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Survival Analysis Methods for Personal Loan Data

UBS AG, Financial Services Group, Pelikanstrasse 6, CH-8098 Zurich, Switzerland
Department of Management, University of Southampton, Southampton, United Kingdom, S017 1BJ
maria.stepanova{at}ubs.com
l.thomas{at}soton.ac.uk

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.

Subject classifications: Risk: estimating credit risk for personal loans; Failure models: Survival analysis applied to credit scoring models.
History: Received November 1999; revision received August 2000; accepted October 2000.