An integrated data mining model for customer credit evaluation

Authors:
Kap Sik Kim;Ha Jin Hwang
Affiliations:
Department of Computer Information Science, Daegu Polytechnic College, Daegu, Korea;Department of Management, Catholic University of Daegu, Kyungbuk, Korea
Venue:
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part III
Year:
2005

Citing 6
Cited 0

The Bierman-Hausman credit granting model: a note

Management Science
A database perspective on knowledge discovery

Communications of the ACM
Neural network applications in business: a review and analysis of the literature (1988-95)

Decision Support Systems
Neural network credit scoring models

Computers and Operations Research - Neural networks in business
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Performance evaluation of neural network decision models

Journal of Management Information Systems - Special section: Strategic and competitive information systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Based on the customer information relating to details of financing and payment histories from a financial institution, this study derived single data mining models using MLP, MDA, and DTM. The results obtained from these single models were subsequently compared with the results from an integrated model developed using GA. 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 data mining model using GA.