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Analytics Provides Carriers Food for Thought

There’s an all-you-can-eat buffet of information available to insurers, but is it too much data to digest?

By Michael P. Voelker | Updated on March 07, 2011

It’s generally accepted that the first written insurance agreement was established with the Hammurabi code. It took quite a while—over 3,000 years—before humankind could establish enough understanding of risk transfer and mathematics and analyze enough data to develop the first actuary tables in the late 1600s. Since then, the sophistication within every part of the risk-sharing process—from rate-making to underwriting to claims—has increased at a quickening pace, driven by greater precision and predictability and built on an ever-expanding amount of data.

Despite the industry’s developments associated with cross-company information sharing—bureau rates, claims databases, etc.—there has long been competitive advantages to be gained by the amount of data an insurer could collect in order to fine-tune rates and underwriting, support new products, and carve out new market niches. It was a model that favored companies with larger books of business generating more data and with more staff resources available for information collection to establish greater certainty around predictability.

However, an explosion of new data sources is turning that model on its head. “There is more data, and more access to data, than there ever has been—and it’s growing,” says Matt Josefowicz, director of insurance at Novarica. “Geocoding, geographic information sources, aggregated consumer information, commercial databases, credit scoring, property peril scoring detailed dossiers on individuals and businesses—there’s a massive amount of information that can be obtained simply by searching the Web.”

In this new environment, there are fewer competitive advantages to be gained from the amount of unique information an insurer can compile itself. “We’re evolving from a time when insurers needed to be fantastic hunters with a simple digestive system to one where they’re almost being force-fed data,” says Josefowicz. “The challenge is: How can we evolve our organization to spend fewer of our resources on duplicating the effort of data entry, and instead handle that data more effectively?”

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