A note on coarse classifying in acceptance scorecards
A note on coarse classifying in acceptance scorecards
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.
credit scoring, coarse classifying, data mining, product customization
714-718
Jung, K.M.
1bdfb1c1-fec0-471c-8d0d-7244f707e3db
Thomas, L.C.
a3ce3068-328b-4bce-889f-965b0b9d2362
2008
Jung, K.M.
1bdfb1c1-fec0-471c-8d0d-7244f707e3db
Thomas, L.C.
a3ce3068-328b-4bce-889f-965b0b9d2362
Jung, K.M. and Thomas, L.C.
(2008)
A note on coarse classifying in acceptance scorecards.
Journal of the Operational Research Society, 59 (5), .
(doi:10.1057/palgrave.jors.2602358).
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.
This record has no associated files available for download.
More information
Published date: 2008
Keywords:
credit scoring, coarse classifying, data mining, product customization
Identifiers
Local EPrints ID: 51740
URI: http://eprints.soton.ac.uk/id/eprint/51740
ISSN: 0160-5682
PURE UUID: 220cecf2-1f77-4403-adf2-615a7daa8f48
Catalogue record
Date deposited: 06 Jun 2008
Last modified: 15 Mar 2024 10:18
Export record
Altmetrics
Contributors
Author:
K.M. Jung
Author:
L.C. Thomas
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics