7 Geospatial Intelligence Companies for P&C Insurance

There aren’t that many trillion-dollar industries left where technology isn’t already shaking things up. One of the last dinosaurs to be hit by the asteroid of technological disruption is the insurance game. Specifically, we’re talking about property and casualty (P&C) insurance, which represents $1.6 trillion in premiums and accounts for about one-third of the entire insurance industry, according to McKinsey & Company. The big brains at McKinsey think it’s about time all those insurance agents, who still sport ’80s big hair and porn mustaches on their business cards, start to innovate. 

Six insurance trends.
No. 3 is the No. 1 reason for this article. Credit: McKinsey & Company

Why? For one thing, a growing tsunami of natural disasters threatens the bottom line in a big way. Last year, in the United States alone, the insurance industry coughed up $76 billion between wildfires, hurricanes, and giant murder hornets, up 40% from $54 billion in 2019, reinsurance company Swiss Re reported. That roughly jives with a separate report that showed the industry’s net income after taxes dropped 27.5% to $35.1 billion in the first nine months of 2020, while net underwriting gains declined to just $300 million, from $5.4 billion a year earlier, thanks to all those natural catastrophes. Surprisingly, insurers are upbeat about the future, betting that technology will help save the day, according to an industry survey by Deloitte.

One technological tool that will soon be in every insurance company’s toolbox is geospatial intelligence, a type of AI-driven analytics that derives business insights using imagery from satellites, drones, manned aircraft, or other sensors. We’ve written quite a bit about the different ways of using geospatial intelligence – sometimes referred to as location intelligence – as a way of generating new sources of revenue. P&C insurance has become a key market for geospatial analytics, which uses AI technologies like computer vision and machine learning to automatically assess risks, process claims, and more. 

The leading company in space-based geospatial intelligence, Planet, serves a number of markets, including finance and insurance. Since we’re thinking about taking a position in Planet stock once it has completed its merger with a special purpose acquisition company (SPAC), we wanted to assess how their imagery is being used in the geospatial insurance market.

All Hail P&C Insurance

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Founded in 2014, Cape Analytics is a Silicon Valley startup that typifies how companies combine geospatial imagery and machine learning to automate insurance and underwriting. We first profiled the company back in 2017 as one of 10 AI insurance startups. Cape Analytics has now raised $75 million after a $44 million Series C back in July. As you might expect, many of the investors are P&C insurers like Hartford and State Farm, though leading venture capital firms like Lux Capital and Khosla Ventures are also among the 20 firms betting on the startup. Cape Analytics uses machine learning and computer vision to characterize and analyze a property, from the condition of the roof to wildfire danger to neighborhood amenities. It has also begun to release specialized products like Hail Intelligence, which provides address-level risk assessments for hail damage, which cost the insurance industry more than $14 billion last year, according to Cape Analytics.

Example of a property profile.
Credit: Cape Analytics

The company now serves more than 50 subscription customers across insurance and real estate markets, including Hippo Insurance, Amica Insurance, and State Auto Insurance. The new funds are earmarked to “diversify its suite of data sources and partnerships, expand its coverage footprint in the U.S., Canada, and beyond, and grow its team of machine learning, data science, and risk experts.” 

Tracking Catastrophes

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One of those data sources is Nearmap (NEA.AX), a small-cap company that trades on the Australian Securities Exchange but is headquartered in Utah. Founded in 2007, the company provides high-resolution imagery from aerial platforms, with a focus on insurance, property, construction, and related industries like solar. Its aircraft fly up to three times per year to cover more than 1,700 U.S. urban areas, representing 80% of the population. One of its flagship solutions is post-catastrophe aerial imagery for P&C insurance carriers that provides high-resolution aerial captures following catastrophic events within days after they occur. Last year, Nearmap captured post-catastrophe imagery of more than 20 events, including tornadoes, hurricanes, wildfires, severe wind events, and even civil unrest.

AI annotated map of properties.
Credit: Nearmap

More recently, the company introduced Nearmap AI, which uses machine learning to add data layers onto aerial imagery, as shown above, to inspect things like tree overhangs that might crash through a policyholder’s roof. We may choose to take a closer look at this company in a future article.

Time for a New Roof

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Founded in 2014, San Francisco-based Betterview is another AI insurtech startup that we previously covered. It has now raised more than $15 million, with about half of its funds coming in a venture round in June 2020. Many of its investors are also insurance companies such as Nationwide and EMC Insurance. Betterview’s Remote Property Intelligence platform combines geospatial data from manned aircraft and satellites with machine learning to identify major property risks. These insights include a 100-point “Roof Condition Score” and a rules and flagging engine to help insurers quickly identify risk and mitigate losses. 

