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AI Insurance: Who Is Insuring the Algorithms?

September 1, 2020 by Matthew Jones

There are some algorithms in life that, even with the very best marketing, don’t really matter too much.

Executive Summary

Matthew Jones, a principal of fintech venture firm Anthemis, proposes the development of a new algorithmic insurance line of business—a modern-day hybrid of cyber, product liability, and errors and omissions insurance. After outlining what it would cover, he proposes a framework for assessing AI risk to bring the concept to life and suggests the possibility of a rating agency that also might supply algorithm ratings as an enabler for the insurance industry. In his view, a good starting point could be an underwriting model that considers People, Process, Technology and Data. For each component, he offers relevant questions, such as "Is a Ph.D better than a master of Science degree" when evaluating the quality of people building AI models. It's time for insurers to figure out if they want to cover these risks before they find out that they were covering them all along, he concludes.

For example, if Netflix’s recommendation algorithm points me toward the first episode of a terrible new show when all I needed was a “Frasier” re-run, I’ll be fine. I might have wasted 20 minutes trying out the new show, but I can be back in Seattle without leaving my couch. Annoyed and inconvenienced, sure. But life goes on.

Executive SummaryMatthew Jones, a principal of fintech venture firm Anthemis, proposes the development of a new algorithmic insurance line of business—a modern-day hybrid of cyber, product liability, and errors and omissions insurance. After outlining what it would cover, he proposes a framework for assessing AI risk to bring the concept to life and suggests the possibility of a rating agency that also might supply algorithm ratings as an enabler for the insurance industry.

In his view, a good starting point could be an underwriting model that considers People, Process, Technology and Data. For each component, he offers relevant questions, such as “Is a Ph.D better than a master of Science degree” when evaluating the quality of people building AI models.

It’s time for insurers to figure out if they want to cover these risks before they find out that they were covering them all along, he concludes.

Another inhabitant of Seattle, e-commerce giant Amazon, launched its Amazon Web Services (AWS) platform back in 2006. Amazon certainly didn’t invent cloud computing, but without question the company played a key role in propelling it forward and making cloud-based IT infrastructure far more accessible from both ease-of-access and cost perspectives. No longer needing to invest thousands of dollars on servers prior to a company’s launch, cloud computing has led to an explosion of startups able to serve customers from anywhere. More importantly, however, these companies, many of which have grown well beyond the startup stage, are now able to deploy sophisticated applications that use artificial intelligence (AI)—classifying, deciding, suggesting—just like Netflix’s recommendation algorithm.