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Using Geospatial Property Intelligence & GIS for Risk Assessment

July 7, 2021

Underwriting and risk assessment are two of the most important components of insurance operations. The cost of poor risk assessment practices can be catastrophic, both for the insurance carrier and the customer. But despite the high stakes, the way insurers calculate risk has been slow to keep up with the digital transformation of the insurance industry. Yes, many insurers utilize artificial intelligence and big data for things like claims and billing, but some areas of their policy processes could still use help.

As of late, some insurers have started to see the potential in using geospatial property intelligence to inform risk assessment and underwriting. Using this widely-available data and technology, insurers can now quote, assess, and protect their customers in a whole new way.

Understanding GIS & Geospatial Data

GeoSearch, Inc., a geospatial science and technology firm, defines GIS as: “A geographic information system (GIS) is a framework for gathering, managing, and analyzing data. Rooted in the science of geography, GIS integrates many types of data. It analyzes spatial location and organizes layers of information into visualizations using maps and 3D scenes.”

Geospatial, on the other hand, is a term that refers to anything that has a geographic location component. So geospatial data simply indicates that the data or data sets have a geographic location tied to them, like an address or even GPS coordinates.

Understanding how GIS and geospatial data relate to one another can be difficult. To put it simply, GIS is a form of geospatial data technology in that it is used to “acquire, manipulate, and store geographic information,” according to GIS Lounge.

How Are Geospatial Data & GIS Used in Risk Assessment?

Historically, carriers have had to rely on third-party data sources like public tax records, building permits, and hazard information about surrounding areas to inform the underwriting process. But with geographic information systems (GIS) now informing risk assessment, geospatial data is giving carriers a treasure trove of new insights. Here are some of the tasks being impacted by this data.

Insurance Underwriting — Geospatial data such as current property condition, surrounding property values, crime rates, fire hydrant locations, proximity to water, proximity to emergency services, and more can all better inform insurance underwriting. This level of granular detail wasn’t available before GIS and geospatial data.

Hazard & Threat Mapping — Hazard maps display a geographic area’s risk for earthquake, landslide, flood, fire, or other natural threat. This geospatial data can be leveraged by GIS systems to identify high-risk areas and inform more accurate underwriting practices.

Proactive Risk Mitigation — Geospatial images are regularly taken by satellite or aircraft and are processed by machine learning and computer vision algorithms. Using this data, insurers can automatically interpret the imagery at scale to generate new risk insights. This allows them to proactively protect their customers if they spot an issue, like a deteriorating roof or overhanging trees.

Benefits of Using Geospatial Data & GIS for Risk Assessment

There are a number of benefits of using geospatial data and GIS for risk assessment, but the most impactful for insurance carriers are:

  1. GIS and geospatial data more accurately informs the risk assessment and underwriting process, ultimately delivering the most accurate quote possible.
  2. This technology allows insurers to increase the speed at which they make accurate property assessments and policy quotes.
  3. By creating faster, more accurate quotes, insurers are delivering better customer experience, which increases customer conversion rates.
  4. The insights derived from GIS and geospatial data allow insurers to increase ongoing customer engagement – insurers are always looking for ways to build relationships and loss avoidance, so by proactively helping a homeowner protect their property, insurers can nurture customer relationships and protect their investment.
  5. GIS and geospatial data is highly structured, highly objective, and is collected at scale, meaning insurers can deliver new kinds of risk insights that weren’t possible before.
  6. Insurers can reduce their combined ratios (impact loss ratio and expense ratio) by better aligning risk with price.

Geospatial Data & GIS Risk Assessment Use Cases: CAPE Analytics

CAPE Analytics is a property intelligence company that uses geospatial imagery, artificial intelligence (AI), and GIS to provide instant property attribute information for buildings across the U.S. and Canada. Their offering includes traditional underwriting data, such as roof material and roof geometry, but it also cleans up and brings more accuracy to that data while expanding upon the information insurers have that they wouldn’t ordinarily have access to on-demand—such as roof condition, vegetation coverage, and yard debris. This allows carriers to make the most accurate and efficient underwriting and rating decisions, all in an easy to use, intuitive platform.

Geospatial images and data have existed for years, but it would be far too cumbersome for a person to assess all the data that geospatial images provide. That’s where CAPE Analytics property intelligence comes in — their platform can extract information from the images automatically, so carriers have the most relevant and up-to-date information they need.

The Future of CAPE Analytics GIS & Geospatial Data for Risk Assessment

Using GIS and geospatial data is a new frontier for the insurance industry, which means insurers are still discovering the potential of this technology. Ultimately, GIS means access to new data and new insights, which will allow the industry to evaluate risk in a new way. Things that didn’t influence price or risk before – like cracks in a driveway – will now make an impact. The new correlations stemming from big data and machine learning are changing the industry and will continue to do so.

For carriers, one of the most promising opportunities with this data will be the potential for pre-underwriting. Pre-underwriting is when insurers have access to geospatial information on homes across the country, and can use it to “pre-underwrite” before a customer requests a quote. Insurers can then proactively market to these properties that fit their business model and more effectively target customers that will convert. This could spell a whole new era for new business development in the world of property and casualty insurance.

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Andy Yohn
Andy is a co-founder of Duck Creek Technologies and has been involved in the design and development of the solution offerings of the company. Andy brings a solid mix of technical and business skills together through his 30+ years of working in the insurance automation industry. Andy served as founding Chief Architect of the Duck Creek Platform and currently is actively involved with product management and research and development projects. Prior to Duck Creek, Andy had a thirteen-year tenure with AMS Rating Services. Andy holds a bachelor's degree in Computer Science with minors in Mathematics and Music.