Intelligent Credit Service Risk Predicting System Based on Customer’s Behavior By Using Machine Learning

This paper presents a model for predicting the behavior of customers in an intelligent manner in the form of customer credit risk for use in decision making for executives in business organizations by applying management's decision to credit corporate customers by machine learning techniques. Machine learning techniques, which are important technique that are the heart of artificial intelligence (Ai). A decision Tree model that is analyzed for credit business customers in business organizations which consists of six attributes, the number customers of 1,100 records. The risk is classified into three classes, namely, low, medium and high. Our model analysis can be done with accuracy of 85.82% of the customer genius in the form of risk to credit customers of the trading organization that has been developed to support the decision making of executives more quickly and more effectively.