September 15–29, 2025

Guidelines for Assessing and Mitigating Antitrust Risk

Following are some of the key issues we have seen emerge as we monitor these areas of the law and some questions you might consider asking about the software provided or used by your business.

 

ISSUE

Inputs: Tools that rely on public, lagged, and/or anonymized data tend to be less risky than tools that rely on confidential, current data from competitors. If a tool uses nonpublic information, companies should be attentive to whether there is a risk that they can access competitors’ confidential data (and vice-versa).

 QUESTIONS

  • What data is used?
  • Is the data public or nonpublic? Is the company providing or receiving nonpublic commercially sensitive information?
  • How current is the data?
  • What data is available to participants?
  • Is data from competitors segregated? Are competitors’ data pooled—either for training an algorithm, to generate recommendations, or for some other reason?

 
Independence: Ensuring that pricing recommendations are nonbinding reduces antitrust risk.
  • What are the terms of use?
  • Are settings customizable? Are competitors’ settings shared (directly or indirectly)?
  • What is the output?
  • Are there recommendations?  If so, what are they—prices, commercial terms, or benchmarks?
  • Are recommendations binding, or can individuals deviate from them?
  • How often do deviations occur in practice?

 
Marketing: Public statements touting a tool’s ability to discipline, optimize, or otherwise increase prices or revenues across an industry can be problematic.
  • How it the tool marketed and distributed? As means to increase profitability? For disciplining sales and pricing?
  • How widely is the tool used in the industry?
  • Does the company know if its competitors are using it? Would the company use it regardless?
Business Rationale: Ideally, there are documented procompetitive bases for using the tool, such as increasing efficiency or lowering prices for customers.
  • What are the company’s expectations or reason for using the tool?
  • What benefits has the tool led to in practice?

 

Recent Developments

Appeals

Third Circuit Reviews Information Sharing Allegations Against Defendants in the Hotel Industry – Cornish-Adebiyi v. Caesars Entm’t, No. 24-03006 (3d Cir.)

  • In May 2023, hotel guests brought a putative class action against Cendyn, the provider of an algorithmic pricing and revenue management software used to manage hotel pricing, and nine Atlantic City hotels that use the technology. Plaintiffs claim that the hotel defendants have used Cendyn’s technology to coordinate pricing in violation of Section 1.
  • The district court twice dismissed complaints, finding insufficient allegations of confidential information sharing. The court refused to “infer a plausible price-fixing agreement” from the allegation that the hotel defendants used the same pricing software. Plaintiffs appealed to the Third Circuit.
  • On September 17, 2025, the Third Circuit heard oral argument, which focused primarily on the allegations of sharing of confidential information. Defendants argued that plaintiffs failed to allege that Cendyn “pools” competitors’ nonpublic competitively sensitive data to make pricing recommendations. The panel noted that the complaint did allege that the hotel defendants shared their confidential information with Cendyn to coordinate pricing.
  • The argument was held one month after the Ninth Circuit affirmed dismissal of claims in a similar case brought against Cendyn and a group of Las Vegas hotels. In Gibson v. Cendyn, LLC, 148 F.4th 1069 (9th Cir. 2025), the Ninth Circuit noted in its opinion that Plaintiffs did not allege that Cendyn pooled, shared, or used competitors’ confidential information to generate price recommendations.

 

Settlements

Nevada Concludes Its Investigation into RealPage – Nevada v. RealPage, Inc., No. A25-928577-B (Dist. Ct. Clark Cnty.)

  • On September 19, 2025, RealPage announced that it reached a settlement with the state of Nevada regarding use of RealPage’s revenue management software in the state.
  • Nevada had not joined the Department of Justice (“DOJ”) and nine other State AGs in filing a lawsuit against RealPage in August 2024. Nevada’s complaint, filed simultaneously with its consent decree, mirrored allegations in the DOJ’s complaint.
  • The consent decree establishes limits on RealPage’s use of non-public data, including that: (1) data used in its software to generate rent recommendations must be more than three months old, aggregated, and anonymized; (2) rent, occupancy or availability data published to Nevada customers must be aggregated and anonymized; and (3) data used by RealPage to train its models must be more than three months old. RealPage also will make a charitable contribution of $200,000 to the State of Nevada for distribution to Nevada-based nonprofit or governmental organizations that provide down payment assistance or rent reduction to Nevada residents. Finally, RealPage will provide annual certifications to Nevada for the five-year term and maintain an antitrust compliance program with training for revenue management personnel.

Settlement Reached with User of Revenue Management Software in Rent Price-Fixing Case – In re Yardi Revenue Mgmt. Antitrust Litig., No 23-cv-1391 (W.D. Wash.)

  • In September 2023, residential real estate renters brought Section 1 price-fixing claims against Yardi Systems, the provider of an algorithmic pricing and revenue management software, and nine real estate owners and management companies that used the software. Additional similar lawsuits followed against approximately forty additional defendants.
  • On September 26, 2025, plaintiffs moved for preliminary approval of a class action settlement reached with one real estate defendant, FPI Management, Inc.
  • The settlement provides for multiple forms of relief. Notably, FPI will not license or use revenue management software without assurances from the software vendor that (1) non-public, confidential information obtained from other owners or managers will not be used in any form to recommend prices for leases to FPI; (2) FPI’s non-public, confidential information will be not used to recommend prices to other owners or managers; (3) recommendations made to other owners or managers will not be disclosed to FPI; and (4) recommendations made to FPI will not be disclosed to other owners or managers. FPI also will pay $2.8 million into a class settlement fund.

Summary Judgment

Agri-Stats Moves for Summary Judgment in DOJ Case – United States v. Agri-Stats, No. 23-cv-3009 (D. Minn.)

  • In August 2024, the DOJ sued Agri-Stats, alleging that the provider of business intelligence reports facilitated an unlawful information exchange among its meat processor customers, in violation of Section 1.
  • The complaint alleges Agri-Stats collects competitively sensitive information from meat producers, runs the information through its data analytics software, and redistributes the information to the producers. DOJ further alleges Agri-Stats provides consulting services and meets with individual subscribers, advises them on opportunities to increase prices and revenues, and shares competitor information received by Agri-Stats but not contained in the reports.
  • On September 17, 2025, Agri-Stats moved for summary judgment, arguing that DOJ cannot establish market-wide harm to competition. In the alternative, Agri-Stats urged the court to limit DOJ’s claims to two broiler chicken reports because DOJ offered evidence of anticompetitive effects for only two such reports and Agri-Stats no longer distributes pork or turkey reports.
  • The DOJ’s opposition is due on October 8, 2025.

Comments from Enforcers

Antitrust Enforcers Speak Publicly About Their Approaches to Pricing Algorithms

  • Speaking at the 52nd Annual Conference on International Antitrust Law and Policy at the Fordham School of Law on September 18, 2025, Assistant Attorney General for Antitrust Gail Slater discussed the application of antitrust law to pricing algorithms. She called the issues raised in DOJ’s case against RealPage “bread and butter antitrust,” noting that while not all pricing algorithms are “bad,” the RealPage case involves a shared algorithm, use of competitively sensitive data, and “anticompetitive outcomes.”
  • At the same conference, the head of the UK’s Competition and Markets Authority (CMA), Sarah Cardwell, indicated that the CMA has no active cases concerning algorithmic pricing. The CMA plans to closely monitor the landscape and devise its enforcement policy.