The use of Artificial Intelligence (AI) in Fraud Detection by Government Auditors: A Systematic Literature Review
Keywords:
Artificial Intelligence (AI), Fraud Detection, Government Auditors, Public Sector Auditing, Literature ReviewAbstract
This study examines the role of artificial intelligence (AI) in fraud detection by government auditors through a systematic literature review of 17 scientific articles published between 2023 and 2025. The increasing complexity of financial transactions and the limitations of traditional audit methods underscore the need for innovative solutions. This review aims to identify the benefits, challenges, and driving factors for the adoption of AI technology in fraud detection. Using a systematic approach, the study analyzes the potential of AI, particularly machine learning and data mining techniques, in enhancing efficiency and accuracy in detecting data anomalies. The findings indicate that AI significantly strengthens auditors' capabilities but faces challenges such as skilled human resource limitations, privacy and ethical issues, and infrastructure needs. The successful adoption of AI depends on organizational readiness, regulatory support, and auditor competence. AI serves as a powerful supporting tool rather than a replacement for auditors. Integration with technologies like blockchain can further enhance fraud detection systems. This review provides strategic recommendations for academics and practitioners in the public sector, contributing to a holistic understanding of AI's role in fraud detection.
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