Group Insurance Data in the U.S. - Moving Beyond the Rearview Mirror With Customer Data
While driving to the office recently, it occurred to me that when it comes to assessing and pricing risk, the U.S. group insurance industry is still primarily using a “rearview mirror” perspective. The rest of the world is well on its way with embracing new predictive technologies while we lag behind in our business. At a time when Property & Casualty insurers are exploring cutting-edge solutions, such as “usage based insurance and telematics” for auto insurance (Big Data), group insurers continue to struggle to capture and store basic information (little data) about the end customer - the individual.
It’s been two years since our last blog about challenges when it comes to acquiring good data for U.S. group insurance. At that time we asserted that most group insurance carriers had very little data on the individuals covered by their plans. Carriers were receiving life-by-life census/exposure data at time of sale (and hopefully at renewal) but struggled to keep it up to date. Even if they were able to obtain current data it couldn’t be accessed easily. Here we are 24 months later and, how far have we come?
The Stakes Are High
If you happen to be a weather geek like me, perhaps nothing better illustrates the importance of quality data (and utilization thereof) than the difference found between the U.S. Global Forecast System (GFS) versus the European Centre for Medium Range Forecasting (ECMWF) weather model. The European model is more accurate because it uses more data and has a better simulation system…hmmmm.
The quality, accessibility and utilization of data is just as important to the insurance industry. Carriers that have industry leading capabilities not only have a leg up when analyzing their historical experience, but more importantly the ability to capitalize on the opportunities that predictive modeling represents.
The good news is we are hearing more and more that carriers are making solid progress in improving the quality, quantity and accessibility of their data. This is true not only at the group/employer level but, more importantly, at the individual level as well. The continued migration to employee-paid, worksite- and exchange-friendly group products have certainly been factors. The proliferation of benefit admin systems/providers - such as ebenefit marketplace, ADP, Oracle PeopleSoft, Zenefits and PineappleHR, to name just a few - has undoubtedly also had an impact.
Presuming we are well on our way to being the master of our traditional data needs, are we tracking the right things? Now that our customer is increasingly becoming the individual rather than a group employee plan, knowing what influences his or her purchasing decisions is paramount to our success. One way insurers can position themselves to understand the end customer better is through the use of behavioral economics.
Whether it's big, small or data we haven't even thought of yet, group insurers will need to continue to focus on better ways to capture and use information about individual customers. One thing is for sure, Gen Re will continue to challenge our clients to think differently about their business and provide the technical and strategic insights to assist them in these very competitive markets.
In case you missed it, read our article on Putting Behavioral Economics to Work for the Insurance Industry.