Summary: Fleets already capture the telematics data that would make commercial auto claims faster and cheaper. But that data almost never reaches the adjuster who needs it. One insurer closed that gap and saw days-to-first-payment improve by 24.5 days and FNOL completion rates hit 85%. The fix is a translation layer between the major telematics providers and the claims workflow. For Guidewire carriers, this is open whitespace.
Fleets generate millions of telematics data points every day. Speed, location, harsh braking events, G-force readings, dashcam footage, engine diagnostics. The data exists. The sensors are installed. The telematics providers are transmitting.
And yet, when a commercial vehicle is involved in an incident, the claims handler on the other end of the phone is often working with a handwritten description, a couple of blurry photos, and a form that is missing half its fields.
This is the visibility gap. The data that could resolve a claim in days sits in a telematics platform that the insurer has no connection to. The result is slower settlements, higher costs, and worse outcomes for everyone involved.
J.D. Power’s 2025 U.S. Commercial Lines Insurance Study found that 55% of small commercial insurance customers do not plan to renew with their current carrier. The primary driver? Claims experience. Customers who had a poor claims experience were significantly more likely to shop for a new insurer.
For commercial auto, this is especially painful. The data that would make claims faster, more accurate, and less adversarial already exists inside the fleet’s telematics system. But there is no pipeline connecting that data to the adjuster who needs it.
Consider what happens today when a commercial vehicle is involved in a crash:
The information asymmetry here is staggering. One side of the equation has rich, timestamped, sensor-verified data. The other side is working from a phone call.
Three structural problems keep telematics data from reaching claims teams.
Different systems, different owners. Telematics platforms are purchased by fleet operations teams. Claims systems are managed by insurers. These two groups rarely share tools, logins, or data standards. The fleet safety director and the insurance adjuster may never interact directly.
No standard format for incident data. Every telematics provider structures crash event data differently. Geotab’s crash record looks nothing like Samsara’s, which looks nothing like Lytx’s. An insurer who wants to ingest telematics data would need to build and maintain integrations with dozens of providers, each with its own API, data schema, and update cycle.
Manual processes fill the gap (badly). In the absence of automated data flow, the fallback is people. One large insurer maintains an entire offshore team whose job is to manually re-enter incident data from one system into another. The cost runs into hundreds of thousands of dollars per year. The error rate is exactly what you would expect from humans copying data between screens.
When telematics data flows directly into the claims process, the effects are measurable and immediate.
Faster first payment. One global insurer that connected telematics data to their claims workflow saw days-to-first-payment improve by 24.5 days. That acceleration matters to injured parties, to policyholders, and to the insurer’s own loss adjustment expense.
Higher data quality at intake. Structured, sensor-verified incident data produces dramatically better FNOL records. The same insurer achieved an 85% FNOL completion rate, meaning that 85 out of 100 claims arrived with all required fields populated and verified. Compare that to the industry norm, where missing data, incorrect details, and incomplete forms are the rule.
Lower investigation costs. When the incident record includes GPS coordinates, speed data, G-force readings, and dashcam footage from the moment of impact, there is far less need for expensive field investigations. The reconstruction is already done.
Faster claim registration. Another carrier that implemented structured incident data capture saw claim registration times drop by 30%. They validated this through their own controlled test: a set of claims processed the old way against a matched set processed with structured incident data. The 30% improvement was their finding, not the vendor’s.
Closing the visibility gap requires solving the telematics fragmentation problem. There are dozens of telematics providers in the commercial fleet market, though roughly ten cover the majority of the installed base. Each has a different API, a different data model, and a different approach to crash event detection.
Building one integration is a project. Building fifty is a platform decision.
This is why the most effective approach is a translation layer that sits between telematics providers and claims systems. Rather than asking insurers to build individual connections to Geotab, Samsara, Lytx, Motive, and dozens of others, a purpose-built integration layer normalizes all of that data into a consistent, claims-ready format.
For insurers running Guidewire, this is particularly relevant. Guidewire’s core platform handles policy, billing, and claims management. But Guidewire does not have a native telematics integration for commercial lines. That whitespace represents both a gap in capability and an opportunity for carriers who want to differentiate on claims experience.
The visibility gap is not a technology problem. The technology exists on both sides. Telematics platforms capture the data. Claims systems can process it. The problem is the space between them.
It is worth noting that moving data is not the same as making it useful. Data exchanges exist that can pass raw telematics feeds between systems. But raw GPS logs and accelerometer readings do not help a claims handler. What matters is structured, enriched incident data: a verified crash event with location, speed, severity, fault indicators, and supporting footage, delivered in a format the claims system can act on. The difference between a data pipe and an insight layer is the difference between giving an adjuster a data dump and giving them an answer.
Closing that gap produces measurable improvements in speed, cost, and accuracy. It also produces something harder to quantify but equally important: a claims experience that retains customers instead of driving them to shop.
For carriers evaluating their commercial lines strategy, the question is straightforward. Your policyholders’ fleets are already generating the data that would make your claims process faster and more accurate. The only question is whether you have a way to get that data to the people who need it.
Xtract connects telematics data from the leading providers directly to the claims workflow, giving insurers structured, verified incident data from the moment of impact. Learn more at xtract360.com
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