I spend a fair amount of time on LinkedIn posting and reading about insurance. Not long
ago, there was a discussion about Instacart’s announcement that it would discontinue the use of an AI-powered tool that enabled retailers to charge customers different prices for the same products, the apparent goal being to charge as much as possible to those willing to pay for it. In other words, maximize profits.
This was allegedly in response to investigations by at least two consumer organizations that claimed to have evidence that a number of well-known retailers were using, or at least testing, AI pricing systems. According to a CBS News report, one of the investigations found that prices varied by as much as 23%–identical product, different customers.
The issue in this LinkedIn discussion revolved around the question of whether this practice is, or should or shouldn’t be, legal in the property/casualty insurance industry. Insurance pricing, beyond general anti-discriminatory practices that apply to virtually all industries (e.g., race, color, creed, national origin, religion, etc.), is more highly regulated than most other industries.
“Price optimization” is the term most often used to describe pricing variations of identical products among different individual customers. In a general sense, the term can be applied to pricing variations based on individual customer demand, competitive reasons, and varying or fluctuating costs with the goal being to maximize revenue and/or profits.
Most likely, everyone reading this article has benefited or been a “victim” of price optimization. No one is happy if they believe the latter has occurred, but everyone loves a bargain if the former happens. Price optimization in one form or another has existed for decades in the travel industry by airlines, hotels, cruise ships, etc.
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More recently it has become increasingly common in industries that provide cable TV, internet, and cell services. For example, every year without fail, our cable TV service increases our monthly fee. My wife then calls, complains, and the provider backs off the increase to prevent us from cancelling service, sometimes offering a “new customer” program with broader channels or even a reduced price. Many people probably never call and just accept the higher price. That’s price optimization.
Given the rapid development of data and prescriptive analytics and artificial intelligence, absent any legislative or regulatory restrictions, we can likely expect the use of price optimization algorithms to increase in most industries.
This brings us specifically to the property/casualty insurance industry.