Use of Artificial Intelligence (AI) and Machine Learning (ML) in Corporate Governance against Financial Fraud - Alfiyah Aditya Rahmawati; Zakia Maulida Antono; Vina Yunistiyani (Hikamatzu | Journal of Multidisciplinary, 2025)
Financial fraud continues to pose significant risks to global economic stability, encouraging the growing adoption of artificial intelligence (AI) and machine learning (ML) within corporate governance frameworks. This bibliometric review analyzes 46 articles published between 2017 and 2025, revealing a strong annual growth rate of 35.7%, indicating increasing scholarly attention to this research domain. The findings show that China and India are the most productive countries, followed by the United Kingdom, reflecting the expanding geographical distribution of AI- and ML-based fraud research. Key contributing authors include Chen Y, Li Y, and Wu Z. Keyword and trend analyses highlight emerging research themes such as fraud detection, deep learning, learning systems, and crime-related risk assessment. Recent studies increasingly emphasize advanced ML techniques and AI-driven governance mechanisms to strengthen fraud prevention and monitoring. Future research should further explore comparative empirical evidence on AI and ML effectiveness in corporate governance systems, particularly across different regulatory and institutional contexts, while integrating emerging techniques such as deep learning and hybrid intelligent systems.