Factors Affecting Credit Card Users’ Potential in Maintaining Good Credit Standing

Abstract

The risk of a credit card user going into more than 30 days of debt and hence going into bad credit standing leaves to be a concern for both the user and credit card providers, but there could be multiple factors and reasons why would a person breaks agreements and go out of good credit standing. Using exploratory data analysis, the paper examines a Kaggle credit card dataset to examine and identify if a credit card user or applicant can maintain a good credit standing based on their user information. Multiple different affecting factors were found, identified, and classified if it has good correlation, weak correlation, or no correlation to good credit standing. The correlating factors are recommended to be potentially fed into a regression model to be able to predict users at risk of being in bad credit standing.