Artificial Intelligence and the Legal Framework in Preventing Financial Report Manipulation in Indonesia - Tirtakusuma, Andreas Eno Eno; Tirtakusuma, Eleazar Josiah Josiah; Tirtakusuma, Adino Jedidiah Jedidiah (UNISSULA, 2025)
Financial statement manipulation undermines investor trust and market stability, particularly in Indonesia, where recurring scandals highlight enforcement challenges. This study aims to analyze manipulation techniques, evaluate the dual role of artificial intelligence in detection and perpetration, and propose regulatory enhancements. Employing a qualitative descriptive approach with a normative legal perspective, the research examines case studies of Indonesian firms, including PT Kimia Farma and eFishery, using statutory and conceptual analysis. The findings reveal prevalent manipulation methods, such as inventory inflation and related-party transactions, driven by factors outlined in the fraud hexagon theory, including pressure and opportunity. Artificial intelligence enhances detection through anomaly identification but risks enabling sophisticated fraud if unregulated. Weak internal controls and inconsistent legal enforcement exacerbate these issues. The study concludes that mandatory artificial intelligence training for auditors, stricter disclosure requirements, and dedicated oversight bodies are essential to strengthen financial reporting integrity. These measures can foster transparency and accountability in Indonesia’s financial ecosystem. Future research should explore artificial intelligence’s effectiveness in high-growth startups to address evolving fraud dynamics.