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Conference Paper
An Integrated Approach Using Data Mining & Genetic Algorithm in Customer Credit Risk Prediction of e-Banking
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- Authors
- Yeong Wha Sawng, Soo Cheon Kweon, Seung Ho Kim
- Issue Date
- 2006-05
- Citation
- International Symposium on Collaborative Technologies and Systems (CTS) 2006, pp.1-7
- Language
- English
- Type
- Conference Paper
- Abstract
- Based on customer information, data relating to details of financing and payment histories from a financial institution, we derived single models using multilayer perceptions model(MLP), multiple discriminant analysis(MDA), and decision tree model(DTM). The results obtained from these single models were subsequently compared with the results from an integrated model that was developed using genetic algorithm. This study not only verifies existing single models and but also attempts to overcome the limitations of these approaches. While our comparative analysis of single models for the purpose of identifying the best-fit model relies upon existing techniques, this study presents a new methodology to build an integrated approach using data mining and genetic algorithm.
- KSP Keywords
- Comparative analysis, Data mining(DM), Decision Tree(DT), Decision tree model, Financial institution, Integrated models, New methodology, Risk prediction, an integrated approach, credit risk, customer information