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The Rough Notes Company Inc.



February 27
09:26 2018

ISO Emerging Issues Perspective

Can automated processes facilitate quick and effective resolutions?

Today’s cars are smarter, and that means auto insurers need to be smarter, too. Modern vehicles collect vast amounts of valuable data, and original equipment manufacturers (OEMs) are preparing to share it with the vehicle owner’s consent—if insurers are ready to receive it and realize its potential for more accurate underwriting, more efficient operations, and a better customer experience from quote to claim. This trove of data can lead to a previously unthinkable automation of processes driven by machine learning and artificial intelligence (AI) that accelerates decision-making across multiple workflows.

A policyholder potentially stands to benefit from a tech revolution that can initiate and augment the claims process by pulling in the data when a claims systemor adjuster needs it.

But connected car data typically doesn’t fall into an insurer’s lap ready to be interpreted and implemented. This data tends to come from many sources, including newer vehicles with embedded connectivity and unconnected vehicles in which the data is collected by dongle, smartphone, or tethered solutions. The different means of collection can also result in wide variations in the amount, type, structure, and granularity of the data collected.

Such data is not necessarily designed for insurers’ direct consumption. Deriving insights, therefore, can be difficult, time-consuming and costly if an insurer attempts to go it alone. This is where a data exchange—a place where data is sorted and scrubbed—can help insurers over the hurdles to realizing the potential of connected car data. Combining normalization of disparate data with an understanding of the insurance landscape requires a partner that has:

  • Experience with state-by-state insurance regulations as well as insurance data analytics relating to rating, loss costs and claims
  • Capability to build and manage integrations among many telematics service providers
  • Resources to standardize, normalize, analyze, and deliver data to help support insurers and their underwriting and claims workflows.

Powering up UBI

A data exchange can power usage-based insurance (UBI) and telematics-driven claims programs by collecting and normalizing data from OEMs, telematics service providers (TSPs), and other sources to solve the “many-to-many” problem of linking automakers and telematics service providers with a field of insurers.

If an exchange carries a full suite of capabilities, it can streamline the policyholder experience, reduce costs, and improve efficiency, as well as use the data within the existing claims workflow. Insurers could access data on driving behavior before a policy is written or even before a vehicle leaves the scene of an accident.

For UBI purposes, an exchange would provide a single, efficient access point for vehicle and fleet driving data as well as access to a wider scope of vehicle classes and industries. An exchange might also act as a complement to insurers’ existing solutions and provide them an opportunity to use UBI-based rating guidance. Ideally, the exchange should be flexible enough to allow insurers to bring their own models or leverage third-party models and analytics.

The rise of connected cars has accelerated the development of insurance telematics. Starting with simple, mileage-based UBI, this evolution has progressed to providing driving feedback and driver coaching enabled by driving data, which in turn can affect premiums and losses. Coming online just recently is crash and event notification data identified from the vehicle’s data control module.

It seems likely that the next frontiers include crash events with contextual data, detailed electronic data recorder (EDR or “black box”) data, event replay, no-touch claims, and proactive services to reduce the number of accidents.

Service through science

As telematics-enabled services move up the development curve, new technological tools come into play, including machine learning (that is, training the models) and AI. Some of the most exciting possibilities lie in the realm of claims. Whether for auto, property, or workers compensation, first notice of loss (FNOL) can be initiated instantly from an event trigger. With policyholder collaboration and the application of AI, 20% of no-touch and 30% of low-touch claims can be within reach, with conventional adjusting still applied to more complex claims. The results can lead to faster cycle times, lower costs, and, ultimately, greater policyholder engagement and satisfaction.

Moving toward no-touch claims can start simply with easy, one-vehicle events involving only a driver and a car that’s still drivable and connected. For example, the connected car allows the insurer to know the accident’s severity and damage through the electronic data recorder information, including occupant information and a plethora of data points that enable reconstruction of the event. The vehicle senses it was in an accident, and the exchange normalizes the transmitted data and provides key algorithms to train the models through machine learning and AI. This allows the claim to be routed automatically. The implications of such revolutionary technology affect policyholders, insurers, and their claims staff.

A policyholder potentially stands to benefit from a tech revolution that can initiate and augment the claims process by pulling in the data when a claims system or adjuster needs it. This bypasses traditional procedures—possibly waiting days for police reports, policyholder testimonies, and disparate data, which are then left to an adjuster’s judgment. A vital component is insurers’ understanding of policyholders’ privacy concerns relating to sharing their driving and accident data. Customers want faster claims resolution, but they may fear the insurance company will raise their rates, even over a small claim. Therefore, transparency about how and when the data is used is critical for insurers to gain customers’ trust.

Claims staff need to understand that automating claims will change how they work. Staff may be able to spend less time on simple claims and gain more time for complex claims that require deeper expertise. This means they may have to redeploy their talents, and insurers will have to ensure they have the right teams to embrace a no-touch future. Learning new technologies, streamlining processes, and optimizing data will help employees better serve their customers and possibly gain greater job satisfaction.

What will claim automation look like in the future? Insurer collaboration with various industry partners will be critical to achieving progress. Telematics data changes the process by harvesting available evidence to expedite claims resolution, rather than relying on the often drawn-out collection of individual testimony. Whether data is collected by a smartphone, dongle, tethered device, or embedded telematics, a crash can be automatically detected; and analytics from the data exchange enable fraud detection, damage and injury triage and resolution, liability analysis, and adjudication plus closure. Together, these elements help determine a quick and effective resolution for the claim, and likely will result in a more satisfied customer.

 The authors

Dawn Mortimer is assistant vice president of IoT/telematics—personal lines auto telematics product development, at Verisk (Nasdaq:VRSK). Saurabh Khemka is senior vice president and general manager of IoT/telematics at Verisk.

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