Automated Forensic Auditing and Fraud Control in Nigeria (A Case Study of Federal Medical Center Bida)

This study investigates the development and implementation of an automated forensic auditing system designed to strengthen fraud detection, financial transparency, and accountability within healthcare financial operations, using Federal Medical Centre Bida as a case study. The research is motivated by persistent weaknesses in conventional auditing approaches, particularly the reliance on manual processes and system designs that enable unlogged or manipulated transactions. The study adopts a systematic approach that combines system analysis, software design, and implementation of a pay point management framework capable of real-time transaction logging, audit trail generation, and anomaly monitoring. Core technologies including a centralized database, middleware communication, and monitoring tools were integrated to ensure continuous forensic readiness and reduce opportunities for revenue leakages and unauthorized overrides. Findings from the implementation demonstrate that automated forensic auditing significantly improves data integrity, enhances visibility over financial flows, and supports timely detection of suspicious transactions. The study concludes that automated forensic auditing presents a viable pathway for improving fraud prevention and forensic investigation in public healthcare institutions and recommends further integration of artificial intelligence, blockchain, and advanced analytics in future models. Keywords: Forensic Auditing, Automation, Fraud Control, Healthcare Finance, Real-Time Monitoring, Audit Trail CISDI Journal Reference Format Ibrahim, M. M., Adamu A. Isah., Abdulrahman A. & Tajudeen, F.A. (2026): Automated Forensic Auditing and Fraud Control in Nigeria (A Case Study of Federal Medical Center Bida). Computing, Information Systems, Development Informatics & Allied Research Journal. Vol 17 No 1, Pp 25-40. Available online at www.isteams.net/cisdijournal. dx.doi.org/10.22624/AIMS/CISDI/V17N1P2