Name
Abstract | ||
|---|---|---|
Traditionally, in credit and behavioural scoring one assumes that as all consumers have essentially the same product, its features will not affect whether the consumer defaults or not. Hence, one coarse classifies the characteristics concentrating only on the default ratio. As products and their operational features become customized for each individual (the very purpose of acceptance scoring), then decisions like whether the customer will accept the product or not must depend on the features offered. This paper investigates how one can deal with this dependency when coarse classifying the characteristics. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1057/palgrave.jors.2602358 | JORS |
Keywords | DocType | Volume |
credit scoring,coarse classifying,data mining,product customization | Journal | 59 |
Issue | ISSN | Citations |
5 | 0160-5682 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| K. M. Jung | 1 | 9 | 2.85 |
| lyn c thomas | 2 | 107 | 15.42 |