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Document Type

Article

Abstract

This Article addresses emerging gaps in consumer protection. Insurers, like companies in other industries, are revolutionizing their practices with artificial intelligence and big data. Insurers are finding new ways to price risks and policies, tailor coverage, offer advice to purchasers, identify fraud, and sequence the payment of claims. These changes have subverted consumer protections built into current regulatory regimes, and regulators are struggling to adapt. This is not a niche problem. Insurance is a vital part of the U.S. economy: it rakes in over 1.2 trillion dollars in premiums a year; employs more than 2.7 million people; and undergirds transactions as simple as home purchases and as complex as corporate mergers and acquisitions, the multi-trillion-dollar tort system, and a vast system of private risk management and loss avoidance advice. Despite playing these critical roles, the insurance market is surprisingly inefficient. Deep information asymmetries make it difficult for consumers to evaluate the quality of policies and carriers, for insurers to price risks properly, and make it possible for both sides to act opportunistically. Further, behavioral barriers hamper purchasers, who often buy too little or the wrong insurance. And, in some markets, private insurers might not be willing to supply enough insurance because the underlying risks cannot be adequately spread. Insurance regulation is a necessary part of solving these complex market failures. Most of the previous legal scholarship about algorithmic justice has been in the context of information platforms, criminal justice, and employment discrimination. This Article connects to those discussions and expands them in the specific context of insurance. It does so by providing a taxonomy of the changes in the insurance industry, the potential danger to consumers as a result of those changes, the reasons for regulation, and the ways that regulators must adapt to protect individual consumers and the insurance market.

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