Internal control systems as a mediator between forensic accounting skills and fraud likelihood: Evidence from Nigerian government enterprises
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Keywords

Federal government-owned enterprises, Forensic accounting skills, Fraud likelihood, Internal control systems, Mediation analysis, Public-Sector governance.

How to Cite

Akpadaka, . . O. S. ., Edeh, O. P. ., & Kato, S. N. (2026). Internal control systems as a mediator between forensic accounting skills and fraud likelihood: Evidence from Nigerian government enterprises. Asian Development Policy Review, 14(1), 81–98. https://doi.org/10.55493/5008.v14i1.5838

Abstract

Fraud and corruption continue to impede the effectiveness of Nigeria’s Federal Government-Owned Enterprises (FGOEs), which manage strategic public resources but often operate under weak oversight and governance challenges. Strengthening fraud prevention in these entities requires both capability development and system-level reforms. This study examines whether internal control systems (ICS) mediate the relationship between forensic accounting skills (FAS) and fraud likelihood (FL) in Nigerian FGOEs. Grounded in the Resource-Based View, Fraud Diamond Theory, and Agency Theory, the analysis investigates how forensic expertise and control mechanisms jointly mitigate misconduct risks. Data were collected from 256 finance, accounting, and internal audit personnel across 33 enterprises and analyzed using covariance-based structural equation modeling (CB-SEM). The results show that stronger forensic accounting skills are associated with more robust internal controls and lower fraud likelihood. Mediation analysis further reveals that ICS partially transmit the effect of FAS to fraud outcomes. The presence of a dedicated forensic unit demonstrates only a weak association with fraud likelihood after accounting for FAS and ICS. The study extends public-sector fraud literature by demonstrating the central role of internal control systems and underscores the need for capability building aligned with COSO-consistent control frameworks.

https://doi.org/10.55493/5008.v14i1.5838
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