Predicting Credit Card Customer Loyalty Using Artificial Neural Networks

DOI

10.2991/jcis.2008.80How to use a DOI?

Keywords

credit card, customer loyalty, neural networks, rule extraction

Abstract

Customer loyalty is one of the key factors in customer retention and segmentation. However, quantitative research in this area based on non-subjective data has been rare in the literature. This paper shows how back propagation neural networks can be used to predict the loyalty level of credit card customers based on transaction records. In the meantime, a set of decision rules are also extracted from the trained neural networks in order to improve the clarity and explicability of the loyalty model.

Copyright

© 2008, 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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TY  - CONF
AU  - Tao Zhang
AU  - Bo Yuan
AU  - Wenhuang Liu
PY  - 2008/12
DA  - 2008/12
TI  - Predicting Credit Card Customer Loyalty Using Artificial Neural Networks
BT  - Proceedings of the 11th Joint Conference on Information Sciences (JCIS 2008)
PB  - Atlantis Press
SP  - 469
EP  - 474
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2008.80
DO  - 10.2991/jcis.2008.80
ID  - Zhang2008/12
ER  -