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Artificial Intelligence in the Financial Sector: Economic Efficiency of Automated Risk Management
Dumchykov M. A., Dmitrishyn D. M., Bohachenko M. M.

Dumchykov, Mykhailo A., Dmitrishyn, Dmytro M., and Bohachenko, Maksym M. (2025) “Artificial Intelligence in the Financial Sector: Economic Efficiency of Automated Risk Management.” Business Inform 12:38–38.
https://doi.org/10.32983/2222-4459-2025-12-38-38

Section: Finance, Money Circulation and Credit

UDC 336.71:004.8:005.334:330.131.7

Abstract:
The article examines the economic efficiency of applying artificial intelligence in automated risk-management systems within the financial sector of Ukraine, considered against the backdrop of global digitalisation trends. The relevance of this topic is driven by the rapid development of financial technologies, the increasing complexity of risks in the banking industry, and the growing need to enhance the effectiveness of managerial decision-making. It is emphasised that the digitalisation of the financial sector has acquired particular significance during wartime, when traditional risk-management systems have proven insufficiently flexible for rapid responses to constantly evolving threats. The study highlights that artificial intelligence – owing to its capacity to process large data volumes, detect hidden patterns, and forecast risk events in real time – has become a critically important instrument for ensuring financial stability. The scientific novelty of the research lies in its comprehensive analysis of the economic effects resulting from the adoption of AI-based technologies in the risk-management practices of Ukrainian financial institutions, with due consideration of the international experience of leading global banks. The article systematises approaches to assessing the effectiveness of AI-driven solutions, identifies the specific challenges of the Ukrainian banking system, and proposes practical recommendations for optimising the implementation of intelligent systems. The results demonstrate that the integration of artificial intelligence into financial risk management leads to a 15–30% reduction in operational costs, a 25–40% increase in the accuracy of credit-risk forecasting, and a reduction in fraud-detection time to a matter of seconds – compared with hours under traditional approaches. The analysis of risk dynamics in Ukraine’s financial sector reveals an increase in credit risks under martial-law conditions, as well as a rise in cyberthreats and operational risks. At the same time, the Ukrainian banking sector has shown high adaptability: according to the National Bank of Ukraine, banks are actively implementing digital solutions, which has enabled them to maintain stability even under extreme circumstances.

Keywords: artificial intelligence, financial sector, risk management, automation, credit risk, operational efficiency, digitalisation, financial stability.

Tabl.: 1. Bibl.: 24.

Dumchykov Mykhailo A. – Doctor of Sciences (Law), Associate Professor, Associate Professor, Department of Criminal Law Disciplines and Legal Proceedings, Educational and Scientific Institute of Law of Sumy State University (59 Petropavlivska Str., Sumy, 40000, Ukraine)
Email: [email protected]
Dmitrishyn Dmytro M. – Postgraduate Student, Department of Financial Technologies and Entrepreneurship, Sumy State University (116 Kharkivska Str., Sumy, 40007, Ukraine)
Email: [email protected]
Bohachenko Maksym M. – Postgraduate Student, Department of Financial Technologies and Entrepreneurship, Sumy State University (116 Kharkivska Str., Sumy, 40007, Ukraine)
Email: [email protected]

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