Walking the floor at InsureTech in Las Vegas this year, there was a resounding theme around the power of quality, accurate data in insurance workflows, and the question everyone’s asking everywhere: where does AI fit in all of this?
From how we segment leads to how we assess risk, data and AI are the driving forces reshaping every stage of the policy lifecycle. Models are emerging, and they are emerging quickly. They can not only predict who’s most likely to convert into a paying customer but also evaluate mortality risk in life insurance or quantify policy-level exposure in commercial auto with confidence.
What’s even more exciting is how this intelligence is closing the gap between marketing, underwriting, and claims - turning once-siloed processes into a single, data-driven ecosystem.
And nowhere is that more visible than in lead segmentation.
Insurers spend roughly 7–8% of revenue on marketing - about $10–11 billion a year across the industry. But, only around 1.7% of leads actually convert to a policy. That’s a lot of money being thrown at a lot of people in hopes of a bite. By using risk data to understand the human behind a lead and how they score on risk, carriers can focus on the right prospects, improve conversion rates, and connect marketing dollars directly to underwriting value.
The impact of better data doesn’t stop at marketing—it carries through every step of the insurance journey, starting with how we quote and underwrite.
Our most popular visitors at the booth were life carriers hungry at the sight of “new data.” Everyone we spoke with had that nagging feeling in their gut that there “has to be a better way.” If data was written on your booth, this group was ready to talk.
Most life carriers still rely on expensive MVRs and criminal reports that only tell part of the story. MVRs are costly and don't provide nationwide data, while other court data sources often don’t update regularly and exclude arrest information. All important signals that can highlight risk long before a claim ever occurs.
The result is underwriting teams working with incomplete insights and marketing teams chasing volume instead of precision.
We see the same challenge play out in the commercial auto sector.
Carriers often quote and bind policies with limited visibility into the full driver population. On average, only about 25% of drivers in a policy are actually screened using MVRs, leaving a major blind spot in risk assessment. That lack of visibility translates to higher loss ratios and missed opportunities to price policies accurately. Commercial auto insurance is feeling this the most.
AI may be the buzz, but accuracy is the breakthrough. The carriers who invest in the truth behind their data will be the ones who turn insight into impact.