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Abstract: 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. DOI: https://doi.org/10.51505/IJEBMR.2025.9802 |
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