Approve borrowers that other lenders are missing


Most traditional underwriting systems use fewer than 50 data points for credit decisions. The Zest Automated Machine Learning (ZAML) platform is an end-to-end underwriting solution that allows you to take advantage of machine learning and thousands of data points, at scale, and with speed and full transparency. With ZAML, you can more accurately assess thin-file and no-file borrowers—such as millennials—that traditional underwriting systems overlook.
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ZAML data assimilation connecting 4 circles representing disparate data pointsData
Assimilation

Rapidly discover, acquire, and onboard data sources at a massive scale.

Graph representing ZAML's modeling toolsModeling
Tools

Train, ensemble, and productionalize machine learning models in one streamlined workflow.

Open box representing ZAML's capability for modeling explainability Modeling Explainability

Unpack the “black box” of machine learning models to clearly communicate economic value and support compliance.

Safely grow your lending business 

 ZAML allows you to increase your approval rates by leveraging machine learning

VIEW GROWTH CASE STUDY

Cut your credit losses without losing borrowers 

ZAML allows you to improve your underwriting by leveraging machine learning

VIEW RISK CASE STUDY

ZAML data sheet 

Learn more about ZAML's offerings

VIEW ZAML DATA SHEET

Machine learning and compliance can coexist 

ZAML explainability tools help you overcome "black box" concerns of maching learning

VIEW COMPLIANCE CASE STUDY

Get started with ZAML today!

ZAML robot with hand up waving Holla!