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How to Use ATTOM’s Environmental Hazard Data to Verify and Assess the Impact of Natural and Man-Made Hazards

When it comes to claims management as an insurer, it’s vital that you have access to real-time, accurate data on the latest natural and man-made hazards. How can you verify that a severe weather event or manmade hazardous occurrence has taken place? Furthermore, how can you precisely assess how much damage has been done to a property you insure?

In the event of a catastrophe, your clients rely on you for timely and efficient case management – as such, the ability to quickly verify the occurrence of natural and man-made hazards and the damage they cause is key to retaining customers. In this post, we illustrate how you can verify a hazardous occurrence quickly and reliably using environmental hazard data.

The Rise of Man-Made and Natural Disasters: The Real Costs to Insurers

                                                                                                                                                                                 Screenshot from the NOAA.

Natural disasters, from tornados to wildfires, currently cause an estimated $160 billion worth of damages to homes and commercial properties across the U.S.. In 2018, losses from natural disasters rose well above the inflation-adjusted average of the last 30 years ($140 billion) to

Globally, America has experienced some of the worst losses due to natural disasters. Last year, Hurricane Michael resulted in losses of $16 billion, as well as insured losses of $10 billion. In addition, Northern California suffered America’s most devastating wildfire in over a century – destroying over 150,000 acres, claiming 86 lives, and exceeding 2017’s record-breaking $11.8 billion pay-out figure. These catastrophes have led to record insurance pay-outs, and the astronomical costs to insurers have even forced some insurance companies to close their businesses.

Moreover, man-made environmental hazards, such as brownfields and superfunds, are also on the rise. Currently, there are over 450,000 brownfield sites found in the U.S and over $190 million has been spent on their clean up.

Map of location of hazardous waste sites from Duke University.

In the current climate, the pressure is mounting on small and large insurance companies to settle claims quickly to ensure customer satisfaction and reduce stress for teams processing a claim.

Streamline Your Verification Processes with Environmental Hazard Data

As an insurer, the quality of your data is more important than ever in supporting your ability to detect fraud and accurately assess damages and compensation figures.

ATTOM’s reliable environmental hazard data, composed of data from several government agencies, enables you to locate and asses the severity of a natural or manmade disaster. ATTOM provides data on each of the most common natural disasters – including data on any natural event that may adversely impact populations or property.

In addition, our hazard datasets also cover man-made environmental hazards that threaten the health and well-being of residents in a geographical location, such as pollution and toxic chemical contamination. Our comprehensive hazard data covers:

  • Earthquakes
  • Wildfires
  • Registered polluters
  • Floods
  • Underground storage tanks & spills
  • Radon
  • Superfunds
  • Hurricanes
  • Hail storms
  • Landslides
  • Brownfields
  • Meth labs

With our Bulk Property Data Licensing solution you can access real-time data on offer 155 million properties, and assess whether a property in your portfolio has been impacted by a natural or man-made disaster, as well as deduce the severity of the damages. Moreover, our nationwide datasets can also be seamlessly integrated with your own servers to ensure timely verification.

Verifying Natural and Man-Made Disasters with ATTOM

After disaster strikes, the pressure is on for insurers to act quickly to process claims. With ATTOM, you can accurately verify disasters and their impact on your customer base. Contact us here to learn more.



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