IMPACT OF FORENSIC ACCOUNTING TECHNIQUES ON FRAUD PREVENTION OF LISTED DEPOSIT MONEY BANKS IN NIGERIA.

This study was carried out the impact of forensic accounting techniques on fraud prevention in the listed Deposit Money Banks in Nigeria. The objectives were to; examine the relationship between data mining techniques and fraud prevention in Nigerian DMBs, investigate the relationship between digital forensic and fraud prevention in listed banks and examine the effectiveness of litigation expertise in detecting and preventing fraud in DMBs. The study made used survey questionnaires for primary data and documentary analysis enhances used methodological triangulation. Ordinary least square method (OLS) of multiple regressions and multiple regressions was employed in analyzing data collected to determine the impact of forensic accounting technique on fraud prevention among listed deposit money banks in Nigeria. The study adopted a convenience sampling technique to select respondents who have direct involvement with fraud prevention systems and forensic accounting technique. The study reveals that insightful patterns regarding the application of forensic accounting techniques and their influence on fraud prevention in Nigerian deposit money banks. The overall response rate of 91.2% indicates a high level of engagement from the respondents, suggesting that the results are robust, reliable, and representative of the banking sector. The study also indicates that first bank recorded the highest response rate of 13.60%, while fidelity bank had the lowest at 11.40%, demonstrating relatively uniform cooperation across institutions and supporting the credibility of subsequent analyses is because of possible financial losses that could result from none payment of loans, which makes the business of banking risky. The study therefore, recommends that Nigerian deposit money banks should prioritize the development of litigation capabilities by training forensic accountants and legal teams in evidence handling, court procedures, and asset recovery as well as banks should leverage data mining techniques to identify unusual transaction patterns and monitor financial activities in real time.