How to Avoid the Uncertainty Mark-up for Catastrophe Coverage

Uncertainty can prove costly when it comes to purchasing property insurance. When pricing catastrophe risks, underwriters must be able to quantify them accurately. Where uncertainties arise, underwriters often adjust prices in an attempt to compensate for the unknown or decline the risk entirely. Uncertainty also tends to drive up the loss estimates produced by CAT modeling tools used to help underwrite property coverage today. To avoid paying unnecessarily high prices, insureds should provide detailed data that creates a complete and accurate picture of their exposures in a schedule of values. Complete submissions based on more precise data are likely to receive a warmer welcome from underwriters who have seen an increase in submission volume in the current market. Brokers that can provide a detailed catastrophe risk assessment report using the latest modeling technology can help clients make more informed decisions about risk transfer strategies and better position them to achieve the most cost-effective insurance program.


Because a catastrophe can jeopardize a business or put an organization under severe financial strain, property owners should know how much damage a natural disaster could cause; how much it would cost to repair or replace damaged property; how long a property might remain out of service and the costs associated with that interruption. A natural catastrophe risk assessment report outlines the potential financial impact of hurricanes, thunderstorms, floods, earthquakes, and wildfire, making it an essential and valuable tool for property owners, brokers, and underwriters. In addition, creating a more accurate picture of a property portfolio’s risk makes it more attractive to carriers and lays a stronger foundation for negotiating optimal catastrophe coverage.

From 1997 to 2016, tornadoes, wind events, hail, and flood losses made up 39.9% of U.S. insured catastrophe losses. Source 2


A risk assessment report utilizes industry-leading models to produce an overview of natural catastrophe exposures for a portfolio of properties and ranks the risks for each property and peril by severity. Catastrophe modeling has become a key component of every property placement submission and may impact not only pricing but terms and conditions as well. Models use historical data and statistical techniques to derive the probable losses to a property that would be caused by windstorms, earthquakes, and other perils of various magnitudes like a 100-year, 1,000-year, or 10,000-year flood. A 100-year flood is one that statistically has a 1 percent chance of occurring in a given year. It’s worth noting that two years might see back-to-back 100-year floods. These intervals are also referred to as ‘return periods.’ A 10,000-year return period implies an annual probability of 0.0001 percent.

Models also estimate average annual losses, which generates a long-term average of annual damage estimates. This figure is often used as a basis for calculating premiums. The standard deviation measures the variability of year-to-year damage expectations, and a high number may indicate a property is at risk of occasional but very severe hazards. Moreover, natural catastrophe models are used by insurers to monitor and adjust their own specific risk appetites. Carriers may seek, for instance, to reduce portfolio exposure around specific hazards in particular areas such as hurricane-prone Florida or the Gulf Coast, high-hazard hail zones in the Midwest, or along the West Coast where earthquakes are more common.

Insureds can use the results of a catastrophe risk assessment report to help choose the limits they want to purchase and inform how they want to structure risk retention or transfer programs. For example, a larger portfolio may include a small number of properties that pose the greatest risk and entail the highest insurance cost. Property owners may want to consider how different strategies can help mitigate the costs related to those particular properties. Strategies can include taking higher retentions to lower premium costs or using a parametric product to cover some of the increased exposure.


When it comes to models, more accurate data generates higher-quality results, which has a direct impact on insurance costs. Models are highly sensitive to uncertainty driven by poor or missing data, and this often leads to elevated premiums. Avoiding this means property owners need to provide comprehensive data about each building in their portfolio. Important data includes the exact location of a building; occupancy, or how it’s used (i.e. retail, office, or warehouse); type of construction (i.e. wood frame, joisted masonry, or reinforced concrete); the year it was built, the number of stories, and whether there is a working fire suppression or sprinkler system. The risk assessment report helps to identify missing data, such as inaccurate property addresses or the number of stories in a structure. They can also indicate where engineering reviews may be useful. Inexact data can lead to potentially expensive assumptions. When a model does not have the exact property location, it will substitute the geographic center of the zip code, which could be an area more susceptible to natural catastrophes like floods, earthquakes, hurricanes, or wildfire. A property also might be mistakenly placed closer to the coast or a fault line. Problems with location data include using post office boxes or ranges of numbers for addresses. If the construction details aren’t complete, a model may rely on local building codes for the period during which the building was constructed to create an estimate, which could fail to reflect upgrades or retrofitting and may result in higher loss estimates for older buildings.

 Natural catastrophe losses fell in 2018 and 2019, but rose to $74.4B in 2020, an increase of 88% since 2019. Source 2


Underwriters, who have been tasked with reining in insurers’ losses on property policies, are increasingly seeking additional information to improve the accuracy of modeling results, particularly for windstorm and earthquake coverage. These secondary modifiers include the condition of a building, frame bolting, exterior cladding, and foundation. For windstorm, underwriters may want to assess items including window protection, roof anchors, tree exposure, roof geometry or pitch, and the age of the roof.

Secondary modifiers for earthquakes include a building’s shape and whether it features a soft story, that is a ground floor with large openings such as windows and doors that may make the structure more likely to collapse. Adjacent buildings may pose the danger of pounding - damage caused by adjacent structures colliding during earthquake-induced motion. Soil type can also help determine how stable a structure would remain in the event of an earthquake. For example, structures built on man-made fill in San Francisco suffered heavier damage in the 1989 earthquake due to liquefaction.1

For locations that account for a large portion of a portfolio’s insurance costs, it may be advisable to have engineers review secondary building characteristics to provide additional data that may help to reduce the impact on premiums. The goal is to provide insurers and policyholders with the most comprehensive picture of the risk possible.


A comprehensive catastrophe risk assessment report streamlines the placement process and often helps to produce better results. The ramifications go beyond price, as clients who develop a best-in-class grasp of their property exposure often find markets are more receptive and willing to provide insurance solutions. Doing this work up front can pay significant dividends when it comes time to negotiate a property program. Property owners who understand the key drivers behind their insurance risks and subsequent costs are ultimately better prepared. CRC Group is home to brokers that can provide a detailed risk assessment and have deep property placement expertise that makes it easier for clients to achieve the best possible outcome. That’s a priceless advantage in a hard property market. Contact your local CRC Group producer today.


  • Colin Morris is a Senior Risk Analyst with CRC Group’s Red Bank, NJ office.
  • David Pagoumian is the President of CRC Group’s Red Bank, NJ office. David specializes in property placements and is an active member of the Property Practice Advisory Committee.


  1. Liquefaction Hazard Maps, U.S. Geological Survey.
  2. Spotlight On: Catastrophes - Insurance Issues, Insurance Information Institute, December 13, 2021.