Case Study: a mid-sized health plan achieves 91% claim prediction accuracy and recovers $24M+ with Zymr

a mid-sized health plan achieves 91% claim prediction accuracy with Zymr and recovers $24M+

The customer, a mid-sized health plan, faced challenges in optimizing its revenue cycle due to growing claim volumes, fragmented data pipelines, and limited visibility into prediction outcomes. They required a secure, governed machine learning infrastructure to support predictive analytics while maintaining healthcare compliance. To address this, they partnered with vendor Zymr for a production-ready AI platform.

Zymr implemented a HIPAA-compliant machine learning infrastructure with automated data pipelines, governance frameworks, and explainability controls. The solution processed 4.1 million claims and achieved 91% prediction accuracy. This enabled an operational recovery of over $24 million for the health plan and accelerated model deployment cycles.