The NineHertz partnered with an insurance carrier based in the USA that offers insurance in multiple domains, like property, auto, and liability, to businesses as well as individuals. The firm used to manage the entire claim management process through manual review. As the claim volume increased, the service quality impacted and processes became longer.
The client needed to upgrade its legacy claim management system that could better analyze the policyholder needs, suggest insurance, analyze claim documents, and automate the FNOL intake and routing process. At the same time, a new solution needed to bring real-time visibility for the end customers to establish trust.
The biggest challenge was slow and manual processing, where it took days to review claim forms, cross-reference policy coverages, route claims to concerned persons, and validate the supporting documents. At the same time, the limited fraud detection capability consumed more than 3-4 hours for the adjuster for each claim to ensure that the submitted claim is not subject to any discrepancy or policy breach.
Fragmented documentation workflow was another challenge, as different documents like repair estimations, photographs, police reports, and hospital bills were received in different formats. Also, policyholders had no visibility into their claim process and only received update status when called in multiple times.
The NineHertz built a next-generation claim management solution that automates the repetitive tasks, reduces discrepancies, and brings a unified dashboard for easy data access.
Our team built an NLP-based FNOL intake engine that can extract the information from various sources like web forms, emails, mobile submissions, and call transcripts. Thus, the information can be cross-referenced in no time without human intervention.
Our system consisted of a smart document processing platform that ingests data in various formats like PDFs, images, and scanned documents. It extracts the structured data so that the adjuster receives a pre-populated claim file.
We integrated a dedicated fraud detection module that processes every incoming claim based on historical fraud patterns. It can flag anomalies through damage inconsistency, claim frequency, timing, and customer behavior.
To ensure that customers don’t have to wait for a human support agent for minor queries or updates, we integrated an automated customer communication layer that sends real time notification and alerts to the policyholder at each stage of the claim lifecycle.
The AI-powered claim automation platform brought measurable results within a year of implementation, as customer experience was enhanced and operational economics got more structured.
Claims tasks such as routing, document processing, and FNOL intake used to take over 14 days but are now completed in less than 8 days. Low complexity claims do not get resolved within a 24-hour period after they have been submitted.
In 6 months, the customer satisfaction score increased from 55 to 81 due to quicker resolution, fewer documentation disputes, and timely updates on status.
The new fraud detection module flagged 3.2✕ more high-risk claims within the first quarter. The fraud loss money saved through the system exceeded the total cost of new platform implementation in less than a year.
Automation of tasks like documentation processing and claim routing reduced the operational costs by 38%. The adjusted capacity was not diverted toward more complex claims, ultimately increasing productivity and operational flow without adding headcounts.
