Artificial Intelligence in Forensic Accounting: A Literature Review

Abstract

This literature review examines the transformative impact of artificial intelligence (AI) on forensic accounting. Drawing from recent academic research, industry reports, and global case studies, the review traces the historical evolution of AI applications—from early expert systems to modern machine learning and natural language processing techniques. Key challenges, such as data quality, model explainability, ethical concerns, and regulatory gaps, are examined alongside the opportunities that AI presents, including improved detection accuracy, real-time monitoring, and the ability to analyze unstructured data. The review emphasizes the synergistic relationship between human expertise and AI, advocating for hybrid approaches that enhance investigative efficiency and objectivity. It also identifies future research directions, including explainable AI, blockchain analytics, continuous auditing, and the integration of advanced techniques such as federated learning. This review offers scholars and practitioners a comprehensive and up-to-date understanding of how AI is transforming forensic accounting practices globally.