Most insurance companies can see a change coming. To meet the requirements of Solvency II (SII) or the Solvency Modernization Initiative (SMI), all but the smallest insurers will most likely be looking at creating and managing a much greater data flow than they might have dreamed about just a year or two ago.
But how best to translate data into meaningful insights is still subject to some debate. One likely answer may be through visualization.
We can take a look at the incredibly complex patterns of rush hour traffic and almost instantly decide if it’s safe to cross the street. Creating the fractals required to describe the geography of George Clooney’s face would take so much longer than the millisecond it takes for him to receive an adoring smile as he walks down Fifth Avenue. When it comes to pattern recognition, the eyes do have it.
Unfortunately, save for a few geniuses, most of us cannot look at numbers on a huge spreadsheet and rapidly determine where our most pressing risks lie. For insurers though, there is a real near-term need to find a way to both determine those risks and bring them to the attention of the relevant parties.
The formal adoption of the Own Risk and Solvency Assessment (ORSA) manual at the recent national meeting of the National Association of Insurance Commissioners (NAIC) is just the latest reminder that with SMI and SII, risk management is now a new and more complex ballgame.
The governance emphasis included in both SII and SMI means more information will be needed to reach the highest levels of an insurer faster than ever before.
As my colleagues in Deloitte’s Insurance Practice Technology Leadership noted in their report, "Tech Trends 2011: Insights for Insurers on the Natural Convergence of Business and IT," while insurers are progressing with the use of analytics, “much potential insight is buried within static reports that are accessible only by a small fraction of the organization.” To find that information, the use of advanced analytics may well become the de facto standard for insurers under the upcoming solvency regimes. But analytics alone may not be enough.
This is not how our brains work. We’re used to finding patterns in shapes and movements. Tables don’t provide this, and valuable information may be lost if its value is not properly communicated to the general user.
New visualization tools allow for more intuitive understanding, based on techniques including graphic presentation, touch- or gesture-based drill downs and on-the-fly relationship mapping with real-time updates.
The idea is to present the information in a way that is intuitively understood, with the relationships and the effect of relationship changes much easier to grasp than from a static table or spreadsheet. New and improved visualization tools include both open source and others from dedicated players and general technology companies, allowing for various entry or exploration costs.
For insurers already wondering how to find resources to meet the data demands of the new solvency regimes, visualization may seem an unnecessary next step. But if this is the time when so many are moving to improve their information technology abilities, what better time than now to use a tool that is finally coming of age.
This column originally appeared at Insurance Networking News.
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