Application of Decision Trees in Mining High-Value Credit Card Customers
Jian Wang1, Bo Yuan, Wenhuang Liu
1Graduate School at Shenzhen, Tsinghua University, P.R. China
Available Online December 2008.
- 10.2991/jcis.2008.79How to use a DOI?
- credit card; customer value; decision tree model; lift curve
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.
- © 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/).
Cite this article
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 -