Mining Your Data From the Outside In

Increasingly, when it comes to the world of data, what lies outside of the traditional core insurance system landscape is fast becoming more interesting than what lies within it. For years, insurers have relied on their own data capture mechanisms to create unique insight enabling them to outperform the market when understanding the characteristics that make up a good risk versus a bad risk, and the end customer’s propensity to buy. Size was important—the more data an insurer had access to, the greater its chance of developing unique insight.

Now, I am not going to argue that insurer size is no longer important when talking about data, when simply, it still is. However, there are a growing number of external data sources fueled by the connected social generation, geospatial data and initiatives targeted at making public data more accessible, which may benefit insurers when combined with existing internal sources for use in underwriting risk selection, pricing and claims validation. Some insurers, both large and small, are starting to look seriously into how this data can be used to drive growth and profitability.

Typically, these external data sources are supplied through local government, industry sponsored initiatives, commercial organizations specializing in the aggregation and analysis of data as a service, and now also through open data markets, such as InfoChimps and Windows Azure Marketplace. Knowing how to navigate this market, and its associated legal aspects, is a major challenge for many insurers.

Potential considerations:

* Build internal capabilities, or partner, to specialize in the search, acquisition and modelling of new data sources;

* Undertake effective due diligence to validate the authenticity of external data sources, permissions of use and jurisdiction;

* Combine data from a variety of sources, both internal and external, to test validity, build new models and discover new insight;

* Use data not only for risk selection and pricing, but also for incentivising good risk behaviour and practices; and

* Agree internally the ethics around using some of the data in risk selection and pricing - especially in relation to the use of social network data.

For more discussion around this topic, check out the Post Magazine’s Webinar on ‘Optimising Pricing and Underwriting Data’ from last Friday. The debate was focused on the U.K. P&C market. However, many of the themes and lessons learned are transferrable between insurance markets across the world.

This blog has been reprinted with permission from Celent.

Jamie Macgregor is a senior analyst in Celent's insurance practice, and can be reached at jmacgregor@celent.com.

The opinions posted in this blog do not necessarily reflect those of Insurance Networking News or SourceMedia.

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Analytics Policy adminstration Data and information management
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