A Markov Decision Model for Selecting Optimal Credit Control Policies
AbstractThe rapid growth of consumer credit has created a need for improved credit control policies which result in lower total credit costs. This paper investigates one approach for achieving that objective. The credit control problem is formulated as one of developing optimal policies for an infinite horizon Markov decision model. The model utilizes standard financial data; it also requires the measurement of the costs and returns from alternative credit control policies. The Markov model is transformed into an equivalent linear program. A sample problem is solved and the resulting policies analyzed.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by INFORMS in its journal Management Science.
Volume (Year): 18 (1972)
Issue (Month): 10 (June)
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Robert Till & David Hand, 2003. "Behavioural models of credit card usage," Journal of Applied Statistics, Taylor and Francis Journals, vol. 30(10), pages 1201-1220.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.