How to Measure the Quality of Credit Scoring Models

被引:0
|
作者
Rezac, Martin [1 ]
Rezac, Frantisek [1 ]
机构
[1] Masaryk Univ, Brno, Czech Republic
关键词
credit scoring; quality indices; lift; profit; normally distributed scores; ASSOCIATION; RISK;
D O I
暂无
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Credit scoring models are widely used to predict the probability of client default. To measure the quality of such scoring models it is possible to use quantitative indices such as the Gini index, Kolmogorov-Smirnov statistics (KS), Lift, the Mahalanobis distance, and information statistics. This paper reviews and illustrates the use of these indices in practice.
引用
收藏
页码:486 / 507
页数:22
相关论文
共 50 条
  • [21] Building classification models for customer credit scoring
    Benyacoub, Badreddine
    El Bernoussi, Souad
    Zoglat, Abdelhak
    PROCEEDINGS OF 2014 2ND IEEE INTERNATIONAL CONFERENCE ON LOGISTICS AND OPERATIONS MANAGEMENT (GOL 2014), 2014, : 107 - 111
  • [22] Credit Risk Scoring with Bayesian Network Models
    Leong, Chee Kian
    COMPUTATIONAL ECONOMICS, 2016, 47 (03) : 423 - 446
  • [23] HOW TO MODEL ROC CURVES - A CREDIT SCORING PERSPECTIVE
    Kochanski, Blazej
    12TH INTERNATIONAL DAYS OF STATISTICS AND ECONOMICS, 2018, : 853 - 863
  • [24] CREDIT SCORING MODELS IN ESTIMATING THE CREDIT WORTHINESS OF SMALL AND MEDIUM AND BIG ENTERPRISES
    Zenzerovic, Robert
    CROATIAN OPERATIONAL RESEARCH REVIEW, 2011, 2 (01) : 143 - 157
  • [25] Advantages of credit scoring models in loan applicants evaluation
    Mileris, Ricardas
    CHANGES IN SOCIAL AND BUSINESS ENVIRONMENT, PROCEEDINGS, 2007, : 170 - 173
  • [26] Data mining feature selection for credit scoring models
    Liu, Y
    Schumann, M
    JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2005, 56 (09) : 1099 - 1108
  • [27] Developing Unsupervised Learning Models for Credit Scoring Problem
    Tudor, Liviana N.
    VISION 2025: EDUCATION EXCELLENCE AND MANAGEMENT OF INNOVATIONS THROUGH SUSTAINABLE ECONOMIC COMPETITIVE ADVANTAGE, 2019, : 3588 - 3594
  • [28] A review of fuzzy logic applied to credit scoring models
    Gomez Jaramillo, Sebastian
    CUADERNO ACTIVA, 2012, (03): : 37 - 44
  • [29] Credit scoring using global and local statistical models
    Schwarz, A
    Arminger, G
    Classification - the Ubiquitous Challenge, 2005, : 442 - 449
  • [30] Decision Trees as Interpretable Bank Credit Scoring Models
    Szwabe, Andrzej
    Misiorek, Pawel
    BEYOND DATABASES, ARCHITECTURES AND STRUCTURES: FACING THE CHALLENGES OF DATA PROLIFERATION AND GROWING VARIETY, 2018, 928 : 207 - 219