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Home Uncategorized

Insured Losses from 2018 Natural Disasters Top $22.5 Billion Heavily Impacting Insurers

by Jackie Davis
January 22, 2019
in Uncategorized
Reading Time: 3 mins read
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Last year the United States experienced a historic number of natural disasters including the California wildfires that leveled entire towns, and Hurricane Michael that flooded cities from Florida to North Carolina. These two events topped the list of costliest natural disasters for 2018, according to Munich Re. With over $22.5 billion combined in insured losses, these disasters hit unprepared insurers hard, even forcing some to close their doors who couldn’t pay the staggering totals.

With over $64 billion in outstanding liabilities but only $23 million in assets Merced Property and Casualty Co. has closed their doors for good. Could this have been avoided with better data? A recent study by Perr & Knight explored how inaccurate premiums are negatively impacting insurers. Using data-driven solutions, policies are set to the correct price based on risk ensuring that both the insurer and insured are covered in the event of a major loss.

 


 

Research conducted on insurance premiums using data sets like zip codes and street segments, compared to parcel-level data showed that in five to ten percent of cases, pricing was inaccurate, and premiums were either significantly under or overpriced. Some homeowner policies were underpriced by as much as 86.7 percent or $2,800 annually, causing major loses for insurers. If multiple homes in the California wildfire’s path had underpriced premiums, it should come as no surprise that Merced Property and Casulaty was insufficiently funded and unable to cover their share.

A top U.S. insurer found that only three percent of properties that made a claim following the wildfires had been identified as high risk. The large number of unanticipated losses is estimated to have cost insurance companies over $100 million. By investing in data intelligence solutions, insurers can gain better insights into a customer’s risk and craft policies accordingly.

“By putting data to work an insurer can improve the overall quality of their underwriting efforts by identifying key exposures that might otherwise have gone unnoticed but that need to be addressed and factored into pricing,” said Mike Hofert, Managing Director of Insurance Solutions at Pitney Bowes.

To learn more about hyper-accurate insurance data, click here.

Tags: California WildfireCamp FireHurricane Michaelinsuranceinsurance dataMerced Property & Casualty CoMunich RePerr & KnightPitney Bowes

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