IDEAS home Printed from https://ideas.repec.org/a/ids/ijbfmi/v3y2017i3p248-258.html
   My bibliography  Save this article

Design dynamic credit risk model with fuzzy rules for auto dealers

Author

Listed:
  • Ying Zhou

Abstract

Credit risk scoring is one of the risk assessment tools of auto dealers, but it is complicated, which is affected by various variables and factors in different behaviour mechanisms. This paper incorporates the behaviour style of auto dealers in their ability to pay debt in a dynamic system with fuzzy rules for uncertainty. We discuss credit risk assessment of auto dealers by establishing a relevant credit risk evaluation system and present a dynamic fuzzy credit scoring model to forecast the credit risk of auto dealers. Our work focuses on two aspects: 1) we are investigating the credit risk of auto dealers in a dynamic system; 2) fuzzy rules are also integrated into a dynamic system as fuzzy inference system. Simulation results of a dynamic fuzzy credit risk model are presented in five different classes. Numerical results of simulation are analysed, a dynamic trend of management variety, sell rate and credit risk score are also provided.

Suggested Citation

  • Ying Zhou, 2017. "Design dynamic credit risk model with fuzzy rules for auto dealers," International Journal of Business Forecasting and Marketing Intelligence, Inderscience Enterprises Ltd, vol. 3(3), pages 248-258.
    • Handle: RePEc:ids:ijbfmi:v:3:y:2017:i:3:p:248-258
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=85364
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijbfmi:v:3:y:2017:i:3:p:248-258. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=156 .

    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.