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Evaluation of SMEs’ Credit Decision Based on Support Vector Machine-Logistics Regression

Author

Listed:
  • Rui Xie
  • Rui Liu
  • Xian-Bei Liu
  • Jia-Ming Zhu
  • Ghulam Mustafa

Abstract

This article uses support vector machines, logistics regression, and other methods for the comprehensive evaluation of credit decision-making of small, medium, and microenterprises and comprehensively uses software programming such as MATLAB and SPSS Modeler to solve the problem. The results, such as credit risk evaluation index system, credit risk classification model, and credit decision-making comprehensive evaluation model, are obtained. Finally, this article starts from the credit decision of small, medium, and microenterprises and provides theoretical and practical suggestions for banks to control the risks of small, medium, and microenterprises and their own development.

Suggested Citation

  • Rui Xie & Rui Liu & Xian-Bei Liu & Jia-Ming Zhu & Ghulam Mustafa, 2021. "Evaluation of SMEs’ Credit Decision Based on Support Vector Machine-Logistics Regression," Journal of Mathematics, Hindawi, vol. 2021, pages 1-10, March.
    • Handle: RePEc:hin:jjmath:5541436
    DOI: 10.1155/2021/5541436
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    Cited by:

    1. Srđan Jelinek & Pavle Milošević & Aleksandar Rakićević & Ana Poledica & Bratislav Petrović, 2022. "A Novel IBA-DE Hybrid Approach for Modeling Sovereign Credit Ratings," Mathematics, MDPI, vol. 10(15), pages 1-21, July.

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