Applications of artificial intelligence technologies in credit scoring: A survey of literature

Author

Chen, Bing ; Zeng, W. ; Lin, Yashen

Author_Institution

Software Sch., Xiamen Univ., Xiamen, China

fYear

2014

fDate

19-21 Aug. 2014

Firstpage

658

Lastpage

664

Abstract

Credit scoring is becoming a competitive issue with rapid growth and significant advance. Building a satisfactory credit model has attracted lots of researchers in the past decades and it is still one of the hottest research topics in the field of credit industry. This paper emphasizes on surveying the development of the artificial intelligence technologies for solving credit scoring. It covers algorithms including the support vector machines, artificial neural networks, genetic algorithms, genetic programming algorithms and their hybridization.

Keywords

artificial intelligence; financial data processing; genetic algorithms; neural nets; support vector machines; artificial intelligence technology; artificial neural networks; credit industry; credit scoring; genetic algorithms; genetic programming algorithms; satisfactory credit model; support vector machines; Accuracy; Artificial intelligence; Artificial neural networks; Classification algorithms; Genetic algorithms; Support vector machines; artificial neural networks; credit scoring; genetic algorithms; genetic programming; support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2014 10th International Conference on

Conference_Location

Xiamen

Print_ISBN

978-1-4799-5150-5

Type

conf

DOI

10.1109/ICNC.2014.6975914

Filename

6975914