The literature review examines the revolutionary impact of data analytics on risk management practices. It synthesizes current research on how organizations are leveraging big data, artificial intelligence (AI), machine learning (ML), blockchain, and the Internet of Things (IoT) to enhance their operational risk management (ORM) systems. The review explores the shift from traditional to data-driven risk management, analyzes current challenges in implementing data-driven ORM systems, and investigates future horizons of risk management in a data-driven world. Key findings indicate that while data-driven approaches offer significant improvements in risk identification, assessment, and mitigation, organizations face substantial challenges in data quality, privacy concerns, cultural resistance, and integration with legacy systems. The review concludes by highlighting emerging trends and identifying areas for future research in this rapidly evolving field.