Abstract
This study examined the effect of forensic accounting techniques on payroll fraud detection in the Nigerian Federal Ministry of Finance and its agencies. A population of 173 staff was studied, and multiple regression analysis assessed the influence of five techniques data mining, document authentication, interview technique, ratio analysis, and payroll reconciliation on fraud detection. Findings showed that data mining had a positive but insignificant effect, indicating that its current use and technological advancement were insufficient for a statistically meaningful impact. Document authentication had a positive and significant effect, demonstrating that verifying employee records and payroll entries enhanced detection of ghost workers and unauthorized alterations. The interview technique also had a positive and significant effect, highlighting the value of structured investigative interviews in uncovering payroll irregularities. Ratio analysis exhibited a positive but insignificant effect, suggesting that analytical reviews alone were not strong enough to significantly influence fraud detection. Payroll reconciliation had a positive and significant effect, confirming that systematically comparing payroll records with personnel files and bank statements effectively identified duplicate payments and salary manipulations. The study recommended investing in advanced data mining tools, enhancing document authentication through biometric verification and centralized systems, providing regular training in interview techniques, integrating ratio analysis into automated dashboards, and institutionalizing automated payroll reconciliation supported by adequate staffing and technology to strengthen payroll integrity and minimize fraud across government agencies.