This tutorial will take a structured approach to analyze credit risk data:

• First, we will explore a real credit risk data set, discuss some of the properties, and take an in-depth look at some of the variables
• Second, we will build a logistic regression model to predict loan default.
• As a third step, some machine learning methods such as decision trees will be explored.
• Next, we’ll be looking at how survival analysis can be used to analyze loan default. The advantage of this method is that the timing of default can be modeled. Unlike the other methods discussed, these method focuses on when default will happen and not whether it will happen.
• We’ll end the tutorial with a discussion on how to evaluate the performance of the methods covered.