Developing Credit Scoring Models for Banking and Beyond

Editor’s note: Aric LaBarr is a speaker for ODSC East this April 23–25. Be sure to check out his talk, “Developing Credit Scoring Models for Banking and Beyond,” there!

The interpretability of machine learning models is paramount in many industries. From credit-worthiness to insurance claims, and anti-money laundering to readmittance to a hospital, getting end-users to understand the output of analytical models can be a challenge. Why is interpretability so important? Interpretability promotes understanding. In turn, understanding promotes …

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