A regional property and casualty insurer was relying on manual document reviews that slowed claims handling and let inconsistencies slip through, contributing to incorrect payouts. Spej built a system that checks claim documents against policy terms and previous records and flags inconsistencies for a person to review. Over $100K in potential fraud flagged within weeks of deployment.
By Sean Blair, Co-Founder & Chief AI Officer, Spej.
| Client | A regional property and casualty insurer |
| Industry | Insurance |
| Results | Over $100K in potential fraud flagged within weeks of deployment. Faster, more consistent claims reviews, with a person checking flagged issues. |
The problem
Manual document reviews slowed claims handling and left inconsistencies unchecked, contributing to incorrect payouts.
What we built
A system that checks claim documents against policy terms and previous records, then flags inconsistencies for a person to review.
The results
- Over $100K in potential fraud flagged within weeks of deployment.
- Faster, more consistent claims reviews, with a person checking flagged issues.
The figure is potential fraud flagged for review, which is different from confirmed fraud or money recovered.
About this case study
We keep this client anonymous, and this page sticks to the results we have published. For a different insurance engagement, see how we built an AI operating model for a regional insurer.
If your claims team is buried in document review, book a free AI readiness call, or see Design & Build, AI implementation, managed AI platform or white-label partner, and more client work. Work with us through your MSP or advisor.
FAQ
What problem did the insurer have?
Manual document reviews slowed claims handling and left inconsistencies unchecked, which contributed to incorrect payouts.
What did Spej build?
A system that checks claim documents against policy terms and previous records, then flags inconsistencies for a person to review.
What were the results?
Over $100K in potential fraud flagged within weeks of deployment, and claims reviews became faster and more consistent, with a person checking flagged issues. Potential fraud flagged is not confirmed fraud or money recovered.
Does the AI decide claims on its own?
No. The system flags inconsistencies for a person to review.
How does a project like this start with Spej?
With a free AI readiness call, then an AI Roadmap starting at $10,000. Before each paid stage, Spej and the client agree on what success means and how it will be measured.