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Assessment of Evaluation Methods for Prediction and Classifications of Consumer Risk in the Credit Industry

Assessment of Evaluation Methods for Prediction and Classifications of Consumer Risk in the Credit Industry

Satish Nargundkar, Jennifer Lewis Priestley
Copyright: © 2004 |Pages: 19
ISBN13: 9781591401766|ISBN10: 1591401763|ISBN13 Softcover: 9781591402152|EISBN13: 9781591401773
DOI: 10.4018/978-1-59140-176-6.ch014
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MLA

Nargundkar, Satish, and Jennifer Lewis Priestley. "Assessment of Evaluation Methods for Prediction and Classifications of Consumer Risk in the Credit Industry." Neural Networks in Business Forecasting, edited by G. Peter Zhang, IGI Global, 2004, pp. 266-284. https://doi.org/10.4018/978-1-59140-176-6.ch014

APA

Nargundkar, S. & Lewis Priestley, J. (2004). Assessment of Evaluation Methods for Prediction and Classifications of Consumer Risk in the Credit Industry. In G. Zhang (Ed.), Neural Networks in Business Forecasting (pp. 266-284). IGI Global. https://doi.org/10.4018/978-1-59140-176-6.ch014

Chicago

Nargundkar, Satish, and Jennifer Lewis Priestley. "Assessment of Evaluation Methods for Prediction and Classifications of Consumer Risk in the Credit Industry." In Neural Networks in Business Forecasting, edited by G. Peter Zhang, 266-284. Hershey, PA: IGI Global, 2004. https://doi.org/10.4018/978-1-59140-176-6.ch014

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Abstract

In this chapter, we examine and compare the most prevalent modeling techniques in the credit industry, Linear Discriminant Analysis, Logistic Analysis and the emerging technique of Neural Network modeling. K-S Tests and Classification Rates are typically used in the industry to measure the success in predictive classification. We examine those two methods and a third, ROC Curves, to determine if the method of evaluation has an influence on the perceived performance of the modeling technique. We found that each modeling technique has its own strengths, and a determination of the “best” depends upon the evaluation method utilized and the costs associated with misclassification.

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