Predictive Risk Categorization of Retail Bank Loans Using Data Mining Techniques
Keywords:
Data Mining, Loan Prediction, Classification Algorithm, Credit Risk Assessment and J48 AlgorithmAbstract
In the present highly competitive environment of the banking industry, reducing default and preventing NPA loans in retail banking is a major challenge. Data mining techniques are already popular in different banking sectors for mining important information to discover knowledge that can be used for marketing, analysis and predictive purpose for tremendous available data of already existing customers. We are using classification algorithms SVM, CART, j48 algorithm for predicting risk and then categorization of loan customer into any of three risk categories i.e ‘low risk’, ’medium risk’ and ‘high risk’. The risk category of customer will be used as a suggestive indicator for customization of the repayment schedule and follow up procedure required.
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