European generic scoring models using survival analysis

被引:26
作者
Andreeva, G. [1 ]
机构
[1] Univ Edinburgh, Sch Management, Edinburgh EH9 1RS, Midlothian, Scotland
基金
英国经济与社会研究理事会;
关键词
credit scoring; regression analysis; risk; banking;
D O I
10.1057/palgrave.jors.2602091
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Credit scoring discriminates between 'good' and 'bad' credit risks to assist credit-grantors in making lending decisions. Such discrimination may not be a good indicator of profit, while survival analysis allows profit to be modelled. The paper explores the application of parametric accelerated failure time and proportional hazards models and Cox nonparametric model to the data from the retail card (revolving credit) from three European countries. The predictive performance of three national models is tested for different timescales of default and then compared to that of a single generic model for a timescale of 25 months. It is found that survival analysis national and generic models produce predictive quality, which is very close to the current industry standard-logistic regression. Stratification is investigated as a way of extending Cox non-parametric proportional hazards model to tackle heterogeneous segments in the population.
引用
收藏
页码:1180 / 1187
页数:8
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