The Growing Power of Data in Insurance Product Development

By Monique Hesseling, Partner, SMA Strategy Meets Action

Monique Hesseling, Partner, SMA Strategy Meets Action

Over the last years insurers have made great progress in using both their own as well as external data for reporting and analytics. After putting operational KPIs in place and reporting on those, many insurers moved into more predictive capabilities around customer profitability or optimization of their distribution channels. Although those were great improvements over times past, these reports and analyses were still primarily based on historical internal data, sometimes augmented with demographics. More recently we have seen insurers start using internal and external data to develop new products and services. This growing trend has been supported by a couple of emerging developments: analytical tools and skillsets have become more commonly available, external data sources and toolsets have become more prevalent and easier to use, the upcoming Internet of Things allows for many more data points than ever before, and customers (be it distributors or policy owners) ask for much more personalized experiences than in the past.

Let’s take a look at each of these developments and discuss how they play together in product development.

Analytics: Although carriers, especially those that are smaller, are still struggling to attract and retain data scientists, current analytics solutions are enabling business people to run their own custom reports, design their own dashboards, and even create their own models based on pre-defined data sets – all in a visually appealing and easy to read way. These new analytics technology solutions have provided carriers with much better insights into their own data and have given them the ability to manage their books of business and customer interactions in a more granular way, allowing for more targeted decision making that supports profitable growth and operational efficiency. Targeted customers are more easily identified, thanks to additional segmentation criteria, and the most suitable proposition can then be offered to these insured and prospects. The resulting analyses also provide more pinpointed insights about which product features are likely to be of interest or not, and what each feature in a particular product contributes to the actual performance of this specific coverage.

External data sources and toolsets: Insurers have used demographic data, some location specific data, and hazard data for a long time. Until recently, they did not have good ways to customize, visualize, and access these data sets easily. Consequently, they relied heavily on externally created models. Newer, modern analytical tools, coupled with more intuitive forms of modeling and/or analyzing data, augmented by powerful visualization tools, and preferably supported by mobile and digital capabilities are now bringing data analyses and modeling to the masses. Analytics and modeling is no longer the prerogative of only a small group of very smart and experienced data scientists. Today, every insurance employee can get insights from internal and external data. Currently, we are seeing modeling and reporting, especially around distribution and customer/market segmentation, being driven by the business users with limited involvement from IT. The influx of external datahas led to much more fine-tuning in distribution management, acquiringand retaining new customers, and personalizing offerings and services. As a recent SMA study shows, over 80 percent of insurers in the USA have a strategic investment focus on data and analytics, outranked only by 85 percent having strategic initiatives in place to enhance their customers’ experiences (Strategy Meets Action 2015).

New intuitive visualization tools allow for data sensing, capitalizing on both structured and unstructured data. We see these exploratory analytics being used to sub-segment customers and agents as well as to identify unmet product needs, mainly around non-mainstream coverages such as art, classic cars, extreme sports, unusual building materials in homes and offices, or events. This kind of technology enables insurers to create insurance products and services that are based more on dynamic behavior and events rather than on static assets. This is a major next step in insurance product development.

“Telematics data enabled commercial insurers to assist their customers with better driver management, optimize routes and truck use, and improved claims prevention and handling”

The Internet of Things: Very recently, insurers have started to use IoT data to support their clients with individualized products. The first highly visible wave of applying IoT data was evident with telematics. Telematics data enabled commercial insurers to assist their customers with better driver management, optimize routes and truck use, and improved claims prevention and handling. Personal lines carriers followed quickly with telematics-based product offerings that considered where and when people drive, and later by how they drive. More sophisticated offerings included immediate driver feedback,credits for improved driving, and young driver support. The most advanced personal lines telematics-based offeringsin Europe and South Africa include services such as concierge services that reschedule your meetings if the car predicts that you are running late, discounts for gas stations and coffee along your route, and free maintenance services if you’re driving improves significantly.

The latest new insurance products incorporate another application of IoT data via sensors. Shipping containers and airline luggage get outfitted with a tracking sensor, allowing customers to monitor location, and in some cases the temperature and humidity of their cargo. Bike manufacturers have started to include trackers in the frames of new high end bikes to help locate them in case of theft. Home monitoring systems can ping the insurer when a stove is on for too long and overheating, or when electrical wiring needs to be fixed. People use individual fitness trackers and get discounts on their life insurance. And, in hospitals, sensors on critical but mobile equipment are able to proactively ping the nursing station when the equipment is not returned to its rightful place. All of these examples are being sponsored, supported, or instigated by insurers. They all create a better customer experience – and hopefully fewer claims. They also allow for much more individualized product offerings, and for more touch points with insureds than insurers have ever enjoyed.

When we consider all these different trends around the use of data and analytics, a couple of conclusions become readily apparent. In the coming years, insurance products will be much more individualized and event or activity targeted than they have ever been. Insurance offerings will incorporate value added services that manage risks and exposures better and consequently limit losses. Prevention will be a bigger part of the actual offering, and the customer experience will improve thanks to more frequent and targeted touchpoints between the customer and insurer. I think we can agree that all of these are great things, benefitting insurers, their distribution partners, and their insured – all because we are finally able to access and use all the data we have to pinpoint which true risk to insure or mitigate. Exciting times for all of us data aficionados!!

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