Tapping Into the Geospatial Goldmine
The rise in geospatial imagery and data has insurers looking past the challenges to tap into its potential. Here are two ways to do so.
As geospatial data becomes more available, technology is beginning to catch up. The location-specific intelligence makes use of everything from census data, weather data and different types of imagery, and all can be applied across the entire insurance policy lifecycle. Still, “with more data comes more challenges,” said Ashish Hingrajia, solution product manager at Nearmap, during a live webcast on the future of geospatial and insured losses.
“Insurers find themselves wondering, ‘How do we use all this data to our advantage? What’s its importance and relevance?’” In part, advancements in AI have streamlined the analysis of this information. Hingrajia pointed to two key use cases – responding after a catastrophic event and providing intelligence to mitigate future claims – where quality geospatial imagery and analytics can prove their value to insurers.
A valuable tool for post-catastrophe response
One use case for all this geospatial data is in insurers’ post-catastrophe strategy. The frequency and severity of weather events and natural catastrophes have increased significantly over the years, hobbling entire communities and costing insurers billions of dollars.
Geospatial data, like aerial imagery gathered from fixed-wing aircraft (which, in contrast to satellite, stratospheric balloon or drone imagery, balances great resolution with affordable frequent image capture) provides insurers with insights complementary to information gathered from customers on the ground.
This data can be used to help insurers better estimate the impact of a specific event, which accelerates the claims workflow and gets much-needed money in the hands of claimants so they can rebuild. At the same time, insights gleaned from the data help insurers quickly estimate the financial impact of an event.
Reducing risk through property intelligence
In the case of wildfires, geospatial data has important applications pre-catastrophe, such as assessing a property’s vegetation to evaluate wildfire risk.
“Understanding that they’ll have the policy for several years, insurers have traditionally taken a long-term view of wildfire risk,” said Hingrajia. “But with the geospatial data collected from imagery and real-time analysis of it, insurers can identify the health of the surrounding vegetation and track erosion. All this data informs more accurate and updated policies.”
Similarly, geospatial data from aerial imagery can show previously difficult-to-access areas — a roof, for example — that an agent on the ground wouldn’t necessarily be able to easily see and assess. Drones come in handy here: While they are limited in their geographic coverage, they can pinpoint exactly where roof damage exists and transmit imagery to an insurer for evaluation.
Nearmap’s Hingrajia sees the growing abundance of geospatial data as a future boon for insurers — especially if they can tap an ecosystem to help them use it well. “It will be exciting to see if regulators, insurers and third-party data providers can come together to allow geospatial data to solve pricing and underwriting challenges in highly prone natural catastrophe areas,” he said. “It certainly has the potential to help insurers eventually provide more coverage — and quality coverage — to close any underinsurance gap.”