Carriers Inject BI Across The Enterprise
Insurance Networking News, July 1, 2008
No doubt to the vexation of carriers and vendors alike, business intelligence (BI) and predictive analytics are often lumped together. Given the rapid growth of the technologies in recent years, the confusion is understandable, especially when one considers that both technologies use the wealth of historical and third-party data insurers have on hand to build models to either augment human decision-making or eliminate it altogether through automation.
Despite this cosmetic resemblance, the differences are profound. Historically, BI has become synonymous with operational metrics and monitoring, querying and reporting functions. Modern BI solutions generate scorecards, a collection of metrics and reports on a unified interface used to measure against objectives and dashboards, which use metrics to give users the pulse of an organization. While BI is reactive, and looks backward to gauge performance, predictive analytics seeks to use data in real time for sub-second decisions to affect future performance. While BI tools enable slicing and dicing and give insurers a high-level view of what’s going on, predictive analytics promises insurers actionable knowledge and a granular view of their operations. Thus, if BI is a look in the rearview mirror, predictive analytics is the view out the windshield.
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“It’s not just analyzing, finding something interesting and wondering what you can do with it,” says Colin Shearer, SVP for market strategy for Chicago-based SPSS Inc., supplier of predictive analytic solutions, “it’s the ability to go seamlessly from analyzing historical data, finding hard facts, then deploying them to improve your processes. We can embed our models live in an operational process and in the systems that support them.”
A TREND, NOT A FAD
Yet, whether considered separately or lumped together, business intelligence and predictive analytics are no longer seen as optional and are now established as a cost of doing business, especially in areas such as personal auto.
“For operational decisions, such as underwriting and claims, use of business intelligence and predictive analytics is going up rapidly and ubiquitously,” says Mark Gorman, principal of St. Paul, Minn.-based Mark B. Gorman & Associates LLC. “It’s no longer a simple ROI discussion, it’s no longer something you can put off until later—if you are going to be in the market, you are going to have to do it.”
Gorman says there are several factors for the expanded use of the technologies ranging from industry demographics to broad acceptance from upper management. “It’s well established now among actuaries and senior managers that this methodology and process is the wave of future,” he says. “This is a trend, not a fad.”
A second, perhaps more important trend Gorman sees is the technologies being used more for performance and strategic purposes. “We’re seeing more applications for strategic decisions about things like entering new territories or distribution channels,” he says.
Gorman isn’t alone in seeing the value of increasing BI deployment across the enterprise. Considering the ascendancy of service-oriented architectures and the advent of Web-service platforms that allow carriers to pull data from a variety of systems across the enterprise, it is not surprising that use of BI has spread apace.
“The value of BI is that it offers you consolidated analysis from disparate data sources,” says Craig Bedell, director of Global Insurance Services for Ottawa-based Cognos, a business intelligence company recently acquired by IBM. Bedell says that when it comes to data analysis it is best look at the pond, not at the stream feeding it. Thus, by aggregating data from across enterprise for analysis, the whole is indeed greater than sum of its parts, Bedell says. “Having BI as an enterprise capability, and using the insight you get from one department in another department, is key. If you can understand claims activity relative to agent or type of business, doesn’t it make sense to feed that type of info back to distribution management?”
One area were predictive analytics was quick to gain traction is in claims. Carriers can use analytics to assess prior claim history and then drive decisions within the claims process. Bill Dibble, SVP of claims at Birmingham, Ala.-based Infinity Property and Casualty Corp. says the company began to implement a predictive analytics solution from SPSS in October of last year.
Bill Dibble
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