In a successful trial, Discover and Zest found that the inclusion of more data and more sophisticated math reduced default rates significantly with no portfolio risk.
ZAML helps you make more accurate assessments of borrower risk across the credit spectrum and opens up new channels and markets by reducing the risk of making loans in areas where you have a limited track record.
ZAML helps you build models with much higher precision so you can eliminate bad borrowers and slash charge-off rates while keeping approvals steady.
ZAML tools help you maximize the value of your datasets by finding new sources of predictive power for underwriting. Outpace your competitors by incorporating thousands of variables to better assess risk.
A leading e-commerce company wanted to extend credit to its customers, but lacked the expertise and data. It turned to Zest to build a new machine learning underwriting model to accurately score consumers that lack a traditional credit profile.
Are you ready to expand your consumer lending business with the power of machine learning?