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Why Insurance Companies Need Parcel and Boundary Data

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One of the biggest challenges facing the insurance industry is the sufficient assessment of the risk profile of real estate properties.

Underwriters rely heavily on accurate and up-to-date data to help adequately assess the risk and corresponding cost of insuring a particular property.

Reliable and accurate parcel and boundary data can help insurance providers gain better insights into properties and eliminate inaccurate quotes that waste time, money, and, ultimately, frustrate customers.

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What is parcel and boundary data?

Parcel and boundary data represent the basics of any property and include nearly everything you need to know about the land that makes up the property.

A parcel or boundary represents the boundaries, borders, or coordinates of a plot of land or whole property rather than the specific units within the property.

boundary-data-example

Using Quantum Geographic Information System (QGIS)* shown above, counties are able to map boundaries on a map that show every property or plot of land in a given area.

And with the constant development of land and continuous construction of buildings, boundaries can be split, modified, merged, or otherwise changed so frequently that existing boundary lines can be used to track proposed and future changes from governing authorities to better serve clients.

*Please note, mapping service and integration is not provided by Estated, only raw boundary data points. The boundary applies to the whole property, not to units within the property.

Parcel details, provided by the assessor, can include the following fields:

  • fips_code—Federal Information Processing Series (FIPS) are unique numeric codes assigned US states and counties;
  • depth_ft—the depth of the parcel measured in feet;
  • frontage_ft—the frontage of the parcel measured in feet;
  • area_sq_ft—the total area of the parcel measured in square feet;
  • area_acres—the total area of the parcel measured in acres;
  • land_use_type/category—the general land use category for the property;
  • zoning—unique designation of zoning made by the city;
  • building_count—count of all buildings on the property;
  • lot_code/number—indicates properties with multiple or partial lots;
  • subdivision—name of the subdivision or tract in which the property is located;
  • municipality—jurisdiction in which the property is located.

While boundary (coordinates along a parcel's boundary at specific points) can include the following fields:

  • wkt—the well-known text representation of the boundary as a geometric multi-polygon for use in geographic information system (GIS) software.
  • geojson—a standard format designed for representing geophysical features using longitude, latitude, and elevation.

Interested in learning more about parcel and boundary data, click below to speak with a data expert.

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Importance of property data for insurers

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In combination with the rest of Estated's schema of hundreds of different data points, parcel and boundary data can provide the most accurate and complete picture of a particular property or set of properties, which then becomes a very powerful tool for a variety of industries including insurance.

Leading insurance providers, insurtechs, and underwriters can use property data to help assess the hazard and risks associated with insuring a particular property.

Flooded-neighborhood_1

For example, using geographic parcel and boundary data, an insurance company can easily determine if a property is located near a flood plain or situated in an area more susceptible to catastrophes such as tornado alley or a wildfire zone, and thus calculate their insurance premiums more accurately.


Insurance Use Cases

But how have insurance companies actually used Estated's property data? Over the past 3 years, we've partnered with a variety of industry leaders in insurance including Blend, Obie, and Kin to help with a number of different pain points.

Property data can help insurance companies:

  • Streamline applications with instant user information validation and error correction.
  • Eliminate inaccurate quotes with the most reliable and up-to-date data from millions of trusted sources.
  • Digitize the cumbersome quoting process to deliver your customers instant insurance quotes using existing ownership information.
  • Improve replacement cost success rate by using hundreds of critical data points to better assess risk and evaluate hazard.

Discover how Obie uses Estated property data to expedite risk evaluation and generate insurance quotes instantly.

Download the Case Study below. 

obie-case-dl


Using the raw data provided by Estated, technology-forward insurers can create:

  • Real Estate Maps—outlining boundary lines, surrounding properties, and other data specific to a particular parcel;
  • Zoning and Subdivision Maps—Showcase parcels on map outlining current and proposed zoning as well as existing and proposed neighbourhood subdivisions;
  • Catastrophe Maps and Risk—In combination with other data, detail historical natural catastrophes on a per property basis as well as outline risk levels using parcel boundaries to map natural hazards such as flood plains for insurance estimates.

Find out how Blend doubled their success rate (~90%) for calculating replacement cost using Estated's property data.

Download the Case Study below.

blend-case-study-2

Ultimately, property data helps insurance providers ensure risk is more accurately analyzed and premiums more precisely calculated using data-driven modelling which increases transparency and enhances trust with customers.


Start using Estated property data today

At Estated, we offer the most accurate and comprehensive data, including parcel and boundaries, on over 150 million residential and commercial properties nationwide across the United States.

If you're an insurance company, insurtech, or underwriter looking to better assess property risk, eliminate inaccurate quotes, and enhance your customer experience, Estated property data is the best solution available in today's market. Let's connect below!

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