How a P&C broker accelerated FNOL with 25% faster processing

A leading P&C insurance broker transformed its claims intake process, moving from manual, multi-channel intake to an AI-powered, structured FNOL workflow. 

This wasn’t just about speeding up intake. It was about improving data accuracy, reducing manual effort, and ensuring claims reached carriers faster and more consistently. 

By embedding AI into intake, extraction, and routing, the organization improved both operational efficiency and client experience during critical claim moments. 

Inside the case study, you’ll see how the organization approached: 

• Capturing claim data across emails, calls, and digital forms through a unified intake layer 
• Using AI to extract and structure key claim details from unstructured inputs 
• Automating FNOL summaries and creating consistent, submission-ready claim records 
• Routing claims intelligently into carrier-specific workflows for faster processing 
• Integrating claims workflows across CRM and broker systems to improve visibility and coordination 

The result was faster FNOL submission, higher data accuracy, and a more responsive claims experience, without increasing operational overhead. 

Build a claims intake model designed for speed and accuracy 

Download the case study to see how this P&C broker improved processing speed, enhanced data quality, and delivered a better claims experience.