Underwriting

AI lets insurers make connections and draw insights from data that otherwise may not have been available, at least not at speed or scale.

A look at the life cycle for small commercial insurance policies, then vs. now.

Here is a sort of use-case wish list for AI in insurance, focused on the most repetitive and demanding claim functions.

The answer is a strategy that blends technology, talent development and alignment with the values of the younger generation.

Combining external data streams with internal analytics creates a comprehensive view of properties that legacy methods can't match.

Understanding the complex landscape requires both foresight into identifying the right risk variables and a modern technology stack.

insurers will provide more accurate underwriting, efficient claims processing and a personalized customer experience.

Typically, a risk is underwritten, bound... and forgotten. But new streams of data and automation allow for continuous underwriting.