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Research on Risk Prediction Model of Internet Finance Based on Cloud Computing

Author

Listed:
  • Shuanbao Li
  • Xiaoyan Liu
  • Chengfei Li

Abstract

With the rapid development of the Internet, the traditional Internet financial risk prediction methods can no longer meet the needs of individuals and enterprises, so the concept of cloud computing arises at the historic moment. Cloud computing has subverted the traditional financial risk prediction method and has been widely studied and applied for its distributed, dynamic and autonomous characteristics. How to efficiently and reasonably schedule the resources of cloud data center and improve the accuracy of financial risk prediction is the focus of current research. How to quantify financial risk and financial risk early warning is one of the urgent problems to be solved. Under the framework of cloud computing, this paper combines the feature extraction and data weighting to study the user’s basic attribute data and a large number of downloaded APP types. After that, linear regression with penalty is used to construct the prediction model to improve insolvency. The accuracy of customer default judgment can realize local optimization, so as to improve the prediction and control of hidden risks of customer commercial bank loans and greatly reduce the default risk of bank loans.

Suggested Citation

  • Shuanbao Li & Xiaoyan Liu & Chengfei Li, 2022. "Research on Risk Prediction Model of Internet Finance Based on Cloud Computing," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:jjmath:v:2022:y:2022:i:1:n:2803934
    DOI: 10.1155/2022/2803934
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    References listed on IDEAS

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    Cited by:

    1. Sergey A. Vasiliev & Irina A. Nikonova & Olga S. Miroshnichenko, 2022. "Banks, Financial Platforms and Big Data: Development Trends and Regulation Directions," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 5, pages 105-119, October.

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