Insurers have long wrestled with the question of whether it is better for them to buy or build their information technology; that is, whether it is better for them to develop their own proprietary in-house automation or utilize systems developed by outside vendors, with modifications.

Executive Summary

With the abundance of data and analytical resources, how important is it for insurance carriers to develop and maintain those resources in-house? To what extent can carriers effectively rely on third-party providers? To explore this topic of buy vs. build in carrier data analytics, Carrier Management submitted a series of questions to three individuals—one with a major insurance carrier, another with a major reinsurer and the third with a leading actuarial firm—each a key player in helping carriers make strategic decisions about the selection and utilization of data analytics.

In the age of big data, the question of “buy vs. build” has moved into the realm of data analytics. Where data was once relatively scarce and difficult to gather, the world is now flooded with private and public data, along with previously unimaginable power to organize and analyze that data.

In light of the abundance of data and analytical resources, how important is it for insurance carriers to develop and maintain those resources in-house? To what extent can carriers effectively rely on third-party providers?

The answer will differ from carrier to carrier, of course, and probably among product lines within a carrier. But the question is central at a time when competition is intense for even marginal advantages in pricing. A slight overinvestment here, or an underpriced exposure there, can mean the difference between success and failure.

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