A multi-layer perceptron model of credit scoring.
In this study, a Multi-Layer Perceptron (MLP), one of several neural network architectures, is used to construct a credit-scoring model for the prediction of credit card applicants' credit-worthiness. There are three types of applicant characteristics that affect credit-worthiness. They are c...
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| Main Authors: | , , |
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| Other Authors: | |
| Format: | Theses and Dissertations |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/42786 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | In this study, a Multi-Layer Perceptron (MLP), one of several neural network
architectures, is used to construct a credit-scoring model for the prediction of credit card applicants' credit-worthiness.
There are three types of applicant characteristics that affect credit-worthiness. They are character, capacity and capital. Each characteristic has its input variables and the ones selected for character are Education, Sex, Age and Marital Status. The input variables
selected for capacity are Total Income, Occupation, Years in Service, Number of
Dependents and Number of Cards Held. Those for capital are Home Ownership and Number of Bank Accounts. |
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