Paper Info
Title
A literature review on the application of evolutionary computing to credit scoring.
Abstract
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.
Year
DOI
Venue
2013
10.1057/jors.2012.145
JORS
Keywords
Field
DocType
credit scoring,evolutionary computation,genetic algorithms,classification,variable selection,parameter optimization
Data science,Decision tree,Loan,Evolutionary algorithm,Computational intelligence,Computer science,Evolutionary computation,Linear discriminant analysis,Quadratic programming,Management science,Genetic algorithm
Journal
Volume
Issue
ISSN
64
9
0160-5682
Citations 
PageRank 
References 
18
0.71
58
Authors
3
Name
Order
Citations
PageRank
A. I. Marqués120910.40
Vicente García212410.85
José Salvador Sánchez356531.62