Fenris adds data tools to speed insurer quoting and underwriting

Fenris pushed deeper into the front end of insurance workflows with new data tools built to reduce the form-filling that slows quotes, triggers agent rekeying, and leaves underwriting teams cleaning up bad intake later. The Richmond, Virginia-based company said the launch extends its real-time prefill and enrichment stack and is aimed at carriers, agencies, brokers, underwriters, and technology platforms that already rely on its data.

The company unveiled Plate-to-VIN, Auto Prefill for Additional Household Drivers, and Roof Replacement Cost intelligence on June 3. Plate-to-VIN can generate vehicle details from just a license plate and state, which can trim applications that stall when shoppers do not want to hunt down a VIN. Auto Prefill for Additional Household Drivers widens the picture beyond the primary applicant, a practical fix for households where more than one driver affects the risk profile. On the property side, Roof Replacement Cost intelligence returns estimated roof replacement cost ranges along with roof material and roof area insights for residential workflows, giving underwriters more to work with before a file ever reaches manual review.

Fenris is betting that the payoff starts before bind and compounds after it. FinTech Global research from May 2026 found that 84% of insurance leads abandon quotes before completion, the highest abandonment rate across sectors. Fenris’ argument is straightforward: when accurate driver, vehicle, and property data arrives earlier, applicants face less friction, agents spend less time rekeying, and carriers get cleaner submissions with fewer follow-up questions. That is where the real ROI sits inside carrier systems, in faster bind rates, lower acquisition cost, and better data quality going into underwriting.

The launch also fits a broader stack Fenris has been building since 2016. The company says tens of millions of insurance transactions per year rely on its predictive technology, and its existing auto data services can already return drivers, vehicles, VINs, driver’s license details, and driving history. Its property data can surface building characteristics such as square footage, hazards and perils, and structure replacement cost estimates. Fenris also previously positioned Driver Record Insight to close the pre-underwriting gap around undisclosed driving violations and accidents. In that context, the new tools look less like a pivot than a sharper layer on top of an existing enrichment engine, one meant to improve completion rates first and underwriting precision second.