AUTOMATED FORENSIC AUDITING

Fraud is a reoccurring challenge in financial systems, affecting businesses, government institutions, and the economy at large. Traditional auditing methods dependence on manual procedures has made them inadequate for detecting and preventing fraudulent activities. A technological answer to this problem is the use of automated forensic auditing, which uses machine learning, artificial intelligence, and advanced data analytics to improve fraud detection and control. The study uses a qualitative and quantitative research approach, collecting data from organizations that have adopted forensic auditing technologies. The results will provide useful insights for management, auditors, investors, regulatory bodies, public users, researchers, and policymakers in strengthening fraud control mechanisms in Nigeria. However, the adoption and implementation of automated forensic auditing in Nigeria face several obstacles, including high costs, a shortage of skilled forensic auditors, and inadequate regulatory frameworks