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Determining liability in auto accidents is fraught with challenges: incomplete or unreliable information feeds into a game of he-said, she-said; clunky arbitration processes prevent claims teams from presenting their best defense; and operational inefficiencies delay decisions and rack up expenses.

It’s an area ripe for digitization, and one in which AXA XL has been seeking innovative solutions. Today, with our partnership with Xtract, we finally have a way to leverage data and technology to produce more streamlined claims management and better outcomes for all.

There are many problems plaguing claims processing and liability determination in motor claims, including;

  • Crash data is incomplete or too subjective. Most commercial fleets today employ some type of telematics system. In the event of a crash, telematics devices tell us if either party was speeding, slammed on the brakes or swerved suddenly.

    Unfortunately, accessing and interpreting raw telematics data is not simple or intuitive. Claims organizations typically contract a crash reconstruction specialist to extract and make sense of the information which can range from $2,000 - $5,000 per claim.

    Claims handlers also have information submitted to them by insureds and brokers on First Notice of Loss (FNOL) submissions, including a brief description of the accident and resulting damage, police reports, and photos. Some of this information, however, is based on drivers’ first-hand accounts, which may be skewed by bias or imperfect memory.

    Simply put, the complexity of interpreting telematics data and incomplete or inaccurate FNOL submissions present challenges for claims handlers. Other relevant information such as road conditions, weather, and the activity of vehicles in the moments just before impact all contribute to crash dynamics but aren’t captured in an objective way.
  • Submitting and reviewing data in arbitration is too fragmented. Many insurers opt to settle claims via an arbitration forum rather than go to court. Unfortunately, the traditional method of submitting data to the arbiter does little to help to recreate a seamless narrative of how the crash unfolded.

    Most of the information submitted is raw text and a sketch of the accident, which provides incomplete visual context for the scene. Though photos are often included, these capture only a moment in time and typically serve as testament to the damage inflicted, not the circumstances surrounding the incident or the broader environment in which it took place.

    These pictures and documents are uploaded to the forum in piecemeal fashion, leaving it up to the arbiter to click through each item and piece together the story on their own. This robs each party of the opportunity to present a strong case and fully defend their position.

Exploring A New Solution
These technological roadblocks extend claim duration as it takes more time to collect, analyze, submit and review relevant data. Today, a handler spends weeks manually collecting data to piece together an understanding of the event and make a liability decision. The longer a claim stays open, the more expenses it accrues.

Earlier this year, the AXA XL Environmental Auto claims team conducted an extensive Proof of Value (POV) with Xtract, a provider of motor claims analytical software, to see if it could solve the inefficiencies inherent in the claim process and determination of liability.

The answer was a resounding yes!

Leveraging the Xtract platform, AXA XL was able to identify and dramatically improve the end-to-end claims process yielding a significant return on investment (ROI).

Leveraging the Xtract platform, AXA XL was able to identify and dramatically improve the end-to-end claims process yielding a significant return on investment (ROI).

Xtract’s data aggregation and visualization capabilities directly contributed to two unlikely arbitration wins. Liability determinations were decided more quickly, meaning claim duration and associated expenses shrank, vehicles were returned to the road sooner, and we were able to deliver thousands of deductible dollars back to our clients.

Here’s how the software works:
Telematics + Digital FNOL = A Visual Narrative of the Crash Scene

Telematics data is critical in accident reconstruction.

Roughly 56% of North American commercial vehicle fleets have telematics devices installed, a figure growing by 11% per year. Attitudes around data-sharing have also shifted, with more organizations eager to reap the efficiency gains and cost-saving benefits of analytical insights.

Xtract is unique, as they are device-agnostic, meaning they can utilize data from any telematics provider. Speeding, swerving, and hard turning or braking can indicate dangerous driving that caused an accident or even attempts to avoid one. Xtract analyses data from 10 seconds preceding and accident and following impact and combines it with other data sources to better illustrate how the incident unfolded. If a claim gets disputed, this objective data is the foundation of the accident narrative.

The Xtract platform also includes a digital FNOL function, which allows brokers and insureds to upload a reconstruction of the event including photos, police reports, notes and other data in one central location where it is immediately accessible by the claims team.

The software then aggregates that information with supplemental data – like weather conditions, vehicle details, Google maps imagery of the road and surrounding environment, and additional photos and video pulled directly from connected dashboard cameras (where applicable) -- and uses it to create a comprehensive, visual recreation of the crash scene.

The result is quicker, more accurate claims processing which lowers operational expenses and improves liability exposure.

Proof of Value Success Story
In the course of our POV, digital FNOL functionality enabled some unlikely arbitration wins.

One case appeared to be clear-cut; damage to both vehicles indicated our insured had rear-ended the claimant. A police report supported this conclusion, and we estimated that we had less than a 50% chance of winning a favorable determination of liability.

Aggregating the claim information using Xtract showed us that the other party had abruptly changed lanes and cut our insured vehicle off, which precipitated the impact. 
With the click of a button, a PDF document was generated which allowed us to present this information with a logical flow, supported by illustrations that reconstructed the sequence of events and our own written explanations. Ultimately, we presented a stronger argument and the arbiter decided the case in our favor, overturning the determination made by the police report. This case alone saved us $21,000 and, most importantly, our client their deductible.

Benefits for Commercial Fleet Owners
Tapping into the power of telematics data has long been a challenge in auto claims management. The information needed to drive faster, more accurate decisions has always been there, but was too disconnected or buried too deep to be usable. Xtract brings transparency, cohesion and actionable insights to disparate data. 
The result has been better claim outcomes for our clients, shorter claim cycles, and operational efficiency that yields not only cost savings, but a higher standard of customer service. 

About the Authors
Ryland Box is Claims Manager for AXA XL’s Environmental P&C business and Greg Simotas is Claims Team Lead at AXA XL. Michael Flanagan is CEO of Xtract.

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In the US, the AXA XL insurance companies are: AXA Insurance Company, Catlin Insurance Company, Inc., Greenwich Insurance Company, Indian Harbor Insurance Company, XL Insurance America, Inc., XL Specialty Insurance Company and T.H.E. Insurance Company. In Canada, coverages are underwritten by XL Specialty Insurance Company - Canadian Branch and AXA Insurance Company - Canadian branch. Coverages may also be underwritten by Lloyd’s Syndicate #2003. Coverages underwritten by Lloyd’s Syndicate #2003 are placed on behalf of the member of Syndicate #2003 by Catlin Canada Inc. Lloyd’s ratings are independent of AXA XL.
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