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Methodological approaches to assessing borrowers’ creditworthiness using artificial intelligence
https://doi.org/10.34020/2073-6495-2026-2-207-219
Abstract
The article examines the impact of digital transformation on the banking sector through the lens of the introduction of artificial intelligence technologies. The scientific novelty lies in the substantiation of the author’s methodological approach to assessing borrowers’ creditworthiness, based on the integration of explicable AI (XAI) algorithms and analysis of behavioral patterns from open digital sources. Barriers and risks of implementation have been identified, and an algorithm for minimizing regulatory restrictions has been proposed.
Supporting agencies: The study was carried out within the framework of priority area 7.5.1.4. of the research plan of the Institute of Economics, Industrial Problems and Problems of the Siberian Branch of the Russian Academy of Sciences for 2026, project 5.6.1.5. (0260-20260010) Integration and interaction of mesoeconomic systems and markets in Russia and its eastern regions: structures, institutions, regulation.
About the Authors
А. М. Vyzhitovich
Novosibirsk State University of Economics and Management;
Siberian Institute of Management – branch of the Russian Academy
of National Economy and Public Administration under the President
of the Russian Federation;
Institute of Economics and Industrial Engineering of the Siberian Branch
of Russian Academy of Sciences
Russian Federation
Russian Federation
Vyzhitovich Alexander M. - Candidate of Economic Sciences, Associate Professor, Department of Financial Market and Financial Institutions, Novosibirsk State University of Economics and Management, Department of Economics and Entrepreneurship, Siberian Institute of Management branch of the Russian Academy of National Economy and Public Administration under the President of the Russian Federation, Research Fellow, Department of Analysis and Forecasting of Sectoral Systems Development, Institute of Economics and Industrial Engineering of the Siberian Branch of Russian Academy of Sciences
Novosibirsk
A. D. Kirillov
Novosibirsk State University of Economics and Management
Russian Federation
Russian Federation
Kirillov Alexander D. - Master’s Student
Novosibirsk
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Review
For citations:
Vyzhitovich А.М., Kirillov A.D. Methodological approaches to assessing borrowers’ creditworthiness using artificial intelligence. Vestnik NSUEM. 2026;(2):207-219. (In Russ.) https://doi.org/10.34020/2073-6495-2026-2-207-219
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