Five-Category Classification Prediction for “Three Rural” Loan Risk Based on Support Vector Machine

Based on the data mining method, Support Vector Machine technology, Correlated Analytical Variable Selection method and Principal Component Analytical Variable Dimension Reduction method, setting five-category classification and prediction model for “Three rural” loan risk of commercial bank, then make classification prediction for an Agricultural Bank of China in Changsha and verify the outcome through this prediction model, and make comparative analysis with the classification prediction accuracy of neural network and the time consumed for processing, the advantage of this method is obvious. This five-category classification and prediction model for loan risk have great meanings for bank to establish more robust customer relationship management system and attract more high-quality customer resources.