How to save millions using credit risk prediction with machine learning

Financially interpreting machine learning models for credit risk

Photo by Alexander Mils on Unsplash

Financial institutes can save millions by using credit risk prediction using machine learning. This blog will focus on financially interpreting credit risk machine learning models. The techniques for credit risk prediction using machine learning models are well known. However successful implementation requires translating the model into financial results.

To illustrate the blog, I will take a dataset on credit risk. The data has information about the person who has taken the loan, the kind of assets, the profession, and the loan amount. The defaulter flag equals one if the loan has not been repaid.

Credit risk sample dataset (image by author)

Process for financial interpretation

In order to financially interpret the machine learning results, one can follow the process shown here.

Financial interpretation process (image by author)