Visualize: Insights that power innovation

Visualize: Insights that power innovation

High and inside: the crucial metrics commercial property underwriters need to avoid premium leakage

By Kevin Kuntz, Elizabeth Casas Leano  |  September 28, 2020

We’re often told that appearances can be deceiving. When it comes to commercial property, it’s more than a trite maxim, but words to live by—or at least underwrite by.

What a warehouse, logistics center, or corporate headquarters looks like on the outside may not fully reveal to underwriters what’s actually occurring inside the building. The same goes for building height. Simply learning that a building is listed as having 14 stories may not actually convey the true height of the building.

Determining occupancy and height are just two of a number of crucial data points that many commercial underwriters must successfully source when classifying and pricing commercial property risks. Without reliable data, underwriters not only run the risk misjudging occupancy exposures but of assigning the wrong construction class code to a building, or not accounting for year built or building square footage. Like a house built on a shoddy foundation that eventually costs the owners thousands to repair, an accumulation of these underwriting errors or faulty and unreliable data points can often ultimately lead to mispriced policies.

Occupancy

Underwriters often begin their work by inquiring about the kind of business occurring in a commercial property. That information is especially important given the loss costs for commercial property fires. The National Fire Protection Association reported fires caused an estimated annual average of $2 billion in damage to commercial property between 2014-2018. That accounted for 9.4 percent of all reported fires, but nearly 19 percent of all reported damage.1

However, determining the true nature of the occupancy may be tricky. In some instances, you’d need detailed data or an in-person inspection to confirm this. A car dealership, for example, could simply be an office and a showroom, or it could also house a full-service area complete with an auto repair and body shop involving high-risk activities such as spray painting. Another example is a parcel service office: it could simply handle mail or could include packaging, crating and printing services. 

As they delve further into occupancy, underwriters may want to focus on such criteria as:

  • Proper classification: What’s the building used for and what operations are occurring inside? As an example, if you see a (hypothetical) business named ABC Tire Company, can you tell if that’s an office, repair center, warehouse, or manufacturing facility? It’s one simple, seemingly descriptive name, but it could contain significantly different risks, depending on the true nature of the business.
  • Combustibility of contents: How will the building’s contents affect the structure under fire conditions?
  • Inherent hazards found in certain occupancies: What are the risks inherent with certain occupants? For example, cooking hazards in a restaurant pose a much higher risk than hazards found in an office or a pharmacy.
  • Susceptibility of contents: Are the materials or merchandise in the building prone to damage from the effects of fire, smoke, and water? Pharmaceutical or electronics facilities tend to be much more susceptible to damage than facilities involving general metal products.
  • Sprinkler and extinguisher protection credits: Does the building’s sprinkler system offer adequate protection, and how would it affect a building’s loss cost? Key sprinkler data underwriters will often examine includes the percentage of a building that is sprinklered, the capability of the water supply to meet the demands of sprinklers, and the adequacy of the overall design.

The story about stories

Stories are commonly defined as the space in a building between two adjacent floor levels or between a floor and the roof. The number of stories a building has is another risk element underwriters account for, often in conjunction with square footage.

However, underwriters need to make sure they get an accurate count of the number of stories. For example, many high-rise buildings omit the designation for a 13th floor. You may go into an elevator or see in a building directory a top floor designated as 22, but in reality, that building is 21 stories high. How mezzanines are counted also matters—sometimes they’re counted as a portion of an existing floor, other times as a floor annex.

The number of stories could also affect premiums. A fire in a 100,000 square-foot, two-story building has different challenges than an identically-sized building whose footprint is spread out over six floors. Even with sprinklers and other fire protection measures in place, buildings with a higher number of floors complicate firefighting operations because:

  • it typically takes longer to put water on a fire
  • they often require more firefighters
  • the increased elevation often limits options to perform ventilation
  • they limit access by ground and aerial ladders

Another complicating factor with taller buildings is wind speed. The higher the building, the higher the wind speed it’s subjected to. Most wind damage is a result of limited resistance due to poor design, deterioration of materials, or roof system abuse.2 Wind is one of the largest weather-related risks for insurers in general. Payouts for damage from convective storms, which includes straight-line winds, topped $10 billion in 2019.3

Even a moderate wind event can cause major damage to roof coverings, or rooftop mounted HVAC equipment. That’s why it’s critical that underwriters have building characteristic data related to wind exposures when writing a policy. Indeed, basing decisions on reliably sourced, robust data applies to all aspects of underwriting.

The importance of robust data

How can insurers obtain robust and reliable data about commercial properties? Below are a few suggestions:

Consider the source: Insurers may want to consider where they’re obtaining the data. Is it from a single provider you know and trust? Or does it come from multiple providers, some of which you may have never worked with before, and that may not characterize the data and risks consistently?

Understand data-collection methods: How the data is collected can also affect its currency. Is the data solely based on public records that may be outdated, inconsistently recorded, and limited in detail? Or does it come from private databases that are updated regularly?

Know the team behind the data: It’s also critical to know who’s responsible for the data. Does the team include professionals with experience inspecting commercial properties? If so, how well are they represented on the team?

Delivering powerful insights into commercial property risk

Every year, commercial property insurers on the whole lose billions due, in part, to underwriting errors. Whether it’s misclassifying building construction, failing to understand the occupancy, building size, height, or other crucial factors, these errors often have one thing in common: many could have been prevented with the right data. From hundreds of highly trained and experienced field personnel and virtual survey options to advanced analytical models built upon unrivaled property data assets (to the cutting-edge synthesis of both), Verisk has the tools and experience to help underwriters properly classify and price their commercial property risks. 

Learn more about Verisk's solutions for commercial property underwriters.


This article is the third in a series focusing on commercial property underwriting. Read part one, Three Common Mistakes Inspectors Make When Classifying Commercial Buildings. Read part two, Three attributes of commercial properties that underwriters shouldn't take for granted.


 

  1. Fires by Occupancy or Property Type, National Fire Protection Agency, < https://www.nfpa.org/News-and-Research/Data-research-and-tools/US-Fire-Problem/Fires-by-occupancy-or-property-type>, accessed on September 25, 2020.
  2. Tom Smith, “Wind Safety of the Building Envelope,” National Institute of Building Sciences, June 5, 2017,
    < https://www.wbdg.org/resources/wind-safety-building-envelope >, accessed on September 25, 2020
  3. Severe Convective Storms: Evolving risks call for innovation to reduce costs, drive resilience, Insurance Information Institute, May 2020, < https://www.iii.org/sites/default/files/docs/pdf/convective_storms_wp_050520.pdf >, accessed on September 25, 2020.

Kevin Kuntz is Vice President of Risk Engineering, Safety and Training, and Chief Engineer for ISO Commercial Lines.

Elizabeth Casas is Head of Product Innovation for Commercial Property Underwriting at Verisk. You can contact her at Elizabeth.Casas@verisk.com.