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Default Probability Prediction of Credit Applicants Using a New Fuzzy KNN Method with Optimal Weights

Default Probability Prediction of Credit Applicants Using a New Fuzzy KNN Method with Optimal Weights

Abbas Keramati, Niloofar Yousefi, Amin Omidvar
Copyright: © 2015 |Pages: 37
ISBN13: 9781466672727|ISBN10: 1466672722|EISBN13: 9781466672734
DOI: 10.4018/978-1-4666-7272-7.ch024
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MLA

Keramati, Abbas, et al. "Default Probability Prediction of Credit Applicants Using a New Fuzzy KNN Method with Optimal Weights." Handbook of Research on Organizational Transformations through Big Data Analytics, edited by Madjid Tavana and Kartikeya Puranam, IGI Global, 2015, pp. 429-465. https://doi.org/10.4018/978-1-4666-7272-7.ch024

APA

Keramati, A., Yousefi, N., & Omidvar, A. (2015). Default Probability Prediction of Credit Applicants Using a New Fuzzy KNN Method with Optimal Weights. In M. Tavana & K. Puranam (Eds.), Handbook of Research on Organizational Transformations through Big Data Analytics (pp. 429-465). IGI Global. https://doi.org/10.4018/978-1-4666-7272-7.ch024

Chicago

Keramati, Abbas, Niloofar Yousefi, and Amin Omidvar. "Default Probability Prediction of Credit Applicants Using a New Fuzzy KNN Method with Optimal Weights." In Handbook of Research on Organizational Transformations through Big Data Analytics, edited by Madjid Tavana and Kartikeya Puranam, 429-465. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-7272-7.ch024

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Abstract

Credit scoring has become a very important issue due to the recent growth of the credit industry. As the first objective, this chapter provides an academic database of literature between and proposes a classification scheme to classify the articles. The second objective of this chapter is to suggest the employing of the Optimally Weighted Fuzzy K-Nearest Neighbor (OWFKNN) algorithm for credit scoring. To show the performance of this method, two real world datasets from UCI database are used. In classification task, the empirical results demonstrate that the OWFKNN outperforms the conventional KNN and fuzzy KNN methods and also other methods. In the predictive accuracy of probability of default, the OWFKNN also show the best performance among the other methods. The results in this chapter suggest that the OWFKNN approach is mostly effective in estimating default probabilities and is a promising method to the fields of classification.

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