IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v48y1999i2p239-251.html
   My bibliography  Save this article

A Discrete Variable Chain Graph for Applicants for Credit

Author

Listed:
  • E. Stanghellini
  • K. J. McConway
  • D. J. Hand

Abstract

A bank offering unsecured personal loans may be interested in several related outcome variables, including defaulting on the repayments, early repayment or failing to take up an offered loan. Current predictive models used by banks typically consider such variables individually. However, the fact that they are related to each other, and to many interrelated potential predictor variables, suggests that graphical models may provide an attractive alternative solution. We developed such a model for a data set of 15 variables measured on a set of 14 000 applications for unsecured personal loans. The resulting global model of behaviour enabled us to identify several previously unsuspected relationships of considerable interest to the bank. For example, we discovered important but obscure relationships between taking out insurance, prior delinquency with a credit card and delinquency with the loan.

Suggested Citation

  • E. Stanghellini & K. J. McConway & D. J. Hand, 1999. "A Discrete Variable Chain Graph for Applicants for Credit," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(2), pages 239-251.
  • Handle: RePEc:bla:jorssc:v:48:y:1999:i:2:p:239-251
    DOI: 10.1111/1467-9876.00152
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1467-9876.00152
    Download Restriction: no

    File URL: https://libkey.io/10.1111/1467-9876.00152?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Frank Fabozzi & Omar Masood & Radu Tunaru, 2007. "Discrete Variable Chain Graphical Modelling for Assessing the Effects of Fund Managers' Characteristics on Incentives Satisfaction and Size of Returns," The European Journal of Finance, Taylor & Francis Journals, vol. 13(3), pages 269-282.
    2. L C Thomas & R W Oliver & D J Hand, 2005. "A survey of the issues in consumer credit modelling research," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(9), pages 1006-1015, September.
    3. Elena Stanghellini, 2003. "Monitoring the Behaviour of Credit Card Holders with Graphical Chain Models," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 30(9‐10), pages 1423-1435, December.

    More about this item

    Statistics

    Access and download statistics

    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:bla:jorssc:v:48:y:1999:i:2:p:239-251. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.