Survival analysis methods for personal loan data
成果类型：
Article
署名作者：
Stepanova, M; Thomas, L
署名单位：
University of Southampton
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.50.2.277.426
发表日期：
2002
页码：
277-289
关键词：
摘要：
Credit scaring 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.