Abstract

This comprehensive article explores the multifaceted aspects of data management in the finance sector, focusing on the pivotal roles of data accuracy, security, and regulatory compliance. It highlights the critical importance of data accuracy in risk assessment, emphasizing the consequences of inaccuracies in financial decision-making. The article also delves into the challenges posed by rigorous reporting requirements and the strategies financial institutions employ to ensure data integrity and security. By examining case studies and current practices, it provides an in-depth look at how emerging technologies like AI, machine learning, and blockchain are reshaping data management in finance. The discussion extends to the best practices for meeting regulatory compliance, underscoring the dynamic relationship between financial institutions and regulatory frameworks. This piece serves as an essential guide for professionals navigating the complex landscape of financial data management.

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