Criteria for model selection in credit scoring. Application of discriminant analysis based on distances

被引：0
|
作者：
Boj, Eva [1 ]
Merce Claramunt, Ma [1 ]
Esteve, Anna [2 ]
Fortiana, Josep [3 ]
机构：
[1] Univ Barcelona, Fac Econ & Empresa, Dept Matemat Econ Financiera & Actuarial, Ave Diagonal 690, Barcelona 08034, Spain
[2] Hosp Univ Hermanos Trias & Pujol, Ctr Estudios Epidemiol Infecc Transmis Sexual & C, CIBERESP, Badalona 08916, Spain
[3] Univ Barcelona, Fac Matemat, Dept Probabilidad Logica & Estadist, E-08007 Barcelona, Spain
来源：
ANALES DEL INSTITUTO DE ACTUARIOS ESPANOLES | 2009年 / 15期
关键词：
Credit Risk; Credit scoring; Probability of default; Multivariate Data Analysis; Distance Based Prediction;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
The aim of this paper is to study model selection criteria in credit scoring. Such criteria are usually derived from an error cost function which takes into account misclassification probabilities in good and bad credit risk subpopulations plus other parameters encoding context information relevant to the objective portfolio. We present a distance based classification approach to credit scoring, as an addition to the current repertoire of procedures. We illustrate both method and selection criteria with two real datasets.
引用
收藏
页码：209 / 230
页数：22
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