CLIENT OVERVIEW
The client is a Fortune 500 company that sells auto, home, commercial, and life insurance.
BUSINESS CHALLENGE
The insurer’s previous subrogation identification process involved running predictive models independently of the claims system then transferring those results to claims supervisors. Deriving insights and taking action could take a month or more, and without simplified access to analytics, adjusters ran the risk of creating unnecessary work by identifying false positives for subrogation.
The insurer saw a major opportunity to reduce claims leakage, cut down on missed chances for subrogation, improve the efficiency of adjuster reviews, and ensure precision through real-time predictive insights. The claims and data teams were especially aware of how critical it was to integrate an enhanced subrogation model with its claims platform to achieve real-time data access and insights.
The insurer saw a major opportunity to reduce
claims leakage, cut down on missed chances for
subrogation, improve the efficiency of adjuster
reviews, and ensure precision through realtime predictive insights.
SOLUTION OFFERED
Having worked with its long-time strategic partner ValueMomentum on numerous other claims-related projects, the insurer chose to execute this project alongside ValueMomentum and core systems platform partners. The initiative required close collaboration between the business and IT across the 11-month timeline, from business analysis and development to integration and quality assurance (QA). The teams worked together in two-week sprints using an Agile Scrum process, which was a new way of working for the carrier.
The insurer’s claims team developed and deployed the subrogation model on cloud-based data modeling tools, then worked with ValueMomentum to integrate the machine learning model with its leading claims platform. On top of adjusting to the new way of working, integrating the machine learning model and platform with the claims system required heavy cross-collaboration across multiple internal and external teams. The project team also had to create new solutions to non-production environments and performance testing, which it did by leveraging APIs.
Auto-referred opportunities are recovering losses at a 12% higher rate and have shown a 6% greater likelihood of recovery than claims that were manually referred.
VALUE DELIVERED
The successful development and integration of the modern subrogation model simplified the carrier’s subrogation opportunity capabilities, leading to the automation of nearly 20% of subrogation referrals, a 9% reduction in overall recovery cycle time, and better productivity and efficiency for adjusters and subrogation handlers.
Through this effort, auto-referred opportunities are recovering losses at a 12% higher rate and have shown a 6% greater likelihood of recovery than claims that were manually referred. The insurer estimates this could lead to efficiency savings of as much as $6M. The integration project has also helped prepare the insurer to further integrate modern business intelligence solutions with its core platforms to drive further value across other areas.
