Redefining Fraud Detection: The Synergy Between Auditor Competency and AI-Powered Audit Analytics

Abstract

This research investigates the impact of auditor competence on the effectiveness of fraud detection, with AI-driven audit analytics serving as a moderating factor. In the context of an increasingly digitalized economy, the complexity of financial fraud continues to evolve, posing challenges to conventional audit practices. The integration of Artificial Intelligence (AI) into auditing introduces advanced functionalities such as real-time data processing, anomaly identification, and predictive analysis. Nevertheless, the success of these AI applications depends substantially on the auditors’ proficiency—particularly their technical expertise, critical thinking ability, and digital fluency. Employing a quantitative methodology with Partial Least Squares Structural Equation Modelling (PLS-SEM), this study collected responses from 100 Indonesian auditors familiar with digital audit technologies. The findings demonstrate a strong positive link between auditor competency and the ability to detect fraud effectively. Furthermore, the application of AI-powered audit analytics significantly enhances this relationship, positioning AI as a key facilitator in improving audit outcomes. This study not only adds to the expanding scholarship on digital auditing practices but also aligns with Sustainable Development Goal 9, which promotes innovation and technological advancement to foster institutional integrity. Additionally, it underscores the importance of comprehensive auditor development programs that combine technical training, ethical considerations, and digital tool integration to ensure responsible and effective use of AI in modern auditing.