On March 28, 2024, the U.S. Department of Justice Antitrust Division and the Federal Trade Commission (“the agencies”) jointly submitted a Statement of Interest on behalf of the United States in Cornish-Adebiyi v. Caesars Entertainment, 1:23-CV-02536 (D.N.J. Mar. 28, 2024). This is the third time recently that the agencies have weighed in to support plaintiffs in an algorithmic pricing case, which the agencies sometimes refer to as “algorithmic collusion.” The others, In re RealPage, Inc., Rental Software Antitrust Litig., No. 3:23-MD3071 (M.D. Tenn. Nov. 15, 2023), and Duffy v. Yardi, No. 2:23-cv-01391 (W.D. Wa. March 1, 2024) concern algorithmic price-fixing allegations involving the use of property management software to artificially inflate lease prices. A subset of plaintiffs survived a motion to dismiss in In re RealPage, Inc. and the parties have fully briefed the motion to dismiss in Duffy.
In Cornish, plaintiffs allege that competing casino hotels violated Section 1 of the Sherman Act by, among other things, unlawfully agreeing to use a pricing algorithm platform to set prices for Atlantic City casino hotels which would result in the algorithm helping to set the prices the defendants ultimately charged. Defendants have moved to dismiss the complaint, arguing that plaintiffs’ claims are legally insufficient because plaintiffs do not allege that defendants discussed their choice of pricing software with competitors or agreed to adopt a common pricing platform.
The statement of interest summarizes the views of the Department of Justice and the Federal Trade Commission on the legal principles in play in the case, and addresses two claimed “legal errors” defendants make in their motion to dismiss: “(1) defendants’ suggestion that plaintiffs must identify direct communications between Casino-Hotel Defendants” to plausibly allege a violative agreement under Section 1, and (2) “defendants’ argument that plaintiffs’ price-fixing claim must be dismissed because the recommendations generated by [the pricing algorithm] are not binding.”
According to the agencies, direct communications are not required to show proof of an agreement among competitors, as Section 1 covers tacit as well as express agreements. Further, the agencies argue that Section 1 prohibits competitors from “delegating key aspects of pricing decisionmaking to a common entity, even if the competitors never communicate with each other directly.” Regarding defendants’ argument that there can be no actionable claim of price fixing because the algorithm’s recommendations are not binding, the agencies maintain that “an agreement among competitors to fix the starting point of pricing is per se unlawful, no matter what prices the competitors ultimately charge.”
Along with the agencies’ filings in these cases, regulators have questioned the use of price setting algorithms in public statements. Cecilia Cheng, Counsel to Antitrust Division’s Assistant Attorney General, recently addressed this issue at the American Antitrust Institute’s annual policy conference. Ms. Cheng contended that a price setting tool did not need to rely on confidential pricing information to trigger antitrust liability. It may be sufficient for competitors to recognize that a commonly used algorithm can result in raising prices charged by competitors.
With the agencies’ interest in the potential anticompetitive effects from the growing use of software to assist in pricing decisions, this will likely be an area of ongoing focus for regulators. Companies that are using or contemplating the use of algorithmic pricing tools should continue to monitor the ongoing litigations and the agencies’ views on algorithmic-pricing tools.
