Commercial property insurers don’t want some or even most of the data about the buildings in their portfolios. They want all of the key data at their fingertips when a prospective client is waiting for an answer on coverage. Getting a 100 percent hit rate on the core building attributes necessary to determine insurance coverage and premiums can lead to smarter decisions and a streamlined process, saving time and money.

The best way to get this information is by visiting buildings in person. Verisk’s team of more than 400 field representatives survey almost 400,000 commercial properties a year. But it’s impractical to visit every commercial property in the United States on a regular basis.

Recognizing this deep industrywide need, ISO’s statistical team has built an advanced analytical model for over 11.3 million commercial properties that gives insurers a 100 percent fill rate for five core property attributes: construction class, year built, square footage, number of stories, and primary building use.

Our foundation for this initiative was 4.3 million properties with data gathered in the field by experienced survey professionals. Leveraging these verified on-site reports, Verisk’s analysts have enhanced and expanded the ProMetrix^® experience to increase hit rates and give insurers the full picture for over 15.7 million commercial properties.

Underwriters who once turned to incomplete and inconsistent tax assessor data or relied on guesswork to estimate their exposure can now depend on detailed data that’s automated, actionable, and backed by ProMetrix reliability.

Here’s a peek into the five core property attributes our data scientists modeled:

• Construction class: Insurers rely on ISO construction class codes, which are the gold standard for assessing which buildings are most vulnerable to fire loss. The codes range from Class 1 for frame buildings to Class 6 for fire-resistive buildings. Knowing how a building is constructed is crucial for accurately assessing exposure. Some insurers will not provide coverage to restaurants in Class 1 frame buildings, for example. But tax record data and even data “cleaned up” by aggregators often fails to include ISO construction class codes. A Class 1 building might be labeled as lumber, wood, or a range of different terms. We’re able to use available data about the properties to model the building’s construction class.
• Year built: Knowing the age of a building can help insurers correctly price their policies because older buildings may be more vulnerable to losses from hazards such as fire and wind. Older buildings aren’t necessary designed to hold up to hurricanes and can also be less fire-resistant than newer structures. They may also experience more electrical problems and roof leaks. Verisk analysts are able to determine a building’s age by analyzing other available metrics, such as construction class.
• Square footage: The bigger a building, the greater its potential for loss and the higher the replacement cost. Our model uses a variety of data sources to generate information on the square footage of a building.
• Number of stories: Taller buildings with multiple stories have a higher potential for loss from fire, the primary loss that insurance companies face. It’s more difficult to fight fires in multistory buildings, which ties directly to insurance premiums and coverage. We were able to construct a model for the number of stories using related data about the building and comparable properties.
• Primary building use: Insurers need to know what type of business is being conducted in the properties in their portfolios. A shoe store, for example, differs significantly in its insurance needs from a restaurant, where there are likely to be deep fryers that can create a substantial fire hazard. Buildings with occupants engaging in hazardous activities will more likely be flagged for additional review. ISO Commercial Statistical Plan (CSP) codes give insurers an understanding of what their exposure is likely to be for each customer. Our computer model relies on various data points, including public data, to generate valid CSP codes.

The newly expanded ProMetrix database with increased hit rates provides actionable data on over 15.7 million commercial properties in a seamless, automated stream that’s delivered directly into an insurer’s workflow in an easy-to-use format.

Did you know Verisk’s modeled data can help deliver a 100 percent fill rate on core property attributes? Read our report to learn more.

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