from the development of mathematical methods and computational capabilities for the assessment of individual credit risk. The prospects of implementing such methods in the risk management practice of the credit industry require a detailed examination of their compatibility with the principles of macroprudential supervision, the regulatory and legal framework, and the macroeconomic development objectives of national and global economies. Further study is also required regarding the theoretical substantiation of the underlying principles and the construction of datasets for credit risk modelling (including appropriate feature engineering) from the perspective of microeconomic theory. The aim of the article is the theoretical and methodological conceptualisation of retail credit risk modelling, focusing on the trade-off between the predictive power of non-parametric algorithms, regulatory constraints of compliance (Basel III/IV, GDPR), and policies aimed at expanding financial inclusion. The study employs methods of interdisciplinary, theoretical, critical, and comparative analysis; synthesis; conceptualisation; and formalisation. The results of the study systematise and reveal the essential microeconomic and regulatory content of empirical features used in credit risk models (such as debt burden indicators, socio-demographic characteristics, and parameters of historical payment discipline) through the lens of the life-cycle consumption hypothesis and Markov chains of debt migration. A comprehensive four-dimensional theoretical and methodological framework for model selection is developed and substantiated, integrating into a unified system the microeconomic foundation, risk modelling processes, regulatory constraints, and desired socioeconomic outcomes. It is theoretically substantiated that the use by banks of non-transparent risk management algorithms increases the risks of strict capital rationing and may induce a systemic effect of algorithmic exclusion of marginalised borrower groups, thereby stimulating the outflow of consumer demand into the unregulated shadow banking sector. A conceptual framework for selecting scoring models is formulated, enabling a balance between the accuracy and transparency of risk assessment. The practical significance of the results lies in the theoretical substantiation for the transition of financial institutions toward additive glass-box architectures, which facilitate compliance with GDPR requirements and Basel Committee standards without a substantial loss in credit risk predictive quality, thereby contributing to the long-term institutional stability of the financial system.

Keywords: credit risk assessment; banking risk management; financial inclusion; information asymmetry in lending; regulation of credit services.

Fig.: 1. Tabl.: 2. Formulae: 1. Bibl.: 24.

Anisimova Liudmyla A. – Candidate of Sciences (Physics and Mathematics), Associate Professor, Deputy Dean, Faculty of Economics, Taras Shevchenko National University of Kyiv (60 Volodymyrska Str., Kyiv, 01033, Ukraine)
Email: [email protected]
Voronov Volodymyr I. –

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