A Conceptual Model for Advancing Risk Governance through Data-Driven Compliance Analytics in Financial Institutions

Abstract

Financial institutions operate in increasingly complex regulatory and operational environments, where the integration of risk governance and compliance analytics is critical for organizational resilience. This study proposes a conceptual model that leverages data-driven compliance analytics to advance risk governance, ensuring regulatory adherence, operational transparency, and proactive risk mitigation. The model integrates policy, process, and technology dimensions to optimize decision-making and improve compliance performance. Drawing from systematic literature review, qualitative case studies, and industry best practices, the study provides insights for financial managers, risk officers, and compliance professionals on implementing analytics driven governance frameworks.