IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-38442-4_1.html
   My bibliography  Save this book chapter

A Study of Research and Application of Credit Scoring Model Based on Probit Model

In: The 19th International Conference on Industrial Engineering and Engineering Management

Author

Listed:
  • Da Ren

    (Tianjin University)

  • Maodong Hou

    (Tianjin University)

  • Huan Li

    (Tianjin University)

Abstract

As the main content of the credit risk management, Credit rating has significant research value. China’s current use of credit scoring method is too subjective and unable to adapt to the fierce competition in the banking sector. In connection with the week ability of risk identification of Chinese commercial banks, paper use the Probit regression to build credit scoring models, calculate the probability of default of each customer, divide the customers into two categories, and then test the classification results with ROC curve. The conclusion of the paper shows that the Probit—based credit scoring models can be effective to identify the risk of a manufacturing enterprise, and it is suitable for China’s commercial banks to assess corporate lending credit risk.

Suggested Citation

  • Da Ren & Maodong Hou & Huan Li, 2013. "A Study of Research and Application of Credit Scoring Model Based on Probit Model," Springer Books, in: Ershi Qi & Jiang Shen & Runliang Dou (ed.), The 19th International Conference on Industrial Engineering and Engineering Management, edition 127, chapter 0, pages 1-13, Springer.
  • Handle: RePEc:spr:sprchp:978-3-642-38442-4_1
    DOI: 10.1007/978-3-642-38442-4_1
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-642-38442-4_1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.