A Combined Assessment Method on the Credit Risk of Enterprise Group Based on the Logistic Model and Neural Networks

  • Xiao Min
  • Liu Wenrui
  • Xu Chao
  • Zhou Zongfang
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 144)


As the credit risk of enterprise group is closely related to its financial state, in this paper,we chose the financial indicators and characteristic index of the enterprise groups used in literature [1] and applied the combined method based on the Logistic model and Neural Networks to assess the credit risk of Chinese listed enterprise group. Then we chose correlative Chinese listed enterprise group over the 2004-2008 period as study sample and conducted empirical research by using the combined method. Finally, we made a comparison among the evaluation results of three methods.


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  1. 1.
    Liu, W., Xiao, M., Zhou, Z.: Empirical Study on the Credit Risk of Enterprise Group Using BP Neural Networks. An Academic Edition of ManaMaga 10, 37–43 (2010)Google Scholar
  2. 2.
    Altman, E., Resti, A., Sironi, A.: Default recovery rates in credit risk modeling: a review of the literature and empirical evidence. Economic Notes 33(2), 183–208 (2004)CrossRefGoogle Scholar
  3. 3.
    Berger, A.N., De Young, R.: Problem loans and cost efficiency in commercial banks. Journal of Banking and Finance 21, 849–870 (1997)CrossRefGoogle Scholar
  4. 4.
    Liu, D., Wang, X.: On the Construction of System of the Credit Risk Management of Banks upon Group Customers. Journal of Changsha University of Science & Technology (Social Science) 2, 67–70 (2009)Google Scholar
  5. 5.
    Chen, L., Zhou, Z.: The Research on Measure Default Correlation of Related Corporations Controlled by an Enterprise Group. Chinese Journal of Management Science 18(05), 159–164 (2010)Google Scholar
  6. 6.
    Zhou, Z.: The theories and methods on emerging technology enterprise’s credit risk evaluation. Science Press, Beijing (2010)Google Scholar
  7. 7.
    Wang, C., Wan, H., Zhang, W.: Application of Combining Forecasts in Credit Risk Assessment in Banks. Journal of Industrial Engineering/Engineering Management 13(1), 5–9 (1999)Google Scholar
  8. 8.
    Lee, T.-S., Chiu, C.-C., Lu, C.-J., Chen, I.-F.: Credit scoring using hybrid neural discriminant technique. Expert System with Applications 23(3), 245–254 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.School of Management and EconomicsUESTCChengduChina

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