From Perception to Empirical Association: an Integrated Assessment of Fraud Detection Effectiveness Using Forensicanalytics, Internal Controls, and Continuous Auditing
The increasing complexity of financial transactions and the limitations of perception‑based fraud detection studies necessitate empirically grounded frameworks that move beyond subjective assessments. This study advances the literature by examining the associations among data‑driven forensic analytics (DDFA), internal control systems (ICS), continuous auditing (CA), and fraud detection effectiveness (FDE) using an integrated empirical assessment. An integrated model combining these three mechanisms is developed. A quantitative cross‑sectional research design is adopted, with primary data collected from finance and audit professionals across multiple sectors within a single national context (anonymised for review), yielding 120 valid responses (80% response rate). Data analysis employs SPSS, including descriptive statistics, reliability testing (Cronbach’s α), correlation analysis, and multiple regression modelling with comprehensive diagnostic validation (multicollinearity, residual independence, non‑response bias, and common method bias assessment using both Harman’s single‑factor and full collinearity VIF). Results indicate that all three components exhibit positive, statistically significant associations with FDE. DDFA shows the largest standardised coefficient (β = 0.41, p < 0.001), followed by ICS (β = 0.36, p < 0.001) and CA (β = 0.30, p < 0.001). The model explains approximately 65% of the variance in FDE (R²= 0.65, adjusted R² = 0.63). These findings are interpreted strictly as associational, not causal. The study contributes a coherent, empirically validated framework while addressing prior methodological criticisms related to inconsistent reporting and unsupported causal claims. The findings suggest that organisations prioritising analytical capability alongside governance and monitoring structures may achieve up to 65% improvement in explained detection effectiveness, highlighting the strategic value of integrated fraud detection systems.
