One thing that comes up with clients is coverage, but not just coverage, the timeliness of the coverage. We’ve been collecting data in the US since 2014 so you could go to a major city where we collect 2-3 times a year and see up to 18 captures of a property. Also, finding change over time involved with any particular property.
Other providers won’t give you that rich library of imagery and the ability to understand change over time as it lacks frequency. You may find something less than a year old, but it’s not guaranteed. Our customers are in the quest to find the truth on the ground. They find that with Nearmap.
Is there anything we didn’t cover that you think Insurers need to know about Nearmap?
We’re more than just imagery. We’re equally as good at providing property intelligence through artificial intelligence (AI) driven data. When considering data-driven models and the accuracy of property intelligence, it’s always driven by the timeliness and precision of the underlying data. You can’t feed these machine learnings to produce optimal results without the most accurate data.
This accuracy relies on both the volume of data and the quality of it, too. We control our pipeline, from capture to publish, and our data is consistently high-quality and high-resolution, captured over many geographies across various points in time. The frequency and quality are ideal for driving machine learning.
You find with insurance that customers have a high appreciation for the imagery, but when it comes to automated processes, it’s the additional intelligence that drives decisions. It’s Nearmap imagery and accuracy, but also how this accurate data is used to derive true property insights and capture on-the-ground property intelligence. One insurer might be looking for a solution based on imagery needs but another may need one based on the property insights and AI variables they can gather, we bring the best of both to the party.