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Big Data in Financial Industry Risk Management: Applications and Challenges

In: Proceedings of the 2024 3rd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2024)

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  • Zishan Liu

    (Beijing University of Technology)

Abstract

This paper explores the applications and challenges of big data in financial industry risk management. As technology advances, big data has become a crucial tool in the financial sector, especially in risk management. Big data technologies provide financial institutions with more comprehensive and accurate risk assessment and monitoring tools by integrating data from various sources. The paper first outlines the definition, characteristics, and application framework of big data in the financial industry, followed by an in-depth analysis of its specific applications in credit risk, market risk, operational risk, fraud detection, anti-money laundering, and compliance risk management. Through machine learning and real-time monitoring, big data helps financial institutions identify and prevent potential credit defaults in credit risk management. In market risk management, big data aids financial institutions in accurately predicting market fluctuations and implementing appropriate hedging strategies through real-time market data analysis. Additionally, the paper discusses big data’s role in anomaly detection and process optimization in operational risk management, as well as in transaction monitoring and behavioral analysis for fraud detection and anti-money laundering. However, the application of big data also faces several challenges, including data quality and accuracy, data privacy and security, technology and talent shortages, compliance and legal issues, and difficulties in data integration across systems. These challenges demand higher standards for financial institutions to build effective risk management systems. To address these challenges, financial institutions need to enhance data governance, drive technological innovation, improve big data talent development, and strengthen data privacy and security protection. Finally, the paper concludes that despite these challenges, big data holds great potential in financial risk management, and further development should focus on cross-industry collaboration and innovation to fully leverage its advantages, ensuring the stability and sustainable development of the financial sector.

Suggested Citation

  • Zishan Liu, 2024. "Big Data in Financial Industry Risk Management: Applications and Challenges," Advances in Economics, Business and Management Research, in: Kun Zhang & Hang Luo & Hongbo Li & Azlina Binti Md Yassin (ed.), Proceedings of the 2024 3rd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2024), pages 266-274, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6463-548-5_29
    DOI: 10.2991/978-94-6463-548-5_29
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