If one were to make a movie about price fixing, it would likely feature competitors discussing pricing in a smoke-filled room. But in today’s virtual age, antitrust enforcers are increasingly worried about a very different type of (smoke-free) scene: competitors’ use of technological tools to limit supply and fix prices. In particular, the Department of Justice and Federal Trade Commission continue to scrutinize algorithmic pricing by competitive firms.
Pricing algorithms come in many forms but largely operate by automatically setting prices that maximize a firm’s profits. A single firm using an algorithm to set prices and improve efficiency is unlikely to raise antitrust concerns. Antitrust issues may arise, however, when multiple competitors provide pricing or supply data to an algorithm to maximize profits across all firms. To date, private cases alleging price fixing via algorithms have had mixed success. For example, a putative class action was recently dismissed alleging that Las Vegas hotels conspired to fix prices by using an algorithm to set room prices. In that case, the district court held, in part, that the allegations could not support a conspiracy because the hotels signed up for the algorithmic product at different times and there were no allegations that the hotels “agreed to be bound” by its pricing recommendations. Gibson v. Cendyn Group LLC, No. 2:23-cv-00140-MMD-DJA (D. Nev. May 8, 2024). The Gibson case is currently on appeal to the Ninth Circuit.
Such results have not deterred the government’s interest in halting the usage of algorithms to set prices among competitors. In March 2024, the DOJ and FTC took the unusual step of filing a joint statement of interest in a class action alleging that Atlantic City casino-hotels had price fixed their hotel rooms (the DOJ had previously filed two other statements of interest in other cases alleging anticompetitive algorithmic pricing). In the filing, the agencies stated that: (1) it is “not necessary for conspirators always to adhere to pricing recommendations for a challenged price-fixing scheme to be per se unlawful,” and (2) a pricing algorithm that utilizes pricing data across competitors can be anticompetitive, even if the recommendations from the algorithm are “non-binding” on those companies. This statement is important because, as Gibson indicates, courts might prove too willing to permit agreements to fix prices simply because the algorithm’s results were non-binding on participants. If they routinely follow them, and their rivals know that, that should be sufficient to set forth a price-fixing conspiracy.
On the heels of this joint statement, and following existing multidistrict litigation, DOJ and several states filed an antitrust lawsuit against RealPage, a company that provides property management software to landlords. The complaint alleges that RealPage’s software utilizes the landlord’s pricing data (in part) to provide them with real time, algorithmic pricing recommendations for multifamily rentals. RealPage’s software allegedly “monitors compliance” by the landlords and allow landlords to “outsource their pricing function” directly to RealPage. Among other counts, DOJ alleges that RealPage violated Section 1 of the Sherman Act by engaging in the unlawful sharing of competitor pricing and illegal alignment of pricing. The RealPage case could become one of the landmark cases regarding algorithmic pricing and warrants close scrutiny.
The DOJ’s and FTC’s position on competitors’ usage of algorithmic pricing is clear: if competitors use an algorithm to share pricing data for the purpose of setting prices in a particular industry, that conduct will likely be condemned as a violation of Section 1 of the Sherman Act. Whether the courts ultimately agree with the agencies (and private plaintiffs) will play out over the coming years.
