Credit Risk Prediction in Commercial Bank Using Chi-Square with SVM-RBF
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Date
2020-11-24
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Nature Switzerland
Abstract
Financial credit risk analysis management has been a foremost influence with a lot of challenges, especially for banks reducing their principal loss. AQ1
In this study, the machine learning technique is a promising area used for credit
scoring for analyzing risks in banks. It has become critical to extract beneficial
knowledge for a great number of complex datasets. In this study, a machine learning
approach using Chi-Square with SVM-RBF classifier was analyzed for Taiwan
bank credit data. The model provides important information with enhanced accuracy that will help in predicting loan status. The experiment achieves 93% accuracy
compared to the state-of-the-art.
Keywords: Credit risk · Chi-square · SVM · Bank · Machine learning