How data is bringing roof adjusting into the 21st century

By digitizing the following key data for 28,547 municipalities in the United States, OneClick Code is pioneering automated roofing code identification and permitting processes:

• Roofing codes
• Municipal jurisdiction authority
• Material tax
• Manufacturer specifications

The resultant data set eliminates millions of hours spent by adjusters and contractors required in the claims process by putting the information where it belongs: at the user’s fingertips.

Claims departments responsible for settling roofing claims can enjoy enormous potential loss adjustment expense reductions and loss cost savings through quickly considering a very simple set of questions:

• How many roof claims do we settle on average each year?
• What percentage of those claims require roofing code research
  and review of contractor estimates?
• What is the average time required by an adjuster to research roofing codes and review contractor estimates?
• What is our average adjuster hourly pay rate?

The process to research the roofing codes and review contractor estimates is more involved than it may seem, including but not limited to the following steps: 

• Reviewing supplement
• Identifying jurisdiction
• Searching for roofing codes
• Finding the municipality phone number
• Recording these actions in a claims log
• Adding line items specific to code
• Calling the contractor to discuss approved items
• Reviewing and processing payment
• Downloading and uploading related information

Altogether this typically requires just shy of 120 minutes (two hours) of the adjuster’s time. Moreover if there is a supplemental request by the contractor and it is denied in full or in part it may be requested again. Such an additional request can add anywhere from 30 to 60 minutes to the process each time an adjuster reopens a claim to review a supplemental request and it is not uncommon for this process to repeat three or four more times after the initial request. Associated labor costs aside, there is no real measure for the amount of frustration experienced by the adjuster or contractor in such a process. To fully appreciate that frustration, we recommend trying to work tomorrow without your mobile phone or computer.

Using a data driven solution instead, this entire initial process takes less than five minutes and any resubmission less than one minute resulting in hours of savings each time. It also eliminates or greatly reduces the frustration experienced by the adjuster and contractor during the initial submission and any subsequent reopening by the adjuster. Most importantly, a data driven approach provides defensibility for the position taken, eliminating ambiguity and underpinning acceptance by all stakeholders. Such clarity increases the fidelity of the indemnity process and by definition reduces the possibility of fraud.

Data sourcing processes should be designed around three key values/principals:

RELEVANT
Related to settling roofing claims

RELIABLE
Straightforward answers to the most commonly asked and important questions (such as whether a local code requires a roof to include drip edge, valley liner, or iced water shield in eaves)

PRACTICAL
Updated consistently to ensure accuracy

OneClick Code targets municipalities based on what the Census Bureau calls CBSA’s (Core Based Statistical Areas). A CBSA is a U.S. geographic area defined by the Office of Management and Budget (OMB) that consists of one or more counties (or equivalents) anchored by an urban center of at least 10,000 people, plus adjacent counties that are socioeconomically tied to the urban center by commuting. 95% of the US population lives within 919 CBSA’s which encompasses 1,811 Counties. Within those counties are a further 28,547 local municipalities. Of the 28,547 municipalities, 12,593 issue their own permits. The remaining municipalities require permits, however they submit to the Jurisdictional Authority of an adjacent Municipality or County to obtain those permits. Additionally, municipalities may choose to outsource permit processing to third-party private companies. OneClick Code has developed a patented process for enabling the geolocation of an address in its geographically defined Jurisdiction of Authority in order to ensure data accuracy.

OneClick Code personnel contact each of the 12,593 permit issuing municipalities on an annual basis or semi-annual basis to collect and verify roofing code and sales tax data for digitization involving at least 3,000 different types of documents. Anytime there is a major storm (hurricane, severe storm, etc.), OneClick Code calls the local municipalities within 72 hours to ensure codes are updated for the ensuing claims process.

When working to find the correct sales tax estimation, it is important to know that there are often multiple rates per zip code, county, and/or city. Determining tax rates based solely on zip codes will result in inaccuracies. To ensure accuracy, it is necessary to pull the sales tax information based on an address’ geolocated latitude and longitude, and not simply the zip code or the city which can lead to incorrect input rates and a possible notice from the local tax collector.

In the last two decades, the combination of the rapid rise in severe convective storm (SCS) frequency and severity and skyrocketing roofing costs have created a toxic environment that is punishing homeowners and property insurers’ alike.

• Between 2001 and 2017, there was a 7.5 percent per annum rise in claim severity and 3.3 percent per annum rise in frequency that combined to produce a growth of total loss, or SCS claims inflation, of 11 percent.
• Sales among privately held roofing contractors increased 13.5 percent and 15 percent in 2017 and 2016, respectively while the average profit margin for roofing contractors grew 4 percent annually from May 2014 to May 2018.

Incredibly in 2020, no one in the roofing value chain can confidently answer how much it should precisely cost to replace a roof. Below we highlight a hypothetical example of where an incorrect set of roof data inputs can swing the claim payout by 21%. Perhaps most astonishing in this example is the fact that the payment could be wrong in either direction, i.e. the insurer may end up paying too much or too little based on the data as depicted.