ISSN (Online): 2321-3418
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Economics and Management
Open Access

Artificial Intelligence, Automation, and Data-Driven Decision-Making in Enhancing Banking Efficiency and Business Process Optimisation in Nigeria

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DOI: 10.18535/ijsrm/v14i01.em13· Pages: 10312-10328· Vol. 14, No. 01, (2026)· Published: January 23, 2026
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Abstract

This study investigates the role of Artificial Intelligence (AI), automation, and data-driven decision-making in enhancing banking efficiency and business process optimization in Nigeria. The research employed a predictive research design, targeting 78,000 banking personnel, with a purposive sample of 444 respondents from top-tier commercial banks across six geopolitical zones. Data were collected using a validated and reliable questionnaire (Cronbach’s α = 0.82), and analyzed through descriptive statistics and multiple regression to examine the predictive impact of AI functions on banking efficiency. Findings reveal that AI-driven automation, digitalization, and data-based decision-making significantly improve operational efficiency, customer service, risk management, and workflow optimization. Regression results indicated that AI functions collectively explain 62% of the variance in banking efficiency (R² = 0.62, F = 143.18, p < 0.001), with automation and digitalization having the strongest predictive effect. The study recommends wider AI adoption, infrastructural support, and regulatory facilitation to maximize banking performance and competitive advantage in Nigeria.

Keywords

Artificial Intelligence AIAutomationBanking EfficiencyBusiness Process OptimizationData-Driv

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Author details
Uzoamaka CHIKELUBA
Doctor of Business Management, Ballsbridge University, Commonwealth of Dominica, West Indies
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Sunday Ade Bello
Visiting Professor of Management, Entrepreneurship and Leadership; Ballsbridge University, Commonwealth of Dominica, West Indies
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