By the numbers: How technology is reshaping auto claims

Data analytics for insurers are leading to more accurate claims resolutions.

Several technologies and innovations such as machine learning, artificial intelligence, data analytics are reshaping the way auto insurers conduct business and capture claims information. (Photo: Shutterstock)

The auto insurance market is facing a variety of near-term and long-term pressures that could eat into profits. Conversely, new data technologies and innovations are providing the data to combat these threats, helping insurers maximize their potential for a healthy bottom line.

In the near term, the industry remains on solid ground. According to Deloitte, in the P&C sector, U.S. premiums written grew 4.6% in 2017, the highest percentage in the past decade, before jumping by 12.7% in the first half of 2018.

However, more longer-term outlooks are less clear, mostly because of all the talk of autonomous vehicles. Autonomous vehicle technology, a rise in on-demand transportation and a shifting of liability to manufacturers will shrink the auto insurance sector by more than 70%, or $137 billion by 2050, according to research by KPMG.

Changes ahead

Several technologies and innovations are reshaping the way auto insurers conduct business. For example, everything from artificial intelligence, machine learning, Internet of Things, big data analytics, automation, chatbots and telematics are all impacting insurers and their business models. More specifically, a handful of these technologies are having a direct impact on how claims are processed for customers and their vehicles.

Case in point, the last two years have seen deadly hurricanes hit various locations in the U.S., and these storms provided damage to property, homes and vehicles well into the billions of dollars.

When insurance companies need to calculate payouts, the most critical aspect of the entire process is having access to the most timely and accurate valuation on each vehicle in the portfolio. However, not all valuation services are created equal, and leveraging the wrong value, multiplied over several thousand vehicles with payouts, can be financially devastating to an insurer.

Today’s advanced valuations include data analytics to provide more precise valuations. These VIN-specific data resources take into account each individual vehicle’s unique history footprint, helping insurance professionals determine the impact a vehicle’s history has on its value, both current and future. Even with the use of vehicle history reports, insurance professionals are still reliant on automotive values based on an unscientific, subjective, educated guess as to the impact a vehicle’s history has on its value, which often leads to mistakes and inconsistencies in the valuation and payout process during claims processing

Vehicle values that take into account a VIN-specific history can be as much as 31% more precise when compared to the auction transaction price than valuations without a history adjustment included. This is possible since today’s analytics process leverages data that can help professionals quickly pinpoint a more precise valuation on two individual vehicles of the same year, make and model, based on data inputs that take specific vehicle history events into account. Making an inaccurate estimation of appraisal values can decrease margins for a dealer, as well as increase losses for insurance companies and auto lenders.

History-adjusted vehicle valuations analyze multiple factors and events in a vehicle’s history such as number of owners, vehicle usage, accident and accident severity, title issues, flood/hail/fire damage, CPO history, and other variables that are not obvious when physically inspecting a vehicle.

Insurers have long relied on vehicle valuation data in order to help determine the right payout for each vehicle damaged or destroyed in an accident or natural disaster such as a hurricane. Over the last few years, these natural disasters have been a large reason why large numbers of vehicles have been destroyed, and there is a good chance this pattern will continue in the years to come. With the right tools and resources, such as data- and analytics-driven valuation insight that takes into account each vehicle’s unique identifiable history, insurers can be even more precise in determining the exact vehicle payout to keep clients happy and preserve the right margin in each vehicle portfolio.

Jared Kalfus is executive vice president, revenue, for Black Book, a division of Hearst that provides industry-leading used vehicle valuation and residual value forecast solutions. Black Book works with automotive insurers to provide accurate, timely, independent vehicle valuation data for clients and portfolios. For more information visit www.BlackBook.com.