Consumer Credit Risk Modeling

We analyze the performance of various machine learning algorithms, namely decision trees, random forests, and logistic regression, on predicting consumer credit delinquency. Our data included time-series transactions, credit bureau reports, and internal bank profiles for each customer. The results show that any of these methods far outstrips the current heuristic for credit delinquency, credit score, as shown in my report.