Artificial Intelligence as a Catalyst for Bank Performance: Evidence from Access Bank, Nigeria

Abstract

The performance of Nigerian banks is increasingly challenged by inefficiencies in service delivery, fraud risks, and the limitations of traditional credit management systems. This study examined the role of Artificial Intelligence (AI) as a catalyst for bank performance, with specific reference to Access Bank Plc, Nigeria. Four dimensions of AI deployment were investigated: AI-powered customer service, AI-driven fraud detection and prevention, AI based credit scoring and risk assessment, and AI-enabled process automation. The study was anchored on the Technology Acceptance Model and the Resource-Based View. A descriptive survey design was adopted, and primary data were collected from the employees of Access Bank in Abuja using a structured five-point Likert questionnaire administered across four departments. Data were analysed using descriptive statistics, while one-sample t-tests against the criterion mean of 3.0 were used to test the hypotheses at the 5 per cent level of significance. The results showed that all four AI dimensions recorded grand mean scores well above the criterion mean, with customer service (4.17), fraud detection (4.18), credit scoring (4.14), and process automation (4.21) each differing significantly from the benchmark. The four null hypotheses were accordingly rejected, indicating that AI deployment significantly enhances both the financial and non-financial performance of the bank. The study recommends deeper integration of AI across core banking operations, sustained staff capacity development, stronger data governance and ethical AI frameworks, and strategic collaboration with fintech firms. The findings provide firm-level empirical evidence on the transformative role of AI in an emerging market banking context.