When thinking about advancements in technology and data-driven insights, insurers are often confused about AI and BI—what they are, and how to even know if they are valuable to their business.

Executive Summary

As Cloverleaf Analytics collaborates with insurers of all sizes to derive value from their insurance data in an unpredictable economic environment, company representatives often speak with carriers about the differences between AI and BI—what are they, when do you use which one? According to CEO Robert Clark, these discussions regularly evolve into discussions about what Cloverleaf is terming "insurance intelligence," which doesn't focus on a specific technology. Instead, the idea is to focus on the problems insurers need to solve and the insights needed to solve them, and then to find the right customized combination of traditional and emerging technology approaches to do it.

We have found that to be true in our interactions with carriers across the country, no matter what their size. When we are faced with questions about “intelligence,” we end up first defining these two categories and then introducing a third term: “insurance intelligence.” This new term opens the door for insurers to begin moving toward the next evolution of their business.

Having seen the interest and attention during customer discussions, this article will walk through these stages while also getting into why “insurance intelligence” is the best way forward for the industry.

How Is Business Intelligence Viewed in the Insurance Industry?

From a general standpoint, BI has taught businesses how to make better decisions by more effectively analyzing and interpreting data. The insurers that have implemented BI have typically worked with horizontal players that initially impressed by delivering new insights that made incremental improvements to understanding business operations and predicting future business outcomes.

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