Insurance market works like a cat and mouse game, says book – 03/24/2023 – Market

Messy, opaque and expensive. Buying and collecting insurance policies can be frustrating. It turns out, however, that insurers often feel the same way about their customers — a group of people whose inner secrets are the key to their success or failure.

The reasons behind mutual misunderstanding are at the heart of why many insurance markets function poorly or not at all.

As the authors of “Risky Business” explain [Negócio arriscado], insurance is what economists call a market of selection – one in which the identity of customers is as important as the price they are willing to pay. Some customers will be cheaper for the insurer to serve because they make fewer claims; others, more expensive. The market only works if there is a combination of the two.

“The selection problem introduces a two-way game of cat and mouse, in which insurers try to pick the right customers (and avoid the wrong ones), while the ‘wrong’ types of customers do their best to make insurers believe they are really the ‘right ones'”, argue the authors. The main problem, say Liran Einav, Amy Finkelstein and Ray Fisman, is that customers know far more about their risk than insurers do.

At worst, selection can bankrupt some companies or entire segments of the industry. If an insurance company discovers that customers are more expensive to service than expected, it may raise prices. This could deter lower risk customers from purchasing coverage, leaving the insurer with only the riskiest ones. And so insurance costs rise again and prices rise again, pushing even more people out. Eventually, insurance becomes too expensive for most people or the insurance company goes out of business. The authors give several examples, from divorce insurance to unemployment coverage.

The game of cat and mouse transforms the insurance world in a thousand different ways as companies try to keep the market running smoothly. For example, anyone with a business health insurance policy is familiar with, and perhaps frustrated with, rules that only allow changes once a year. The authors point out that this is to prevent people from buying coverage as soon as they find out they are sick. Likewise, offering free gym memberships is an attempt to weed out people who don’t like gym memberships – and therefore may be less healthy and more expensive for the insurer.

The authors, three academics residing in the United States, keep the debate going in a light-hearted, talkative style familiar to readers of the “Freakonomics” books by Stephen Dubner and Steven Levitt. It’s a book about insurance that doesn’t feel like a book about insurance. However, it is a book about insurance in the United States. Examples from other parts of the world are lacking.

Where the book picks up the pace is with some of the thornier issues that insurers and their customers are beginning to grapple with. Returning to health insurance, for example, the increasing availability of genetic data leads to a new set of challenges, as this information can be used to identify who is most at risk for certain diseases. Should governments allow insurers to use this information to price policies? If so, some people are at risk of being shut out of the market because they lost the genetic lottery. But if insurers can’t use this information and their customers can, the market will be skewed in the other direction.

There are no easy answers here, and the authors don’t attempt to offer any. There are, they say, only compensations. “Whatever balance between efficiency and fairness the government chooses, there will be winners and losers,” they argue. “Losers often have genuinely tragic stories to tell.”

These types of questions will become more common as insurers collect an ever-increasing range of data about their customers. The data might tell them, for example, that people with light hair are more likely to drive at speed. Or that journalists who write book reviews are statistically more likely to have their homes flooded. The information advantage can shift from customer to insurer, and the authors are somewhat dismissive of the potential for big data to disrupt the market. But that potential exists. And it doesn’t necessarily make insurance a less confusing, opaque, or expensive place.