This review paper examines the pivotal role of data analytics in enhancing decision-making and operational efficiency within financial institutions. The research highlights how data analytics tools and techniques optimize business processes, streamline operations, and improve resource allocation. Key areas such as risk assessment, customer segmentation, and fraud detection are explored to demonstrate the practical applications of data-driven decision-making. Additionally, the paper discusses the challenges financial institutions face in implementing data analytics, including issues related to data quality, system integration, and resistance to change. The paper concludes with recommendations for financial institutions to leverage data analytics effectively and suggests avenues for future research, particularly in emerging trends like artificial intelligence and machine learning.
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