Predicting Credit Paying Ability With Machine Learning Algorithms

Most people still have difficulty accessing finance because of a lack or even no credit history. This study aims to develop data model that predicts customer's ability pay from various aspects other than uses the CRSIP-DM (Cross Industry Standard Process Model for Data mining) method. The used in this is Home Credit Default Risk dataset collected by documentation techniques. were then analyzed using modeling analysis techniques, namely logistic regressor, decision tree classifier, random forest and lgbm classifier. found best predicting client payment classifier Random Forest Classifier.