Data analytics is bringing a lot of predictive and adaptive capabilities to many areas of insurance — from fraud detection to telematics to customer management. Analytics may also have a powerful impact on what is probably the industry's greatest strength — agent networks. However, this is a strategic advantage that is too often overlooked.
I recently had the opportunity to catch up with Tom King, senior director of insurance at Pegasystems, to chat about the possibilities data analytics offers to the industry. King, who works with numerous clients in the emerging area of big data analytics, says the potential for data analytics is impressive once insurers look past the more well-known applications in the direct-sales arena.
Data analytics itself has changed quite a bit in recent years, he observes. “If we were having this conversation five years ago, people would be talking reporting if they were talking about analytics,” he says. “Not that reporting isn’t important, but it’s not the same thing as what companies can do today and how they can leverage data.”
There is a great deal of analytic activity taking place with real-time fraud detection and customer tracking. But that’s only one part of the picture, King says. “There’s a whole host of other things that insurers can be doing with information,” he explains. “Something I don’t think a lot of insurers think about is using analytics to support independent agents. The conversations tend to circle around direct."
Providing analytics or generating analytics from agent networks isn’t a straightforward task especially in situations where there are independent agents. “You don’t own the desktops of individual agents,” King says. “And you can't tell the independent agent what to do.”
However, there are ways to leverage data with independent agents, King continues. “You can take the book of business that they have and analyze it, and say, 'based upon your book of business, here’s some of our products that you can sell into your existing book that you may or may or not know about.'” Often, agents may not even be aware of insurers' entire product lines, he adds. Such information helps “create that conversation with the agent” to recommend and promote profitable product lines. “Using analytics, you can do that push.”
Data analytics also plays a role in managing relationships with independent agents, King continues. While relationships vary, “being able to have visibility into all of your agents, and identifying — using analytics — which agents are doing well for you and need to be rewarded, and which ones are struggling and need some help and which ones aren’t bringing you any business. This is something that analytics can do for an insurer on a real-time basis,” he says.
The ability to employ data analytics to support agent networks is an area that needs more attention and focus, King says. “Everyone wants to talk about direct, but much of the business today is still sold by agents. Most commercial lines, and all group insurance, are sold by agents. We’re really only seeing true disintermediation on personal lines of property/casualty, and you’re starting to see direct sales in regular, the individual life lines. But the agency model is still very much alive and well.”
Often, insurers don’t have a great deal of control over desktops on the agents and brokers systems. “Insurers have to figure out creative ways to work with the agent and support them,” King says. Data analytics can help this relationship.
Joe McKendrick is an author, consultant, blogger and frequent INN contributor specializing in information technology.
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