Edi Yusuf Wirawan, Muhammad Abdul Rahman, Edie Kurniawan
Financial fraud remains a major concern for investors in Indonesia, particularly in the manufacturing, banking, and finance sectors. Corporate mismanagement and faulty financial reporting have far-reaching consequences, impacting both individual companies and the overall investment climate. With the rapid digitization of Indonesia’s financial sector, AI-driven fraud detection is gaining traction, especially in project financing and financial due diligence. AI can analyze large financial datasets in real-time, identifying patterns and anomalies more efficiently than traditional rule-based systems. Machine learning models enable financial institutions to flag suspicious transactions proactively, enhancing fraud prevention efforts. This paper explores AI implementation in financial fraud detection, focusing on financial due diligence in project financing. Findings indicate that AI significantly improves the speed and accuracy of data analysis, strengthening fraud detection capabilities. As financial services evolve, AI-driven solutions will be crucial in mitigating fraud risks and ensuring a more transparent financial ecosystem in Indonesia. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
Information System Department, STMIK Multicom, Kotamobagu, Indonesia; Finance Management Doctoral Program, Brawijaya University, Malang, Indonesia; Computer Science Doctoral Program, Diponegoro University, Semarang, Indonesia
