INTEGRATING ARTIFICIAL INTELLIGENCE AND DATA ANALYTICS IN FORENSIC ACCOUNTING: EMERGING TRENDS, CHALLENGES AND FUTURE PROSPECTS

Abstract

Artificial Intelligence (AI) and Data Analytics are transforming forensic accounting by improving the accuracy, efficiency and reliability of fraud detection and investigation. This study explores how AI-driven technologies such as machine learning, natural language processing, and robotic process automation are improving the effectiveness and efficiency of forensic accounting practices. It adopts a qualitative and descriptive research design based on secondary data from scholarly articles, institutional reports and professional publications published between 2016 and 2025. The findings reveal that AI and analytics enable proactive risk identification, real-time fraud monitoring and improved decision-making, thereby shifting forensic accounting from reactive auditing to predictive and continuous auditing frameworks. However, challenges such as high implementation costs, data privacy concerns, algorithmic bias and skill shortages limit widespread adoption, particularly in developing economies. The study concludes that the effective use of AI strengthens fraud detection, improves corporate governance, and increases transparency. It also recommends capacity building, the development of ethical frameworks and collaborative research to support sustainable adoption of technology at the global level.