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Application of the algorithm based on the PSO and improved SVDD for the personal credit rating

Author

Listed:
  • Sulin Pang

    (Department of Mathematics/School of Emergency, Management/Institute of Finance Engineering, Jinan University, Guangzhou 510632, China;
    Guangdong Emergency Technology Research Center of Risk Evaluation and Prewarning on Public Network Security, Guangzhou 510632, China)

  • Shuqing Li

    (Department of Mathematics/School of Emergency, Management/Institute of Finance Engineering, Jinan University, Guangzhou 510632, China;
    Guangdong Emergency Technology Research Center of Risk Evaluation and Prewarning on Public Network Security, Guangzhou 510632, China)

  • Jinwang Xiao

    (Department of Mathematics/School of Emergency, Management/Institute of Finance Engineering, Jinan University, Guangzhou 510632, China;
    Guangdong Emergency Technology Research Center of Risk Evaluation and Prewarning on Public Network Security, Guangzhou 510632, China)

Abstract

Considering the question of personal credit rating, this paper proposes a hybrid method for credit assessment based on an improved Support Vector Data Description (SVDD) algorithm combined with the particle swarm optimization (PSO) algorithm. First, the paper carries out data preprocess, and then it solves the two problems: parameters optimization and feature selection at the same time using the PSO algorithm combined with the improved SVDD algorithm and assesses the credit data using the optimized parameters and features. Finally, the method constructed is tested through two data sets in practice, and the results show that the hybrid method constructed in this paper can obtain higher classification accuracy compared with some other existing credit scoring methods.

Suggested Citation

  • Sulin Pang & Shuqing Li & Jinwang Xiao, 2014. "Application of the algorithm based on the PSO and improved SVDD for the personal credit rating," Journal of Financial Engineering (JFE), World Scientific Publishing Co. Pte. Ltd., vol. 1(04), pages 1-19.
    • Handle: RePEc:wsi:jfexxx:v:01:y:2014:i:04:n:s2345768614500378
    DOI: 10.1142/S2345768614500378
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    References listed on IDEAS

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    1. David Durand, 1941. "Risk Elements in Consumer Instalment Financing," NBER Books, National Bureau of Economic Research, Inc, number dura41-1.
    2. David Durand, 1941. "Risk Elements in Consumer Instalment Financing, Technical Edition," NBER Books, National Bureau of Economic Research, Inc, number dura41-2.
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    Cited by:

    1. Mi Li & Huan Chen & Xiaodong Wang & Ning Zhong & Shengfu Lu, 2019. "An Improved Particle Swarm Optimization Algorithm with Adaptive Inertia Weights," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 833-866, May.
    2. Dionne, Georges & Koumou, Gilles Boevi, 2018. "Machine Learning and Risk Management: SVDD Meets RQE," Working Papers 18-6, HEC Montreal, Canada Research Chair in Risk Management.

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