Harnessing data effectively is the specialty insurance sector’s next great evolutionary step. Success in underwriting will soon demand that carriers strategically tap into the enormous pools of data that grow by the second.

Executive Summary

Specialty insurers lured by huge pools of external data may simply find themselves drowning in numbers if they don't first focus on the business case for using it, writes AXIS Capital's chief analytics officer. Here she provides a step-by-step guide that starts with structuring internal data and considering internal knowledge and commercial customer relationships. Explaining how to prioritize data analytics projects, she provides specific examples of underwriting activities made more efficient by first asking end users what they need. Among them is a system to prioritize submissions.

Failure to adopt an efficient data analytics approach is likely to reduce any carrier’s ability to remain profitably competitive. Everyone knows that, of course, but actually doing it is much more difficult.

Combining data-driven analytics, commercial relationships and the essential human talents of underwriting complex risks is as much an art as it is a science. Carriers must adopt a comprehensive, strategic and inclusive approach that puts the benefits to both their internal end users and customers first.

It is easy to drown in numbers and achieve little. This is especially true of external data, whether sourced from public repositories, commercial suppliers or new data generators, such as the Internet of Things and social media. Jumping in and starting to analyze data without a specific and considered end result in mind will result in lots of wasted effort with little payoff. Further, it is critical to have internal data well understood before pulling in any of the rest. Otherwise, the result will be costly and chaotic, an environment where any business benefits are unlikely to materialize.

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