Name
Abstract | ||
|---|---|---|
Advancements in technology are changing the traditional way of financial transactions. The cash oriented society is transformed
into a “plastic money” society. During the last few years, credit card usage has expanded rapidly worldwide. Customers use
their cards for a number of reasons such as paying regular bills, emergencies, spontaneous spending etc. The credit cards
industry is in the growth stage of its product life cycle and it is a profitable business for banks. In this paper, based
on a data sample from a large Greek bank, we identify factors that are important for a bank’s management in order to approve
or reject an application for a credit card, while at the same time attempting to retain the institution’s clientele. We model
multivariate categorical data using the logistic regression model. To motivate our choice model we assume that the approval
of an application depends on a number of explanatory variables, and our principle objective is to understand the potential
factors that contribute in the final decision and to identify the important covariates in predicting the binary outputs. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/BF02941094 | Operational Research |
Keywords | DocType | Volume |
credit cards,logistic regression model | Journal | 4 |
Issue | ISSN | Citations |
1 | 1866-1505 | 0 |
PageRank | References | Authors |
0.34 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maria Mavri | 1 | 2 | 1.08 |
| George Ioannou | 2 | 106 | 11.99 |