Title :
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
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;
Conference_Titel :
Natural Computation (ICNC), 2014 10th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4799-5150-5
DOI :
10.1109/ICNC.2014.6975914
