ENHANCING FINANCIAL SERVICES THROUGH BIG DATA AND AI-DRIVEN CUSTOMER INSIGHTS AND RISK ANALYSIS

Authors

  • Tianyi Yang Financial Risk Management,University of Connecticut,Stamford CT, USA Author
  • Qi Xin Financial Risk Management,University of Connecticut,Stamford CT, USA Author
  • Xiaoan Zhan Electrical Engineering, New York University, NY, USA Author
  • Shikai Zhuang Electrical Engineering, University of Washington, Seattle, WA, USA Author
  • Huixiang Li Information Studies, Trine University, AZ, USA Author

DOI:

https://doi.org/10.60087/jklst.vol3.n3.p53-62

Keywords:

Big Data, Artificial Intelligence , Financial Risk Monitoring, Machine Learning

Abstract

The article discusses the integration of big data and artificial intelligence (AI) technologies in the financial sector, focusing on supervised learning for pricing models to enhance customer identification and targeting. It details the construction of customer feature systems, including attributes like debit and credit card transactions, loan applications, and online behavior. By leveraging AI, financial institutions aim to accurately profile customers, boost consumption, and improve price management, ultimately aiding risk management and loan approval decisions. The article also covers related work in financial risk monitoring and machine learning in credit risk modeling, highlighting advancements and challenges in these areas.

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Published

05-07-2024

How to Cite

Yang, T. ., Xin, Q. ., Zhan, X. ., Zhuang, S. ., & Li, H. . (2024). ENHANCING FINANCIAL SERVICES THROUGH BIG DATA AND AI-DRIVEN CUSTOMER INSIGHTS AND RISK ANALYSIS. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 3(3), 53-62. https://doi.org/10.60087/jklst.vol3.n3.p53-62

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