When the almost Perfect Storm that was Super Storm Sandy took a sharp left onto the Jersey shore and into New York Harbor, no one was really surprised.
Thanks to waves of weather tracking data and the tools to analyze it, meteorologists had given everybody in the storm’s path a pretty good idea of what was coming.
It will be months before the full financial impact of this devastating storm is understood. But you can bet that insurance companies whose bottoms lines will take a related hit will be looking more closely at the data, too, to determine their own next steps.
In his 2011 white paper on insurance issues and insights, “Analytics: Turning Data into Dollars,” Deloitte’s Howard Mills contends that advanced analytics is particularly powerful for the insurance industry.
Analytics could improve any business that expects its people to repeatedly weigh multiple factors when making decisions. When the decisions are central to a company’s core processes (read “underwriting” or “claims management”), the company can use predictive models to exploit market inefficiencies.
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With analytics, finding small changes can make a big difference. In a business where 80% of each earned premium dollar is “claimed by the claims,” he who can equitably settle claims while reducing claims costs by just 1% stands to realize a huge benefit. Imagine taking a combined ratio from 105 to 95.
Having sold us on the opportunity, Mills then presents the implementation as manageable. To quote, “The good news is that, in some ways, introducing analytics can be easier than many executives may think.” To the good news he adds these simple operating principles:
- Starting where you are: Assess your current capabilities and identify gaps. Focus improvements on low-hanging fruit first.
- “Crunchy questions”: Focus on solving specific problems with very specific questions before exploratory work.
- Signal strength: Detect and respond to the signals that are presented – especially weak signals – faster and better than your competitors.
- Accelerated insights: Automate the delivery of the information people need to do their work – and automate responses wherever possible.
- User engagement and visualization: Deliver insights that people need – in whatever forms they need – to make better decisions.
- Fact-driven culture: Embed analytic capabilities and outputs into business process; make your culture one of discipline and accountability.
- Right-fit analytics: Match statistical and analytic techniques to the job at hand. Buy what you need and need what you buy.
Mills also includes some Deloitte case studies and summarizes the results of its analytics services as applied to talent management, and medical malpractice prediction as well as insurance underwriting / pricing and claims management.
Download the white paper for the details.