Credit card application assessment using a neuro-fuzzy classification system

Credit card application assessment using a neuro-fuzzy classification system

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Article ID: iaor20062714
Country: Spain
Volume: 11
Issue: 1
Start Page Number: 3
End Page Number: 26
Publication Date: May 2006
Journal: Fuzzy Economic Review
Authors: , ,
Keywords: fuzzy sets, economics
Abstract:

Credit cards constitute one of the most common forms of consumer loans. The main purpose of this paper is to apply fuzzy data analysis to the credit scoring problem. A neuro-fuzzy classification technique is compared to the logistic regression approach and novel machine learning algorithms that are currently being investigated as credit scoring methods. The 10-fold cross-validation procedure is performed to analyze the generalization properties and the robustness of the developed models. Neuro-fuzzy classification systems allow for prior knowledge to be imbedded in the analysis and utilize human expertise in the form of fuzzy if/then rules to provide an insight into the reasoning mechanism behind the credit approval/rejection decision. This feature is particularly useful in financial applications such as credit granting, where credit analysts should be in a position to provide an explanation for their decisions.

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