Using Decision Tree Classification Algorithm to Design and Construct the Credit Rating Model for Banking Customers

Abstract

The application of classification models in the credit rating of banking customers has been investigated in the present paper. Credit rating is one of the main applications of data mining in the banking industry. The customers' creditworthiness can be evaluated through credit ratings. The data related to banking customers is very huge, and various classification techniques can be used to explore the hidden pattern and knowledge in data set through data mining. Several studies have been performed on the use of data mining and classification techniques in the credit rating of banking customers. After preparing and preprocessing the data using the C5 decision tree algorithm in this paper, the classification model has been constructed and the credit rating of banking customers has been performed. A set of credit rating data has been used in this regard for teaching and testing the model. The results show that the developed model ranks banking customers with high accuracy by using decision tree making classification algorithms. The proposed classification model can also be used for a credit rating of new banking customers.