Artificial Intelligence Investment, Accounting Recognition and Return on Assets of Deposit Money Banks in Nigeria
DOI:
https://doi.org/10.64137/31079423/IJEBMR-V2I4P103Keywords:
Artificial Intelligence Investment, Accounting Recognition, Return On Assets, Deposit Money Banks, Panel AnalysisAbstract
This study examines the relationship between Artificial Intelligence (AI) investment, accounting recognition and return on assets (ROA) of deposit money banks in Nigeria over 2009-2025. Using a panel dataset of 204 bank-year observations, the study estimates fixed-effects models with bank and year fixed effects and standard errors clustered at the bank level. AI investment is measured as AI-related expenditure relative to total assets, while accounting recognition is measured as a recognition score reflecting the extent to which AI-related expenditure is identified and reported in the financial statements. The results show that AI investment intensity has a positive but statistically insignificant association with ROA. Accounting recognition is positively and significantly associated with ROA in the baseline model, although this relationship becomes insignificant when the interaction between AI investment and recognition is introduced. The interaction coefficient is positive but statistically insignificant, indicating that the data do not support the proposition that accounting recognition strengthens the relationship between AI investment and bank profitability. The study contributes by separating AI investment from its accounting recognition and testing whether recognition moderates the AI-ROA relationship. It offers an accounting-based perspective on the economic consequences of technological investment in an emerging banking market, while highlighting the need for clearer disclosure and recognition guidance for AI-related resources. The findings are relevant to bank managers, auditors, regulators and standard-setters concerned with the financial reporting and performance implications of AI adoption.
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