(Roger Burkhardt is president and CEO of EagleEye Analytics)
It can seem as if the auto insurance industry has shifted into overdrive, as large insurance companies like Progressive, State Farm, and Allstate are aggressively promoting their telematics programs and associated discounts to attract the best risks. Many of these large carriers have been developing their telematics—or pay-as-you-drive programs—for years.
For mid-sized carriers, competition to gain new customers—and more importantly, retain existing customers—in the personal auto insurance market is heating up at an unprecedented pace. While some mid-sized carriers may feel the pressure to implement telematics initiatives of their own just to keep up, many others are taking advantage of new technology and creative solutions to combat adverse selection without actually putting telematics devices in the customers' cars.
New Technology Can Level the Playing Field
While more accurate pricing of risks is necessary for mid-sized carriers to compete, following the leader is not. It is important that each carrier select the right initiative based on its business strategy and size. Many have ruled out telematics because of the cost, resources required, and timing, and are having success with other technology initiatives.
One option for carriers is to forego any kind of in-vehicle equipment and use predictive analytics to determine more accurate pricing. For example, we're working with a mid-sized insurance carrier that is blending predictive analytics with better territorial definitions in order to price its auto risks accurately.
The carrier is using micro-segmentation to predict mileage and risks associated with driving patterns, and fine-tuning its pricing and discounts to remain competitive and retain its best customers. This type of device-less approach avoids alienating customers (who may not want a "black box" in the car), and gives the insurer an effective way to compete.
Traditionally, auto policies have been priced based on factors such as age, gender, location, credit score, and certain historic data. Robust predictive analytics, using machine learning technology, allows carriers to evolve the pricing structure by pricing policies using many more factors. Predictive analytics software looks for combinations of data elements that are highly predictive of a future outcome.
Carriers can view and leverage data in a way that they couldn't before, giving them greater flexibility in a competitive market, especially when that market is rapidly changing. And advanced predictive analytics solutions are now available on a SaaS basis, or in the cloud, eliminating large IT capital costs and IT staff costs in installing and managing specialist in-house software.
For insurers that determine that telematics is right for them, there are ways to reduce some of the costs involved. Smartphone applications, with GPS, already in widespread use, may offer a less expensive alternative to black-box technology but deliver similar data without investment in hardware. Smartphone applications combined with SaaS-based predictive analytics technology provide another less expensive option for mid-sized carriers.
Information such as the time of day, day of the week driven, location driven, and speed driven—much of which is available through GPS and the smartphone—has proven to be the most predictive. Carriers are using this model to infer driving patterns from location-based analysis. GPS devices collect fewer low-value variables than telematics devices do; there is less data to store and interpret.
Beware: Telematics Initiative Can Tax the Carrier's Resources
For mid-sized insurers that often have limited resources, telematics is a complex and costly solution. Adopting telematics is a time consuming process. It can take a year or more to implement and up to five years to see actual results, which can distract the carrier significantly. Further, after telematics has been introduced, there are additional challenges including transmitting, storing, scrubbing, and analyzing the vast quantities of data involved, an area where few insurers have expertise.
The continuous and ongoing nature of the data makes capture and storage a difficult management problem. In addition, mid-sized insurers do not always have the resources to develop, test, or market the numerous policy models that large insurance companies do. The amount of data to sort through makes it increasingly difficult to figure out what's predictive and what's not.
And beyond the technology costs, there are also other potential issues. Some customers, who are very good risks, may not want the black box in their cars. And, if this is the only way they can get the best pricing, there can be a disconnect. Large carriers may view this as a cost of doing business. But for mid-sized carriers, where strong insured relationships are part of their brand, there is a risk of alienating drivers with a one-size-fits-all telematics program.
Mid-sized auto insurance carriers are facing an increasingly competitive market—one that is likely to continue to change rapidly. While some may be feeling pressure to implement telematics, there are other options to consider. In fact, many leading players are using new technology and other solutions to more accurately price their risks. These carriers are leveling the playing field with large carriers that rely on discounts to attract the best risks.
One thing is clear: The market is moving fast, and it is important for mid-sized carriers to develop plans now to combat adverse selection, and move forward quickly.
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