Customer Churn Model – Part 2

This is part two of the multi part series where we will build a Modelshop model from scratch.  You can find the first part, here. In this video, we will build on the exploratory analysis we performed last time and use machine learning to determine the important features, weights, and cut offs for optimally predicting churn. We will also learn how to deploy that ML model and extract predictions along with confidence levels. Best of all we won’t have to write any code!

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Tom Tobin is the CEO of Modelshop. Modelshop provides a no-code platform and suite of lending models designed to accelerate automation of credit risk, origination and servicing decisions. Learn More.

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