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Location, Inc. (Worcester, Mass.), a provider of location-based analytics, has enhanced its FIRE RISK to calculate the probability a location will suffer a fire, answering insurance industry demand for solutions predicting frequency, as well as severity of the loss type.
“It’s not just the people; it’s not just the structure; it’s not just the location; rather, human behavior, property vulnerability, and environment and location, each with many moving parts, converge in unexpected ways to create or mitigate fire risk,” comments Andrew Schiller, CEO and Founder, Location, Inc. “We’re at the forefront of this big data work, with fire frequency emerging as the leading predictor of insurance loss.”
Andrew Schiller, CEO, Location, Inc.
Insurance carriers have traditionally relied on products that attempt to estimate the level of damage that would occur once a fire starts, usually by understanding the distance to a fire station or hydrant and other response factors, according to Schiller. However, according to a recent study by the Underwriters Laboratory, the proliferation of engineered lumber and petroleum-based furnishings, including furniture foams, carpets, and drapes, means today’s houses are more flammable and burn more quickly.
As a result, fire department response time is less important in predicting the severity of loss than understanding which properties are likely to have a fire in the first place.
Quantifying the lift FIRE RISK provides when applied to a holdout data set of over $3 billion in premium, and then applying those findings to the $74 billion homeowners insurance industry, reveals $19 billion in premium adjustments and $1.2 billion in claim reductions annually, according to a Location, Inc. statement.
Examples of FIRE RISK’s key indicators that would increase the probability fire loss include:
- Leaving a hot, greasy frying pan unattended on a stove.
- Falling asleep with a lit cigarette.
- Letting electrical problems lapse.
- Carelessness with space heaters.
“Thirty years ago, you had about 17 minutes to escape a house fire. Today it’s down to 3 or 4 minutes,” Schiller notes. “With the speed of fire engulfment so quick, predicting fire frequency is key to understanding risk. And since most structure fires are directly or indirectly caused by people—the things people do and don’t do, the mistakes people make—modeling human behavior in the context of structure and location has proven valuable.”