ARTIFICIAL INTELLIGENCE AND BANK PERFORMANCE: AN EMPIRICAL ANALYSIS OF ACCESS, FIRST, AND UBA BANKS IN NIGERIA

Abstract

This paper will analyze how the adoption of artificial intelligence (AI) affects the performance of Access Bank, First Bank, and UBA in Nigeria. The quantitative research methodology was applied to gather data on 150 employees immediately engaged in AI operations and to support it with a financial trail of 2018-2023. Relationships between AI adoption dimensions, which comprise operational efficiency, customer engagement, and risk management, and measures of bank performance, which include ROA, ROE, and NIM, were determined using descriptive and inferential statistics, including multiple regression analysis. Results indicate that operational efficiency impacts on financial performance most positively, then customer engagement and risk management. UBA showed a better performance, and this is evidence of its comprehensive AI integration plan. The paper concludes that AI has a huge impact on the performance of a bank and its competitive advantage. It is suggested to focus on AI-based workflow optimization, customer-focused solutions, and risk management systems and invest in employee training and favorable regulatory frameworks.