Neural fraud detection in credit card operations

Author

Dorronsoro, José R. ; Ginel, Francisco ; Sgnchez, C. ; Cruz, Carlos Santa

Author_Institution

Dept. of Comput. Eng., Univ. Autonoma de Madrid, Spain

Volume

8

Issue

4

fYear

1997

fDate

7/1/1997 12:00:00 AM

Firstpage

827

Lastpage

834

Abstract

This paper presents an online system for fraud detection of credit card operations based on a neural classifier. Since it is installed in a transactional hub for operation distribution, and not on a card-issuing institution, it acts solely on the information of the operation to be rated and of its immediate previous history, and not on historic databases of past cardholder activities. Among the main characteristics of credit card traffic are the great imbalance between proper and fraudulent operations, and a great degree of mixing between both. To ensure proper model construction, a nonlinear version of Fisher´s discriminant analysis, which adequately separates a good proportion of fraudulent operations away from other closer to normal traffic, has been used. The system is fully operational and currently handles more than 12 million operations per year with very satisfactory results

Keywords

financial data processing; fraud; neural nets; pattern classification; plastic cards; credit card operations; credit card traffic; discriminant analysis; neural classifier; neural fraud detection; operation distribution; transactional hub; Acoustic applications; Concrete; Credit cards; Finance; History; Insurance; Neural networks; Telecommunication traffic; Traffic control; Transaction databases;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/72.595879

Filename

595879