Effect of Artificial Intelligence on the Financial Performance of Deposit Money Banks in Nigeria

This study investigates the effect of Artificial Intelligence (AI) on the financial performance of deposit money banks in Nigeria, using Earnings Per Share (EPS) as the primary measure of profitability. The research focuses on three AI-related indicators: Software Book Value (SBV), AI-Related Keyword Disclosures (AKD), and Software Expenses Disclosed (SED). Descriptive statistics reveal substantial disparities in AI software investments (SBV), with some banks reporting significant asset values and others showing impairments or negative values. Keyword disclosures and software expense reporting were more uniformly distributed across banks. Using a fixed effects regression model, the study found that AI-related variables collectively have a statistically significant impact on EPS (F-statistic = 18.40, p < 0.0000), explaining 72.44% of the variation in profitability. Among the individual variables, SBV exhibited a positive and statistically significant effect on EPS (p < 0.05), indicating that higher tangible AI investments enhance financial performance. However, AKD and SED showed no significant individual influence on EPS, suggesting that superficial or nominal AI engagements do not translate into improved earnings. The study concludes that the financial performance of Nigerian deposit money banks is significantly enhanced by actual AI integration, rather than by disclosure or reporting alone. It recommends that banks increase tangible AI investments, embed AI into core operational areas, and align disclosures with substantive implementation. Regulatory and industry support should focus on fostering genuine adoption, while capacity building in AI expertise should be prioritized to ensure sustainable performance improvements in the banking sector.