How More Transparent Machine Learning Models Improve Credit Underwriting

We’re redefining explainability as a means to automate the entire model risk management process.

Financial institutions are moving quickly to adopt machine learning (ML) in credit underwriting, with good reason: machine learning models produce more accurate and nuanced predictions about borrower risk.

Despite their benefits, machine learning models are still wildly underused in everyday lending because most of them aren't transparent enough.

In this report, we cover:
  • The current state of ML in credit underwriting
  • How we are changing the status quo with Zest Automated Machine Learning (ZAML™)
  • How ZAML helps make compliance easy

Download your copy of "Redefining Explainable AI for Credit" today!