In order to avoid the loss caused by defaulting on credit cards bill payment, the risk management on credit card default has been acting an imporant role in bank. Through the analysis of the user's personal profile and historical bills, we want find the reason why clients defalut on their July Statement and find the best model for predicting users' July Payment Status.
Among the algorithms used, K-Nearest Neigbor (k=9) gave a higher accuracy, which about 82%. However, the model only uses high-correlation variables to train the model, we still can improve our model through other feature variables.