Time to default in credit scoring using survival analysis: a benchmark study

Lore Dirick, Gerda Claeskens and Bart Baesens

No 507126, Working Papers of Department of Decision Sciences and Information Management, Leuven from KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven

Abstract: We investigate the performance of various survival analysis techniques applied to ten actual credit data sets from Belgian and UK financial institutions. In the comparison we consider classical survival analysis techniques, namely the accelerated failure time models and Cox proportional hazards regression models, as well as Cox proportional hazard regression models with splines in the hazard function. Mixture cure models for single and multiple events were more recently introduced in the credit risk context. The performance of these models is evaluated using both a statistical evaluation and an economic approach through the use of annuity theory. It is found that spline-based methods and the single event mixture cure model perform well in the credit risk context.

Keywords: Benchmarking; Credit risk modeling; Competing risk; Mixture cure model; Survival analysis (search for similar items in EconPapers)
Date: 2015
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Published in FEB Research Report KBI_1522

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