Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)

Fraud detection model & application for credit card acquiring business based on data mining technology

Authors
Tiebin Liu, Shiping Liu
Corresponding Author
Tiebin Liu
Available Online December 2016.
DOI
10.2991/iceeecs-16.2016.185How to use a DOI?
Keywords
data mining; credit card acquiring; anti-fraud
Abstract

Large quantities of fake card transactions bring about huge risks to commercial banks' credit acquiring business, this paper uses data mining technology to build credit card acquiring fraud analysis model based on mass credit card transaction data and merchant materials, and also developed merchant fraud risk management system. The application of this system effectively reduces the frequency of fraudulent credit card transactions, and helps to minimize losses from merchant's fraud.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
Series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
10.2991/iceeecs-16.2016.185
ISSN
2352-538X
DOI
10.2991/iceeecs-16.2016.185How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Tiebin Liu
AU  - Shiping Liu
PY  - 2016/12
DA  - 2016/12
TI  - Fraud detection model & application for credit card acquiring business based on data mining technology
BT  - Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
PB  - Atlantis Press
SP  - 963
EP  - 967
SN  - 2352-538X
UR  - https://doi.org/10.2991/iceeecs-16.2016.185
DO  - 10.2991/iceeecs-16.2016.185
ID  - Liu2016/12
ER  -