Artificial Intelligence dalam Fraud Detection dan Governance: A Systematic Literature Review

Abstract

The development of digital technology has increased the complexity of fraud practices and encouraged organizations to strengthen fraud detection systems through the integration of governance mechanisms and Artificial Intelligence (AI). This study aims to systematically review the development of research related to Artificial Intelligence in fraud detection and governance. This research employs a Systematic Literature Review (SLR) approach using the PRISMA framework. The reviewed articles were obtained from reputable international journals published between 2021 and 2026 and analyzed based on research focus, methods, variables, findings, and future research opportunities. The results indicate that Artificial Intelligence improves the effectiveness, efficiency, and accuracy of fraud detection through anomaly detection, predictive analytics, and real-time monitoring systems. Governance mechanisms such as whistleblowing systems, internal control, competence, and organizational behavior also play important roles in supporting fraud prevention and detection. However, studies integrating AI, governance, behavioral factors, and ESG fraud detection remain limited, particularly in the higher education sector and developing countries. This study contributes by providing a comprehensive mapping of AI-based fraud detection research and proposing future research directions related to governance, sustainability, and digital fraud prevention.