Behavioural models of credit card usage
Robert Till and
David Hand
Journal of Applied Statistics, 2003, vol. 30, issue 10, 1201-1220
Abstract:
Behavioural models characterize the way customers behave in their use of a credit product. In this paper, we examine repayment and transaction behaviour with credit cards. In particular, we describe the development of Markov chain models for late repayment, investigate the extent to which there are different classes of behaviour pattern, and explore the extent to which distinct behaviours can be predicted. We also develop overall models for transaction time distributions. Once such models have been built to summarize the data, they can be used to predict likely future behaviour, and can also serve as the basis of predictions of what one might expect when economic circumstances change.
Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/0266476032000107196 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:30:y:2003:i:10:p:1201-1220
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20
DOI: 10.1080/0266476032000107196
Access Statistics for this article
Journal of Applied Statistics is currently edited by Robert Aykroyd
More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().