PENGARUH KOMPENSASI, KEPUASAN KERJA DAN LINGKUNGAN KERJA TERHADAP RETENSI KARYAWAN PADA PERUSAHAAN JASA PERTAMBANGAN PT. TAMBANG MINERAL TERPADU

Abstract

Digital transformation has significantly increased the complexity of financial information systems while simultaneously expanding the risk of technology-enabled fraud. Although Big Data Analytics has been widely adopted to improve fraud detection capabilities, existing studies primarily emphasize technological aspects and pay limited attention to the roles of business law and corporate governance in ensuring its effective implementation. This study aims to develop a conceptual framework that explains the interaction between Big Data Analytics, Business Law, and Corporate Governance in strengthening fraud detection within financial information systems. The study employs a conceptual research approach based on an extensive literature review of scholarly articles, academic books, international reports, and relevant regulations. Data were analyzed using content analysis and conceptual synthesis to identify relationships among key concepts and construct an integrative conceptual model. The findings indicate that effective fraud detection depends not only on the analytical capability of Big Data Analytics but also on compliance with business law and the effective implementation of corporate governance. Based on the literature synthesis, this study proposes the AI–Governance–Legal Fraud Detection Framework, which integrates these three dimensions into a comprehensive approach for developing adaptive, transparent, accountable, and sustainable fraud detection systems. This framework contributes to the financial information systems literature by offering a multidisciplinary perspective and providing a conceptual foundation for future empirical studies and organizational practices in the era of digital transformation.