DocumentCode
3136288
Title
Application of Classification Models on Credit Card Fraud Detection
Author
Shen, Aihua ; Tong, Rencheng ; Deng, Yaochen
Author_Institution
Graduate Univ. of the Chinese Acad. of Sci., Beijing
fYear
2007
fDate
9-11 June 2007
Firstpage
1
Lastpage
4
Abstract
Along with the great increase in credit card transactions, credit card fraud has become increasingly rampant in recent years. This study investigates the efficacy of applying classification models to credit card fraud detection problems. Three different classification methods, i.e. decision tree, neural networks and logistic regression are tested for their applicability in fraud detections. This paper provides a useful framework to choose the best model to recognize the credit card fraud risk.
Keywords
credit transactions; decision trees; neural nets; regression analysis; classification methods; credit card fraud detection; credit card transactions; decision tree; logistic regression; neural networks; Business; Classification tree analysis; Credit cards; Decision trees; Logistics; Neural networks; Regression tree analysis; Risk management; Testing; Transaction databases; Classification models; Credit card fraud detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Service Systems and Service Management, 2007 International Conference on
Conference_Location
Chengdu
Print_ISBN
1-4244-0885-7
Electronic_ISBN
1-4244-0885-7
Type
conf
DOI
10.1109/ICSSSM.2007.4280163
Filename
4280163
Link To Document