THE ADOPTION OF ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, FINANCIAL TECHNOLOGY (FINTECH) AND AUTOMATION IN BANKING SECTOR

The global banking sector is experiencing rapid transformation driven by emerging technologies such as Artificial Intelligence (AI), Machine Learning (ML), Financial Technology (FinTech), and Automation. This study aims to examine how these technologies are reshaping traditional banking operations, enhancing customer experience, optimizing risk management, and improving decision-making. Using a qualitative content analysis (QCA) approach, the research systematically reviewed academic literature, industry reports, policy documents, and corporate disclosures from 2015 to 2025 to identify key trends and institutional responses. Through open, axial, and selective coding, a conceptual framework was developed to capture the drivers, challenges, and strategic implications of technology adoption in banking. The findings reveal that adoption is primarily driven by competitive pressure, customer demand for digital services, operational efficiency, and regulatory requirements. However, barriers such as legacy systems, cybersecurity risks, talent shortages, and data governance issues persist. The study underscores that successful digital transformation requires more than technological investment—it demands organizational readiness, strategic alignment, and a human-centered approach. The insights offer valuable guidance for policymakers, financial institutions, and technology developers in promoting sustainable and inclusive digital innovation within the banking sector.