Betterview platform
Credit: Betterview

The company’s insights can be accessed directly in Guidewire (GWRE), a $10 billion software-as-aservice (SaaS) company that offers one of the leading P&C insurance platforms for managing policies, billing, and claims, along with a suite of analytical tools. Guidewire is also an investor in Betterview and recently acquired another geospatial provider of property risk data, HazardHub. (On a further aside: Guidewire is also among the top 20 holdings in the Global X FinTech ETF (FINX), so we may take a closer look at the company in a future article.)

Betting Against the Weather

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Founded in 2018, New Yawk-based Arbol has raised $9 million, including a $7 million Series A at the beginning of the year. The startup has built a blockchain-based marketplace for insurance against unexpected weather events using high-resolution geospatial datasets. It offers customers access to parametric coverage, which are insurance products that pay out a flat fee based on predetermined criteria. For example, a farmer can insure himself against drought and pray that rainfall remains below a set amount. The company currently serves businesses in the agriculture, maritime, energy, and hospitality industries. In the first eight months of its operation, Arbol reportedly “facilitated hundreds of weather-risk transfer transactions for institutional clients, representing over $15 million in notional risk.” The use of blockchain means that smart contracts take over and automatically execute payments in weeks (soon, days) if certain criteria are met based on what the blockchain industry calls “oracles.

High-resolution Aerial Imagery

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Founded way, way back in 1992, Vexcel Imaging is a Colorado company known for its aerial camera systems, mobile mapping platforms, and photogrammetry software. More recently, the company launched its own geospatial data program in 2017 and a couple of years later raised $7.5 million in 2019. The company serves a variety of industries across 20 countries, but one of its key markets is insurance. It is the official vendor for the Geospatial Insurance Consortium, a collective of insurance companies that includes names like Liberty Mutual and USAA. Like others on this list, Vexcel leverages machine learning to gather property insights for insurers, among other services.

Aerial imagery of an airport.
High-resolution imagery from Vexcel’s high-end camera systems. Credit: Vexcel

Vexcel announced just last month it would refresh more than four million square miles of aerial imagery in the United States and Europe at a resolution of six inches per pixel.

Location, location, location

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Founded in 2013, Toronto-based Ecopia has raised $6.7 million in disclosed funding. The company leverages AI to generate high-definition vector maps at scale with the accuracy of a trained GIS professional for a number of different markets. For insurance purposes, Ecopia offers the ability to extract high-accuracy building footprints for things like policy underwriting and post-disaster assessment.

Wildfire risk assessment using geospatial data.
Wildfire risk assessment using two different methods. Credit: Ecopia

Take the example of wildfire risk in a place like California to understand the value proposition, as illustrated above. Ecopia calculated two different risk scores for more than 30,000 properties in two California counties. One calculation was based on the central location of the parcel while the other used the building’s actual location using Ecopia’s database of more than 170 million building footprints generated from high-resolution satellite imagery. The results showed that a quarter of parcel-based geolocated properties were mispriced, with significant differences in risk scores. As they say in real estate: location, location, location.

Managing Risk Exposure

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Founded in 2014, Chicago-based UrbanStat has raised $600,000 in disclosed funding to help insurance companies manage exposure to wildfires and more using various AI-powered risk tools. For example, users can type in an address, policy number, or coordinates and analyze the property location with more than 30 different data points, from flooding and tornadoes to building age. 

A wildfire risk map from 2019 shows the accuracy of UrbanStat's algorithms based on a real 2020 wildfire in California.
A wildfire risk map from 2019 shows the accuracy of UrbanStat’s algorithms based on a real 2020 wildfire in California. Credit: UrbanStat

The company’s particular specialty is wildfire risk. Prior to the wildfire season in 2019, for example, UrbanStat’s wildfire risk map classified 80.5% of all subsequently burned areas as “high” or worse risk compared to about 55% for the U.S. Forest Service’s Wildfire Hazard Map. Accuracy increased to more than 90% for the 10 most destructive of 2019, versus about 60% for the U.S. Forest Service. Looks like Smokey the Bear just got smoked.

Conclusion

As far as we can tell, geospatial intelligence in the P&C insurance industry is more than just smoke and mirrors. As more and more natural and manmade disasters pile up, insurance companies will need better data and insights to manage risk and bolster the bottom line. These days, a picture is worth far more than a thousand words.

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