DocumentCode
1898257
Title
Research of SVM Applying in the Risk of Bank´s Loan to Enterprises
Author
Ma, Yinxiao ; Liu, Hong
Author_Institution
Zhejiang Gongshang Univ., Hangzhou, China
fYear
2010
fDate
25-26 Dec. 2010
Firstpage
1
Lastpage
5
Abstract
this paper presents a classification based on support vector machine (SVM) to carry out comprehensive analysis of the ability of enterprises paying debt,reduce the risk of bank to provide a loan. First this paper introduces the main principle of support vector machines to establish data classification model, using historical data for classification. Then collect the financial indices of 80 enterprises in China in 2001 to create support vector machine model for the credit risk classification for banks loan to enterprise; Finally, compared with the result of classification in the traditional Logistic regression model or the BP neural network evaluation model, this paper points out that the classification based on SVM is better than the traditional model and it could improve the classification accuracy.
Keywords
banking; credit transactions; pattern classification; risk management; support vector machines; BP neural network evaluation model; SVM; bank risk; credit risk classification; data classification model; enterprise loan; logistic regression model; support vector machine; Accuracy; Artificial neural networks; Business; Classification algorithms; Kernel; Support vector machines; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
Conference_Location
Wuhan
ISSN
2156-7379
Print_ISBN
978-1-4244-7939-9
Electronic_ISBN
2156-7379
Type
conf
DOI
10.1109/ICIECS.2010.5678225
Filename
5678225
Link To Document