WAYS OF USING ARTIFICIAL INTELLIGENCE IN THE DEVELOPMENT OF BANKING SERVICES

Abstract

This study analyzes the influence of Artificial Intelligence (AI) on the transformation and advancement of modern banking services in the context of accelerating digitalization and growing global financial competition. As banks shift toward data-driven operating models, AI technologies—such as machine learning, natural language processing, and predictive analytics—have become essential tools for innovation, efficiency improvement, and customer-oriented service delivery.

The research investigates the application of AI in core banking areas, including credit risk evaluation, fraud detection, customer relationship management, investment portfolio optimization, and automation of internal processes. Particular attention is given to the use of alternative data sources and advanced analytics, which improve the accuracy and inclusiveness of financial decisions. According to data from the World Bank and the Bank for International Settlements, AI implementation can reduce operational expenses by 20–30%, enhance risk management, and significantly improve customer satisfaction through personalized services.

The paper also discusses major challenges associated with AI adoption in banking, such as data security issues, regulatory limitations, ethical concerns, algorithmic bias, and high implementation costs. The necessity of establishing strong governance and regulatory mechanisms is emphasized to ensure safe and transparent AI usage in financial systems.

Finally, a conceptual framework is proposed for integrating AI into banking operations, focusing on the interaction between technology, human capital, regulation, and strategic management. The study contributes to understanding digital transformation in banking and provides practical recommendations for policymakers and financial institutions.