Big data can be an incredible competitive differentiator for insurance companies -- or could be the source of their demise, if they allow other businesses to gain the upper hand in the use of analytics and data to better manage and price risk and create new, more profitable products. That is a theme (and warning) I've heard several times over the past week, most recently at the Technology Super Session presented on Monday at IASA's Annual Conference and Business Show, underway in National Harbor, Md. Thornton May, futurist and executive director of the IT Leadership Academy, told attendees that, "Big data is going to be the most disruptive technology impacting your industry," and is the technology area that must be top priority for investment.
[Novarica's Martina Conlon argues Big Data Not Yet A Best Practice In Insurance]
However, it also is an area that is experience a significant degree of what May called "de-synchronization," where the pace of change is not uniform. "Some things are changing fast, some are not; some are close to being ripped to pieces, some parts you can't change," he said. This means there is a "disconnect between our ability to create, collect and store data -- and our capability to thoroughly process and exploit it," May explained.
The challenge, he continued, is not about the volume of data. "Everyone knows there is a lot of data. That's not news," May said. "But we truly are at a hinge of history, because the world has changed its mind about data. People at the top of the organization -- the bosses -- discovered data. It used to be someone else's job. Now they expect someone to do something with all that data -- that's what changed."
The ability to "do something" is the differentiating factor, according to May. "You have to be able to observe, orient, decide and act" -- May used the anagram OODA -- faster than your competitor. Without mastery of big data, basically you are blind and they can see. Organizations that can't do this are getting eviscerated by the people who can."
May advised insurers to "Be very aware of the pace of big data experimentation going on in your market space. Articulate a timeline for competence and mastery [to determine]: 'How long will it take me to get good at this stuff?'"
A similar theme was sounded by Novarica managing director Matt Josefowicz at last week's L&T Infotech, Ltd. Insurance End-User Leadership Forum. Covering the topic "Insurance Underwriting in an Age of Data Super-Abundance," Josefowicz observed that once-very-expensive or hard to access sources of data, such as government or medical data "will be accessible thru data calls in ways they are not broadly today." He noted that, although they haven't mastered it, insurers are working on ways to take advantage of new kinds of data such as social media, clickstreams and telematics. "They are using telematics to refine underwriting and rating models," he said.
In this environment, Josefowicz added, "The level of effort and locus of value changes from gathering to analyzing. It used to be possible to know more than your competitors by gathering more information. But that locus of advantage is rapidly diminishing because of all the third-party data. Everyone is able to ask the same questions and buy the same data." The competitive advantage will come in organizations' varying abilities to analyze the data, he predicted.
This has tremendous implications for underwriting, according to Josefowicz. Previously, he noted, the difficulty of gathering enough information about prospective risks was high, "but today that is much lower." The opportunity to differentiate by asking the right questions also is going to be less likely in the future. At the same time, the opportunity to outperform or differentiate in analytics is increasing. And, Josefowicz pointed out, "the transparency of the underwriting process used to be very low, but it's getting higher and higher every day."
The evolution of insurance underwriting will be focused "on streamlining process, increased use of third-party data, automated decision capabilities, and efficiency and effectiveness," Josefowicz said. Beyond this, he predicted the emergence of new players, perhaps "funded by capital markets firms looking for yield," that will be based on "a complete rethink of the underwriting process." A data-enabled player would be able to be more selective about risk -- "there is more opportunity to pick risks you want and spend less time throwing out risks you don't want," he explained. This would "move risk selection from underwriting to marketing through 'pre-underwriting,' which would radically change the cost basis of the process."
The traditional underwriting process, Josefowicz argued, "was designed for a world of information scarcity and is trying to adapt now to information super-abundance." The potential threat to insurers, he predicted, is that "someone with a blank sheet of paper will come and say, 'We're trying to price risk -- how do we balance the cost of information against the quality of models we can build from that?'" The solutions they develop "will not look like underwriting process as we know it."