Application of Decision Trees in Mining High-Value Credit Card Customers

DOI

10.2991/jcis.2008.79How to use a DOI?

Keywords

credit card; customer value; decision tree model; lift curve

Abstract

Along with the rapid growth of credit card market in China, each bank has al-ready accumulated a large number of cus-tomers. Since it is well known that the majority of the profit usually comes from a small portion of the customers, how to identify high-value customers is an im-portant issue to be addressed in the bank-ing industry. The purpose of this paper is to show how a popular data mining model can be used to help banks predict highly profitable customers based on just a few customer attributes.

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  - Jian Wang
AU  - Bo Yuan
AU  - Wenhuang Liu
PY  - 2008/12
DA  - 2008/12
TI  - Application of Decision Trees in Mining High-Value Credit Card Customers
BT  - Proceedings of the 11th Joint Conference on Information Sciences (JCIS 2008)
PB  - Atlantis Press
SP  - 464
EP  - 468
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2008.79
DO  - 10.2991/jcis.2008.79
ID  - Wang2008/12
ER  -