Many people have vivid memories of where they were when COVID-19 became “real” for them. It was the moment that the pandemic evolved from an intangible topic on the news impacting people somewhere far away to something that directly affected daily life in their own communities—and for an a seemingly indefinite period of time. Much in the world has changed as a result of the pandemic, some of it perhaps permanently. In the captive insurance world, coverage for business interruption (BI) may be one of those changes. 

What makes data “bad” or difficult to work with? For actuarial consultants, data from clients is crucial to a comprehensive analysis. Although that data may arrive with any number of issues and challenges, solving those puzzles gives actuaries the opportunity to demonstrate our ability to adapt, innovate and communicate.

As far as I can remember, I have always been drawn to numbers. Throughout my early education, I gravitated to all the various “toys” designed to instill a tactile knowledge of mathematical tenets; there were number chains, peg boards, puzzles (some were even three-dimensional!), to name a few. This attraction has always been founded on one notion, or cliché: “numbers don’t lie.”

Machine learning is a branch of artificial intelligence (AI) that teaches a computer how to analyze and find hidden patterns in data through the use of algorithms. It’s been called a “revolution,” and from self-driving cars to health care, it has begun to change the way we live our lives. Our Pinnacle University group explored the emerging world of machine learning and how it fits into the insurance industry.

Nuclear verdicts (verdicts over $10 million) are becoming more common and contribute to significant angst experienced by commercial auto executives, underwriters and claims handlers across the country. A common theme in these matters is how plaintiff attorneys have been successfully employing reptile theory.