It’s no surprise that most insurers want to continuously refine their back- and front-office operations in order to streamline the auto liability claims experience. This is especially true for casualty claims: In 2016, U.S. liability auto insurance losses neared $100 billion. From a frequency standpoint, we know that property damage losses occur nearly four times more often than a bodily injury claim; however, the claim payout trends more than four times costlier for bodily injury claims. For many carriers concerned about the rising cost of these claims, the intelligence born of data and analytics now plays a key role in qualifying injury causation and managing the outcome of a medical auto claim.

Unlike APD claims, casualty claims comprise multiple layers of cause-and-effect physical metrics, many related to the vehicle, its immediate environment at the time of the crash (relation to roadway), the type and severity of the crash, and of course, the extent of the injuries sustained by the claimant(s). During this “moment of truth,” the insurer has but one opportunity to get things right.

Thankfully, these metrics are now tied to a host of new types of data available, such as telematics and advanced driver assistance systems (ADAS) that promote collision/crash avoidance. Ranging from adaptive cruise control to traffic sign recognition, these technologies are already commonly included on passenger cars to create a safer driving experience (manufacturers of 99% of U.S. automobiles plan to include automatic emergency braking systems as a standard feature on virtually all new cars sold in the U.S. by 2022, according to the National Highway Traffic Safety Administration (NHTSA) and the Insurance Institute for Highway Safety).

As more vehicles become equipped with these types of crash/collision avoidance systems, experts predict a likely reduction in the severity of both collisions and associated occupant injuries. Nowhere is this technology going to be more beneficial than in rear end collisions, which account for 33% of all police-reported crashes.1

And while insurers welcome the reduction in severity of these types of crashes, there remains a problem with inefficiencies around the investigation and evaluation of auto injury claims; at a minimum, whether certain injuries are consistent with the facts of the accident. These inconsistencies are frequently tied to low velocity impact (LVI) claims, and often lead to medical bill review mismanagement, overpayment, litigation and/or fraud.

Linking, Integrating for Improved Outcomes

Let’s follow the path of how linking and integrating data for analytics and intelligence purposes can improve outcomes, specifically to claims related to LVI and soft tissue injuries, which are often associated with the type of crashes outlined above.

Thankfully, we can now add the tracking of another metric to the data stream mentioned above—the impact-induced change in velocity (Delta V or g force), which is recorded at the time of the impact. An excellent gauge of the severity of the forces that are experienced by the occupants, Delta V is the gold standard metric for measuring collision severity and is highly correlated with injury potential.

Let’s look at the example of a top 25 P&C carrier that used a data analytics solution to improve how their claims department identified and assessed LVI claims. In reviewing 6,800 injury features, the carrier identified 2,340 that were associated with LVI, but where vehicle damages were not easily assessed by photographs and repair estimates.

The carrier further wanted to assess the impact of LVI collisions with vehicle damages that made it challenging for an adjuster to determine LVI, such as mismatched bumpers, crumpling outside of occupant cabin, etc. Why? Because manufacturers design vehicles to absorb and manage impact forces using crumple zones to lessen the impact experienced in the occupant compartment. This can result in damages that look dramatic, even in low and moderate velocity collisions, makes the adjuster’s job even harder, and affects loss adjustment expense.

So, the carrier sought to support the adjuster with analytical findings. Using a Vehicle Impact Score (VIS) from Injury Evaluation Solutions (IES) that is automatically generated from the repair estimate and provides a reliable, early indication of impact severity, the carrier was able to assess Delta V, and in the process, identify low impact collisions. These analytical conclusions, along with the adjusters’ key observations, enabled the carrier to then triage the LVI claims for proactive, early injury causation investigations and potential settlement.

This information was carried forward into the carrier’s medical and general damage assessments, improving the consistency and accuracy of overall injury evaluations and resulting in a predicted settlement accuracy gain of $6.8 million.

What if the insurer could combine the analytical conclusions above with intelligence related to the claimant’s clinical treatment? An Auto Injury Solutions (AIS) analysis of Professional Reviews for a Top 10 auto insurer becomes our next case in point. The analysis, requested to address complex medical considerations, such as relatedness, medical necessity, and the appropriateness of treatment duration, focused on a month’s worth of AIS Professional Reviews and included a detailed narrative along with recommendations from a Registered Nurse and a Certified Medical Coder.

Here’s what they found:
· 89% of the medical documentation for soft tissue cases lacked clinical reasoning for extended treatment durations.
· MRI’s were often ordered despite no documented neurological deficits or orthopedic testing. Furthermore, the MRI’s did not change the course of treatment.
· Injections were prescribed before conservative treatments were utilized.

However, when nurses outlined clinical reasons for recommended treatment end dates, it resulted in a median reduction of 44 days. These clinical opinions expedited and improved the overall assessment of injuries and medical special damages considered in the final evaluations, which, in turn, provided a basis for benchmark recommendations and enhanced negotiation strategies. Further, these findings are now being used by claims handlers to inform future evaluations and negotiations.

Creating consistent benchmarks, freeing up the adjuster’s time, reducing loss adjustment expense, increased loss cost management accuracy and avoiding fraud: There is no downside to data analytics and artificial intelligence advancements that afford insurers the ability to more accurately assess APD and link it to successful evaluation and qualification of injury causation. From automating first notice of loss to estimating auto physical damage severity and potential severity of injuries, insurers that embrace these advancements will become the leaders in reducing claims costs, increasing customer satisfaction and improving business outcomes.

Chris Brew, SVP Casualty, CCC Information Services Inc.

1 2015 Motor Vehicle Crash Data from FARS and GES.

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