Analytical assessment of economic effects of artificial intelligence implementation in the banking sector

Abstract

The digitalization of the financial sector is accompanied by the active implementation of intelligent data-processing algorithms that transform approaches to managing banking processes and pricing financial services. Increased competition and growing requirements for operational efficiency necessitate the quantitative assessment of the economic outcomes of intelligent systems in banking activities. The aim of the study is to identify and systematize the economic effects of artificial intelligence technologies in the banking sector, focusing on their impact on costs, revenues, risks, and efficiency. Methods. The study applies methods of economic analysis, comparison, and generalization of scientific findings, as well as elements of economic and statistical evaluation. A logical-structural framework is used to classify economic effects and group them by impact areas. The analysis covers the application of intelligent systems in lending, risk management, customer service, and internal banking operations. Results. The findings indicate that the use of intelligent algorithms reduces operational costs by automating routine processes, improves the accuracy of creditworthiness assessments, and decreases default rates. An increase in revenues for banking institutions has been identified, driven by the personalization of financial products and improvements in customer experience. Increased labor productivity is substantiated through reduced transaction processing time and faster decision-making. The implementation of intelligent systems contributes to lowering information asymmetry and increasing transparency of financial operations. At the same time, additional costs related to technology integration, cybersecurity, and infrastructure modernization are identified. Conclusions. The economic effects of artificial intelligence implementation are complex and manifest in improved efficiency, increased profitability, and optimized risk management in banking activities. The results confirm the feasibility of integrating intelligent technologies to enhance the competitiveness of financial institutions. Further research should focus on developing models to quantify the integrated economic impact and on evaluating the long-term consequences of digital transformation in the banking sector.