FORENSIC ACCOUNTING AS A TOOL FOR FRAUD DETECTION AND PREVENTION IN NIGERIA

The persistent and sophisticated nature of fraud within Nigeria's financial institutions has necessit ated the adoption of advanced forensic tools for detection and prevention. This study investigate s the roe of forensic accounting in fraud detection and prevention in Nigerian financial institutio ns,with specific focus on financial statement analysis, fraud risk assessment, and digital forensic t echniques. The objectives of the study are threefold: to examine the role of financial statement analysis in fraud detection, to assess the effectiveness of fraud risk assessment in preventing fra ud, and to determine the impact of digital forensic techniques on fraud control.Despite growing global recognition of forensic accounting, there exists a notable lacuna in empirical literature foc used on its practical application within the Nigerian context. Most existing studies have been con ducted in developed countries with mature regulatory systems,leaving a gap in understanding ho w forensic accounting operates in developing economies like Nigeria, where institutional weakness es, limited expertise, and insufficient technological adoption pose unique challenges. The study is anchored on the Agency Theory (Jensen & Meckling, 1976), which explains the divergence of int erests between principals (owners) and agents (management), often resulting in opportunistic beh aviors such as fraud. Forensic accounting is positioned within this framework as a strategic mech anism to mitigate agency problems, enhance transparency, and reinforce internal controls. Using a descriptive survey research design, primary data were collected from 95 staff members across selected public institutions in Lagos, Nigeria through a structured questionnaire.One-Way ANOVA and multiple regression analysis were employed to analyze the data and test the study's hypothe ses. The regression model examined the relationship between the three forensic accounting techn iques and fraud control outcomes. The results from regression analysis reveal that financial state ment analysis has a statistically significant positive relationship with fraud detection(β=0.315,p