While the Blue Angels flight exhibition that I wrote about earlier certainly impressed me with its precision, transparency, and speed, it also got me thinking about insurance. What would the cost range be if an accident occurred, and how would an insurance company model that possible cost and calculate a rate? What about insurance for athletes who continually expose themselves to injury in pursuit of excellence? Then, there are the various types of common insurance for the rest of us, such as automotive, life, and health insurance, and we who have those products know what they cost!
The insurance industry is based on statistics, historical data, and predictions used to determine pricing. It is a natural fit for business intelligence (BI), including analytics and reporting applications such as Birst, predictive analytics solutions such as eiVia, price optimization products such as Mimiran, and enterprise mashup dashboards such as mashmatrix Dashboard.
Scott Kemmerer outlines the various applications of business intelligence for insurance in his article in Information Management, “Business Intelligence: A Blueprint for Success.” According to Kemmerer, insurance companies can use analytics to model financial risk; dashboards to monitor operational costs and productivity; price optimization for more focused and accurate pricing; predictive analytics for fraud detection; analytics and reporting to evaluate agent and broker performance; and analytics for improved contract negotiation with outside vendors.
Kemmerer stresses the importance of predictive analytics to help predict outcomes. According to a cover story article in InformationWeek, predictive analytics is one of the four technologies that are re-shaping business intelligence; and research firm Gartner lists predictive analytics second after cloud computing in its top 10 strategic technologies for 2010.
Software-as-a-service (SaaS) BI enables insurance companies to quickly implement BI solutions to a greater number of decision-makers than was ever possible, because SaaS BI requires no software installation, maintenance and expensive equipment to run. Let us hope that the insurance industry increasingly implements and frequently employs SaaS BI to optimize its business and pass the cost savings to all of us who rely on its products.
What types of business intelligence solutions have you seen or plan to implement in the insurance industry?
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