Artificial intelligence in banking: opportunities and risks

The article is devoted to the analysis of the opportunities and risks associated with the application of artificial intelligence in the banking sector under conditions of accelerated digital transformation of the financial system. The relevance of the study is determined by the fact that banks are increasingly integrating intelligent technologies into credit analysis, customer service, fraud detection, compliance, and internal management, while the scaling of digital solutions simultaneously intensifies cyber risks, increases requirements for data quality, raises issues of model transparency, and necessitates stronger institutional control. The research problem is related to identifying the balance between the operational advantages of AI and the risks arising from its implementation in banking activities. The aim of the study is to systematize the key areas of artificial intelligence application in banks and to assess their impact on efficiency, stability, and quality of management. The methodological framework is based on comparative analysis, a structural-functional approach, interpretation of dynamic indicators, and the generalization of international materials from International Monetary Fund, Bank for International Settlements, Organisation for Economic Co-operation and Development, and European Central Bank. The results obtained show that the implementation of AI is accompanied by increased operational efficiency, faster decision-making, expansion of digital channels, and improved accuracy of risk analysis, but at the same time increases banks’ dependence on data, algorithms, and digital infrastructure. The main conclusion is that the sustainable use of artificial intelligence in the banking sector requires a combination of technological development, a formalized governance approach, human oversight, and risk-oriented regulation.

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