Artificial Intelligence Adoption and Operational Efficiency of Deposit Money Banks
Ayobaye Salemcity (),
Olabode Olutola Aiyesan (),
Adewumi Tobi Orina () and
Henry Adelakun Adinlewa ()
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Ayobaye Salemcity: Adekunle Ajasin University
Olabode Olutola Aiyesan: Adekunle Ajasin University
Adewumi Tobi Orina: Adekunle Ajasin University
Henry Adelakun Adinlewa: Afe Babalola University
The Journal of Accounting and Management, 2025, issue 2(15), 190-204
Abstract:
Understanding the need for taking competitive advantage by organizations and staying abreast of innovations has contributed to the adoption of artificial intelligence (AI) by some deposit money banks (DMBs) in Nigeria. Objectives: This study examines the effect of AI on cost reduction and profitability of DMBs in Nigeria. Prior works show that operating efficiency cannot not be fully achieved in traditional banking. Approach: the study aims to investigate how AI can boost productivity, cut expenses, and improve operational efficiency in deposit money banks in Nigeria. To achieve its objectives, the study employs a quantitative approach by utilizing multivariate models for the analysis of the panel data gathered. The study establishes the need for AI in improving operational efficiency and financial performance in the banking sector. Results reveal that AI investments significantly contribute to cost efficiency, which, in turn, enhances profitability in Nigerian DMBs. Implications: The study establishes that AI-driven automation and predictive analytics optimize banking operations by reducing operational costs while improving service delivery. Value: The study highlights the strategic significance of AI in banking, proposing empirical evidence for academics and researchers, guiding bank administrators and policymakers on AI investment for effectiveness and financial sustainability.
Keywords: artificial intelligence; operational efficiency; cost reduction; profitability; artificial intelligence investments (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:dug:jaccma:y:2025:i:2:p:190-204
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