In the midst of increased focus of federal enforcers and courts on application of antitrust laws to developing technology, the U.S. Department of Justice (DOJ) filed an antitrust lawsuit on Friday accusing RealPage Inc., a property management software company, of helping residential landlords collude when setting rental rates through RealPage's software. This suit is the first time the government has sued a company for systematically subverting free-market competition by using mathematical algorithms, though the proposed Preventing Algorithmic Collusion Act summarized here would specifically address application of competition law to such conduct.
Joined by eight states, DOJ's present suit filed in the U.S. District Court for the Middle District of North Carolina asserts claims under Sections 1 and 2 of the Sherman Act. Specifically, DOJ's Complaint alleges competing landlords share competitively sensitive information about their apartment rental rates and other lease terms to train and run RealPage's pricing software. The software then generates recommendations on apartment rental pricing and other terms. In this way, DOJ alleges the building owners can collaborate on their pricing decisions. Consumers are resultingly harmed by higher rental prices, inferior leasing terms, and less concessions, according to DOJ. Meanwhile, the landlords enjoy the benefits of coordinated pricing among competitors. DOJ also alleges RealPage uses this scheme to maintain a monopoly in the market for commercial revenue management software that landlords use to price apartments.
This is not a first challenge to RealPage's activities, as it already faces private litigation and actions from local enforcers in D.C. and Arizona.1 In fact, DOJ filed a Statement of Interest in a consolidated class action suit in Tennessee federal court last year, explaining that Section 1 of the Sherman Act, which bars competitors from fixing prices, applies with "full force" to schemes involving pricing algorithms. Likewise, as summarized in our earlier insight article, DOJ and the Federal Trade Commission submitted a Statement of Interest in March 2024 in Duffy v. Yardi Systems Inc., et al.2 arguing that landlords' joint use of Yardi's pricing algorithm could constitute price fixing. According to DOJ, whether firms effectuate price-fixing through a software algorithm or through human-to-human interaction should be of no legal significance.3
Similar claims of algorithmic price fixing are arising in federal courts across the country concerning a variety of industries, such as, hospitality, health insurance, and real estate. The need for judicial decisions in this area is paramount.
Can you infer an agreement when customers know that competitors are using the same software? Will it become outcome determinative whether the customers' data are being used to train and develop the algorithmic tool? At what point, if any, will liability attach if the customer exercises some decision making beyond the output of the algorithmic tool? How can any rule developed here be harmonized with existing conspiracy jurisprudence involving conspiracy agreement, both in and outside the antitrust context?
These cases, particularly this latest case, should be closely watched by companies making or considering use of algorithmic tools.
We will continue to monitor, analyze, and issue reports on these developments. If you have any questions about potential antitrust risk arising from use of algorithmic tools, please contact one of the Mintz attorneys listed above or your regular Mintz attorney.
Footnotes
1 See Arizona Attorney General Press Release and Complaint (Feb. 2024) at https://www.azag.gov/press-release/attorney-general-mayes-sues-realpage-and-residential-landlords-illegal-price-fixing; DC Attorney General Complaint (Nov. 2023) at https://oag.dc.gov/sites/default/files/2023-11/DC%20OAG%20RealPage%20Complaint%20-%20Filed.pdf
2 Case No. 2:23-cv-01391-RSL.
3 Department of Justice, Statement of Interest of the United States, In re: RealPage, Rental Software Antitrust Litigation, Case No. 3:23-MD-3071 (Nov. 2023), available at https://www.justice.gov/d9/2023-11/418053.pdf
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