Artificial Intelligence and Fraud Prevention in Nigerian Deposit Money Banks (DMBs) - Oluwadare, Oladimeji Emanuel; Adekanmbi, John Ayodele; Omodara, Busuyi Emmanuel (Acta Universitatis Danubius. Œconomica, 2025)
This study examines the effectiveness of artificial intelligence in preventing fraud within Nigerian deposit money banks by evaluating the roles of AI adoption, investment in AI technologies, and public perception in enhancing fraud detection efficiency. This research is vital given the increasing sophistication of financial crimes in the banking sector. The study builds on prior research that recognizes AI as a transformative tool in financial risk management and fraud detection. It addresses gaps in the understanding of how different AI-related factors collectively influence fraud prevention outcomes. A cross-sectional survey design was used, targeting professionals in forensic auditing, risk management, and IT security across five leading Nigerian banks. Structured questionnaires yielded 138 valid responses. Data analysis employed descriptive statistics and multiple regression using SPSS. Findings show that AI adoption, investment in AI, and public perception all significantly enhance fraud detection efficiency. Investment in AI technologies was the most influential predictor. Correlation analysis confirmed strong positive relationships between AI-driven tools and fraud prevention measures. The study provides actionable insights for bank executives, policymakers, and IT professionals seeking to optimize AI integration for fraud risk management. The paper offers empirical evidence on the strategic role of AI in improving financial security in emerging economies.