<![CDATA[Background:The increasing complexity and volatility of global financial markets have intensified the need for innovative tools to manage risks effectively. Traditional risk management methods often fail to adapt to real-time changes and large-scale data, leading to missed opportunities and increased vulnerabilities. Big Data Analytics (BDA) has emerged as a transformative solution, enabling financial institutions to process vast and diverse datasets to predict risks, detect fraud, and enhance decision-making capabilities. Aims:This study aims to explore the role of Big Data Analytics in enhancing financial risk management. It seeks to examine the benefits, challenges, and future implications of BDA adoption, focusing on its impact on risk prediction accuracy, fraud detection, real-time monitoring, and regulatory compliance in financial institutions. Research Method:The study employs a mixed-method approach, integrating quantitative and qualitative analyses. Quantitative data were derived from financial reports, industry surveys, and case studies, while qualitative insights were gathered through interviews with industry professionals and analysis of institutional practices. Statistical tools and thematic analysis were utilized to draw comprehensive conclusions. Results and Conclusion:The findings reveal that BDA significantly improves risk prediction accuracy, fraud detection rates, and response times in risk management. Institutions leveraging BDA reported enhanced compliance metrics and operational efficiencies. However, challenges such as data quality issues, high implementation costs, and regulatory hurdles persist. Addressing these barriers is critical to unlocking the full potential of BDA in financial risk management. Contribution:This study contributes to the understanding of how BDA reshapes financial risk management practices. It provides actionable insights for financial institutions, regulators, and researchers to overcome implementation challenges and capitalize on the opportunities offered by advanced analytics.]]>
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