Using Big Data for Better Operational Efficiency and Risk Management in Banking and Financial Services

Using Big Data for Better Operational Efficiency and Risk Management in Banking and Financial Services

Authors

  • Sophea Khem Department of Finance, Royal University of Phnom Penh (RUPP), Pursat Campus
  • Sovannara Lim Department of Banking, Pannasastra University of Cambodia (PUC)

Keywords:

Executive sponsorship, Data governance, Self-service analytics, Business use cases, Cloud infrastructure

Abstract

The banking and financial services industry generates massive amounts of data on a daily basis. This "big data" presents tremendous opportunities for banks and financial institutions to gain insights and improve operations. In this research article, we explore the applications of big data analytics in banking for enhanced operational efficiency and risk management. We review the sources of big data in banking, the analytics techniques used, and the benefits accrued. Challenges and critical success factors for effective big data implementation are also discussed. Overall, this article aims to provide a comprehensive overview of how big data can transform business processes and risk management in banking and financial services. The key message is that by leveraging big data analytics appropriately, banks can achieve higher productivity, better risk controls, and superior customer service.

Author Biography

Sovannara Lim, Department of Banking, Pannasastra University of Cambodia (PUC)

 

 

 

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Published

2024-01-07

How to Cite

Khem, S., & Lim, S. (2024). Using Big Data for Better Operational Efficiency and Risk Management in Banking and Financial Services. Eigenpub Review of Science and Technology, 8(1), 9–27. Retrieved from https://studies.eigenpub.com/index.php/erst/article/view/64
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