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A Two-step Method to Construct Credit Scoring Models with Data Mining Techniques
International Journal of Business and Information
View Archive Info| Field | Value | |
| Title |
A Two-step Method to Construct Credit Scoring Models with Data Mining Techniques
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| Creator |
Koh, Hian Chye
Tan, Wei Chin Goh, Chwee Peng |
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| Description |
Credit scoring can be defined as a technique that helps credit providers decide whether to grant credit to consumers or customers. Its increasing importance can be seen from the growing popularity and application of credit scoring in consumer credit. There are advantages not only to construct effective credit scoring models to help improve the bottom-line of credit providers, but also to combine models to yield a better performing combined model. This paper has two objectives. First, it illustrates the use of data mining techniques to construct credit scoring models. Second, it illustrates the combination of credit scoring models to give a superior final model. The paper also highlights the prerequisites and limitations of the data mining approach.
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| Publisher |
International Business Academics Consortium
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| Date |
2015-11-12
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| Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion Peer-reviewed Article |
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| Format |
application/msword
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| Identifier |
https://ijbi.org/ijbi/article/view/5
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| Source |
International Journal of Business and Information; Vol 1 No 1 (2006)
2520-0151 1728-8673 |
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| Language |
eng
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| Relation |
https://ijbi.org/ijbi/article/view/5/6
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| Rights |
Copyright (c) 2015 International Journal of Business and Information
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