Subrogation

Data analytics, machine learning, and rules-based analysis help identify and validate subrogation cases. We continuously refine our case identification methodology and determine the most effective validation methods, ultimately reducing false positives and increasing yield.

Creating a positive member experience is key to your overall success. We combine data, technology, people, and processes to uncover opportunities while making member outreach as intuitive and user-friendly as possible.

As we work to identify the full scope of recovery opportunities for your health plan, we complement data analysis and machine learning with the expertise of key technology and information partners. This collaboration powers improved results in mass torts, product liabilities, and medical practice claims.

Avoiding inaccurate claims payments upfront creates true cost avoidance, allowing you to completely avoid the claim cost. Coupled with traditional subrogation recovery, pre-payment subrogation creates a holistic approach while maximizing savings, eliminating rework, and quickly identifying cases.