A literature review on the application of evolutionary computing to credit scoring

被引：83

作者：

Marques, A. I. ^{[1
]}

Garcia, V. ^{[2
]}

Sanchez, J. S. ^{[2
]}

机构：

[1] Univ Jaume 1, Dept Business Adm & Mkt, Castellon de La Plana, Spain

[2] Univ Jaume 1, Dept Comp Languages & Syst, Castellon de La Plana, Spain

来源：

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY | 2013年 / 64卷 / 09期

关键词：

credit scoring; evolutionary computation; genetic algorithms; classification; variable selection; parameter optimization; NEURAL-NETWORKS; GENETIC ALGORITHMS; RISK; CLASSIFICATION; MODELS; FUZZY; OPTIMIZATION; CLASSIFIERS; PREDICTION; BUSINESS;

D O I：

10.1057/jors.2012.145

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

The last years have seen the development of many credit scoring models for assessing the credit-worthiness of loan applicants. Traditional credit scoring methodology has involved the use of statistical and mathematical programming techniques such as discriminant analysis, linear and logistic regression, linear and quadratic programming, or decision trees. However, the importance of credit grant decisions for financial institutions has caused growing interest in using a variety of computational intelligence techniques. This paper concentrates on evolutionary computing, which is viewed as one of the most promising paradigms of computational intelligence. Taking into account the synergistic relationship between the communities of Economics and Computer Science, the aim of this paper is to summarize the most recent developments in the application of evolutionary algorithms to credit scoring by means of a thorough review of scientific articles published during the period 2000-2012.

引用

页码：1384 / 1399

页数：16

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