Commercial real estate owners face a new reality in property insurance as artificial intelligence and data science transform traditional underwriting, according to one industry veteran who argues that decades of accumulated data are now being weaponized to restrict coverage and raise rates.
“I often say that I feel like every keystroke I’ve ever put in my computer is now being used against me,” says Darrin Gross, host of the podcast Commercial Real Estate Pro Network and an insurance broker with over 30 years of experience in Portland, Oregon. “The data scientists now are much more in tune. They have such a large body of data that they really can move and refine their algorithm to be exactly what they want, as opposed to like a good guess.”
The Rise of Algorithmic Underwriting
According to Gross, insurance companies are deploying sophisticated data analysis to fundamentally reshape how they evaluate property risks. “Data scientists are definitely combing the data all the time,” he says. “They’re coming up with algorithms to figure out where they can write business that won’t put them at risk.”
This shift represents a dramatic evolution from traditional underwriting approaches that relied more heavily on human judgment and general guidelines. Now, Gross says, every aspect of a property’s risk profile can be quantified and analyzed with unprecedented precision.
The data-driven approach has particular implications for properties in areas with specific risk factors. “If you have a large property that’s near a lot of fuel, like a forest, or any place that they feel is suspect,” Gross notes, these algorithmic assessments may flag it for higher rates or reduced coverage.
Climate Data Driving Market Changes
The increasing sophistication of data analysis coincides with growing concerns about climate-related risks, Gross explains. Insurance companies are particularly focused on how changing weather patterns could affect property exposure.
“Whether or not you believe in global warming, there are weather cycles that are dramatically changing the property exposure in the eyes of insurance companies,” Gross says. He points to recent examples like the 2020 Oregon wildfires that destroyed entire towns, noting how such events are reshaping risk assessment models.
Solutions and Market Response
While the situation may seem dire for property owners, Gross sees some potential relief on the horizon. “I don’t want to sound the bell to say that the market’s healthy again, but we are starting to see signs and starting to hear some evidence that suggests there are some companies coming back into the market,” he says.
However, he cautions that any market improvements will likely be uneven: “The cycle has the same characteristics. However, the elements that are unique to the cycle are not the same.” The key difference now, he argues, is the unprecedented level of data analysis driving underwriting decisions.
For property owners and managers looking to navigate this new landscape, Gross suggests focusing on elements within their control. This includes maintaining updated systems and documenting property improvements, as these factors now play an increasingly important role in algorithmic risk assessments.
