Impact of Artificial Based Forensic Accounting on Cyber Fraud in Deposit Money Banks in Nigeria

Abstract

This study examines Artificial Intelligence (AI) based forensic accounting and its implications for detecting and preventing high-level cyber frauds in the Nigerian banking sector. Despite the growing adoption of AI-driven systems, Nigerian banks continue to record significant financial losses, raising concerns about the effectiveness of these technologies. Survey researchwas employed, 250 forensic accountants, auditors, IT specialists, and compliance officers across selected banks with respect to adapted questionnaire. Data were analyzed using descriptive statistics, regression analysis, through thematic coding. Findings reveal that AI-based forensic accounting systems exhibit notable flaws, including false positives and negatives, algorithmic bias, lack of transparency, and infrastructural limitations. While respondents acknowledged improvements in fraud detection speed and coverage, statistical results indicated no significant impact of AI on detection and prevention effectiveness. The study concludes that AI, though promising, cannot independently guarantee robust fraud management without human expertise, regulatory support, and infrastructural enhancement. It recommends hybrid approaches integrating AI with forensic accounting judgment, improved data governance, capacity building, and regulatory reforms. The study contributes to forensic accounting and financial technology literature by highlighting the contextual limitations of AI adoption in emerging economies.