Forensic Accounting Techniques and Fraud Detection in Selected Public Entities in Nigeria
Résumé fourni par la source
The increasing sophistication and frequency of fraudulent activities have created a greater need for effective mechanisms to detect and address financial irregularities. This sets the foundation for this study, which evaluated the effect of forensic accounting techniques in detecting fraud within the Nigerian public sector. This study employed survey research design, and population comprised 357 staff members with accounting related functions of the 3 selected Nigerian public entities (Federal Ministry of Finance, Federal Ministry of Budget and Financial Planning, and Economic and Financial Crimes Commission). This study employed a purposive sampling technique to select a sample size of 240 and data obtained through close ended questionnaire was analysed using partial least square through the aid of SMARTPLS. The regression analysis revealed that all three techniques; Benford Law, computer-assisted auditing tools (CAATs), and data mining analytics have positive and significant effects on fraud detection, demonstrating their usefulness in identifying financial anomalies and irregularities. The study concludes that forensic accounting techniques such as Benford Law, CAATs, and data mining analytics are powerful tools that significantly improve fraud detection in Nigerian public sector entities. These techniques provide systematic approaches for identifying financial anomalies, thereby enhancing accountability and transparency within public institutions. Based on the findings, it is recommended that Nigerian public sector entities adopt and integrate these forensic accounting techniques into their financial monitoring and auditing processes.
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Contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Forensic Accounting Techniques and Fraud Detection in Selected Public Entities in Nigeria
- Date Crossref
- 07/09/2026
- Éditeur
- IIARD Publication Co.
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.
Institutions déclarées
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