Artificial Intelligence (AI) transforms the audit landscape by enhancing fraud detection and risk assessment with unprecedented speed and accuracy. This study explores the application of AI in forensic accounting to identify financial irregularities using advanced machine learning models. AI-driven approaches such as supervised and unsupervised algorithms can efficiently detect anomalies in financial data, reducing false positives and improving audit reliability. Through statistical analysis and conceptual modeling, we highlight how AI contributes to a dynamic fraud prevention ecosystem. This research underscores the role of AI in reshaping audit methodologies and proposes a framework to integrate AI into risk management practices.
Dash et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: