Benchmark Web wind reports are now live!

Verisk Climate just released Benchmark™ Wind History Reports through the Benchmark Web platform. This new report allows insurers to order wind data for their claims and underwriting processes.

The wind report is a quick and easy way to:

  • Identify at the first notice of loss whether damaging winds occurred
  • Verify the date of loss
  • Provide a historical view of straightline wind events at the property and nearby
  • Determine if damage occurred while the policy was in force

You can order a report for any property in the continental United States and for any date since January 1, 2009. Order your report here today or find out more information about Benchmark Web.

If you are an XactAnalysis or Xactimate user, you can order the wind report from the assignment record using Benchmark for XactAnalysis.

At least 25 Percent of Claims are Misclassified

A Costly Mistake

In a typical year, around 5% of homeowners will file a weather-related insurance claim in the United States.  One of the most common perils filed is that of hail damage.  Hailstorms can occur anywhere in the United States, but are most frequent across portions of the Great Plains and Midwest.  The high frequency of events can make it especially difficult for insurers to assign hail claims to the proper event date.

Analysis of industry-wide insurance claims from Verisk’s A-PLUS™ property loss database reveals that, consistently over the last five years, at least 25% of hail claims have been assigned an incorrect date of loss (DOL).  This issue is compounded when the hail event is further in time from the date when the claim is first reported.  The result has major implications for catastrophe (Cat) to non-Cat loss ratios, with a direct impact on potential for recoveries.

Percentage of hail claims that have no hail on their assigned date of loss (with a margin of error of one day) with respect to the lag between the reported date of loss and the claim open date (Source: Verisk Climate Benchmark™)

A 2014 Case Example

The 2014 hail season was a below normal year in terms of hail losses, but still recorded 20 PCS designated hail catastrophe events, covering 68 unique days.   The Colorado Front Range Urban Corridor was especially hard hit, with six separate hail catastrophe events impacting the region.  While the majority of hail losses can be traced back to the hail that occurred on one of these catastrophe dates, a significant number of claims were assigned to a non-Cat event.  Verisk Climate estimates that insurers have underestimated the impacts from the 2014 Cat events in Colorado by around 10%.  In addition, analysis has revealed that a few of the claims filed this year were actually the result of a hail event from two years ago, which occurred on June 6-7, 2012.

Areas potentially impacted by damaging hail associated with a 2014 PCS designated Cat event (shaded in yellow) across a portion of the Colorado Front Range Urban Corridor (Source: Verisk Climate Respond™)

The Question of When

Hail damage associated with storms that occurred over a year ago is not an uncommon finding.  Recent hailstorms across the northern suburbs of Dallas revealed a surprising number of claims that were likely attributable to 2012 Cat events.  This highlights an important message for the insurance industry; a properly assigned date of loss may be just as important as the assessment of whether a roof has hail damage.  In assigning hail damage, it is the question of when that has the potential to dramatically improve your financial results.  In some instances, insurers have even found that they were not covering a policy when the hail damage occurred.

Finding a Solution

The good news is that misclassifying claims can be easily avoided.  Claims data analytics including weather peril data can quickly identify these issues and provide insurers with the necessary information to reassign these claims to the proper date of loss.  This not only provides more accurate data for crucial statistics such as Cat to non-Cat loss ratios, but ultimately has the potential to impact insurers’ bottom lines through increases in recoveries and decreases in payments for damage done before the policy inception.