Case Study: Major Auto Lender achieves 60% increase in automated decisioning and 40% decrease in charge-offs with Zest AI

The comprehensiveness of manual underwriting now available automatically

Major Auto Lender faced slow, resource‑heavy manual underwriting and a need to scale consistent credit decisions within its existing LOS. They turned to Zest AI for automated decisioning powered by machine‑learning models to replicate comprehensive manual underwriting at scale.

Zest AI used thousands of historical borrower data points to produce instant scores and reason codes, enabling more accurate auto‑approve and auto‑decline thresholds and reducing the need for manual reviews. The Zest AI models drove a 60% increase in automated decisioning and a 40% decrease in charge‑offs, while delivering faster, more consistent underwriting and saving underwriters for the most complex cases.