No Day But Today: Greystar Reaches Settlement Agreement with the Department of Justice in RealPage Algorithmic Pricing Case
Last August, the Justice Department initiated legal action against RealPage, a prominent property management software company. The lawsuit alleged that RealPage facilitated rent coordination through its revenue management product, potentially breaching Sections 1 and 2 of the Sherman Antitrust Act. By January, the DOJ expanded its complaint to encompass six multifamily apartment owners and managers, asserting that these landlords exchanged competitively sensitive information, beyond their common use of RealPage. RealPage’s operations have also encountered private lawsuits and challenges from local authorities in regions like D.C. and Arizona.
The Proposed Greystar Consent Decree
Recently, the DOJ filed a Proposed Final Judgment against Greystar Management Services, LLC — identified as the largest landlord in the U.S. by the DOJ. While this Proposed Final Judgment does not hold the same power as a court ruling, it offers insight into the boundaries set by legal enforcers.
The Final Judgment’s terms are set to remain effective for five years post-entry unless extended by the court or terminated at least two years in by the DOJ if deemed unnecessary or not in public interest.
Central to the Final Judgment is the prohibition on licensing or using any revenue management tool that leverages non-public data to set rents. Greystar cannot utilize a revenue management product that enforces a rental price floor or limits on rental price reduction recommendations, or mandates acceptance of suggested rental prices. Greystar must confirm to the DOJ that any selected product meets the necessary non-public data compliance requirements. Should Greystar be unable to certify compliance with the Final Judgment, a Monitor will be appointed to oversee the company’s adherence to these directives.
Information Sharing Prohibitions
The Final Judgment also addresses restrictions surrounding information sharing. The past 50 years have seen antitrust restrictions evolve significantly, particularly concerning historical and aggregated data. Antitrust views have further adapted with advancements in algorithmic pricing and artificial intelligence. This adaptation is clearly evident in the consent decree’s provisions. Notably, the DOJ has expanded the definition of competitively sensitive information to encompass:
- Data that could reveal current or future rental supply, demand, or pricing at a property.
- Details regarding the use of settings or user-specified parameters in revenue management products.
- Information about rental pricing amounts, formulas, or strategies.
Furthermore, Greystar is forbidden from making any formal or informal agreements with other landlords regarding which revenue management product to use, sharing non-public data with or soliciting it from other landlords, or utilizing any non-public data received from other landlords. The company is also restricted from attending RealPage meetings, which the DOJ alleged were instrumental in the improper conduct.
The Final Judgment mandates a comprehensive antitrust compliance plan and officer, obliges Greystar to cooperate with the DOJ’s case against RealPage and associated landlords, and requires that Greystar allow DOJ inspection of its operations and records with reasonable notice. In settlements like this, the imposed conduct remedies often surpass what might be mandated in court, encompassing not only the prohibition of specific past unlawful acts but also actions that could potentially lead to violations again. These are commonly known as “fencing in” provisions.
In light of the settlement, the Assistant Attorney General for the Antitrust Division warned that as these systems become more common in the economy, the number of investigations centered on these shared algorithms is set to rise. To mitigate risk, it is suggested that companies thoroughly review the inputs and functionality of shared algorithms to prevent collusion detrimental to consumers. Clearly, algorithmic price-fixing remains a significant concern for regulators and enforcers, and it is likely to continue to be rigorously examined in the foreseeable future.
