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Survival Analysis Methods for Personal Loan Data

Author

Listed:
  • Maria Stepanova

    (UBS AG, Financial Services Group, Pelikanstrasse 6, CH-8098 Zurich, Switzerland)

  • Lyn Thomas

    (Department of Management, University of Southampton, Southampton, United Kingdom, S017 1BJ)

Abstract

Credit scoring is one of the most successful applications of quantitative analysis in business. This paper shows how using survival-analysis tools from reliability and maintenance modeling allows one to build credit-scoring models that assess aspects of profit as well as default. This survival-analysis approach is also finding favor in credit-risk modeling of bond prices. The paper looks at three extensions of Cox's proportional hazards model applied to personal loan data. A new way of coarse-classifying of characteristics using survival-analysis methods is proposed. Also, a number of diagnostic methods to check adequacy of the model fit are tested for suitability with loan data. Finally, including time-by-characteristic interactions is proposed as a way of possible improvement of the model's predictive power.

Suggested Citation

  • Maria Stepanova & Lyn Thomas, 2002. "Survival Analysis Methods for Personal Loan Data," Operations Research, INFORMS, vol. 50(2), pages 277-289, April.
    • Handle: RePEc:inm:oropre:v:50:y:2002:i:2:p:277-289
    DOI: 10.1287/opre.50.2.277.426
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    References listed on IDEAS

    as
    1. Ian Cooper & Marcel Martin, 1996. "Default risk and derivative products," Applied Mathematical Finance, Taylor & Francis Journals, vol. 3(1), pages 53-70.
    2. Jarrow, Robert A. & Turnbull, Stuart M., 2000. "The intersection of market and credit risk," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 271-299, January.
    3. J Banasik & J N Crook & L C Thomas, 1999. "Not if but when will borrowers default," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(12), pages 1185-1190, December.
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