Introduction
The Department of Justice (DOJ) [1] [2] [3] [4] [5], in collaboration with eight state attorneys general [1] [3], has filed a civil antitrust lawsuit against RealPage Inc [1] [3], a Texas-based software company known for its property management software [1] [3], and several landlords using its services [1] [3]. This legal action is part of a broader trend of antitrust scrutiny on algorithmic pricing tools, highlighting a rigorous regulatory stance on emerging AI technologies. The case focuses on allegations that RealPage’s pricing algorithms facilitate collusion among landlords, leading to inflated rental prices and potential violations of the Sherman Act.
Description
The Department of Justice (DOJ) [1] [2] [3] [4] [5], alongside eight state attorneys general [1] [3], has initiated a civil antitrust lawsuit against RealPage Inc [1] [3], a Texas-based software company recognized for its property management software [1] [3], and several landlords utilizing its services [1] [3]. This lawsuit is part of a broader trend of antitrust actions targeting algorithmic pricing tools [1] [3], reflecting a stringent regulatory approach towards emerging AI technologies [1] [3]. RealPage has faced multiple lawsuits since 2022 for alleged violations of the Sherman Act [5], specifically for enabling landlords to collude through its pricing algorithm [5], which has drawn the attention of Congress [5], the DOJ [1] [2] [3] [4], and the Federal Trade Commission (FTC) [5].
The complaint centers on RealPage’s YieldStar and AI Revenue Management software [2], which generates pricing recommendations for property owners and managers by analyzing non-public and sensitive data from participating landlords and property management companies [1] [3]. The DOJ alleges that these recommendations facilitate collusion among landlords, leading to uniform rental price increases that insulate prices from competitive market forces, inflate rents [1] [3] [5], and adversely affect tenants nationwide [1] [3], thereby violating Sections 1 and 2 of the Sherman Act [1] [3]. The DOJ asserts that the use of price-setting algorithms among competitors can constitute an unlawful agreement, even if the prices generated are not final. Senator Amy Klobuchar has been instrumental in advocating for federal policies to monitor such practices [5], urging investigations into potential anticompetitive conduct affecting rental prices [5].
Furthermore, the complaint claims that RealPage monopolizes the commercial revenue management software market [1] [2] [3], holding an 80% market share [1] [2] [3]. Exclusive agreements with landlords mandate the use of RealPage’s systems for pricing quotes [1], reinforcing the allegations of Sherman Act violations [1]. The DOJ has also raised concerns about the marketing practices of algorithm developers [4], suggesting that such practices may encourage collusion by implying that competitors are employing similar pricing strategies, which could lead to a perception of safety in setting prices without fear of being undercut. In 2023, Klobuchar introduced the Preventing Algorithmic Collusion Act [5], aimed at modernizing antitrust enforcement to address algorithm-driven pricing models [5].
The DOJ’s stance indicates a potential view of AI algorithms as facilitators of collusion among competitors [1]. The previous safe harbor guidelines that allowed information sharing among competitors have been withdrawn [1] [3], leading to a more cautious interpretation of algorithms that utilize nonpublic data for recommendations [1]. In a departure from previous cases [1] [3], the DOJ is applying a rule of reason analysis rather than a per se theory [1] [3], requiring courts to evaluate the anti-competitive effects against any pro-competitive justifications [1]. The DOJ’s Antitrust Division has indicated it will evaluate algorithmic information exchanges similarly to traditional exchanges [5], signaling a shift in how these practices are regulated [5].
This lawsuit is not isolated; a private action against RealPage and its clients was filed earlier in 2023 [1], echoing similar allegations regarding the AI pricing model [1] [3]. The court in that case noted indications of a horizontal agreement among landlords based on their pricing behaviors [1], particularly in light of their parallel conduct in raising prices despite higher vacancy rates [3]. Additional lawsuits have emerged in various jurisdictions [5], including a recent case filed by the District of Columbia Attorney General against RealPage and several landlords for violations of local antitrust laws [5].
While many AI pricing algorithms may not fall under the DOJ’s scrutiny [1], RealPage’s model [1] [3], which aggregates private data from multiple landlords [1] [3], raises unique concerns [1]. The DOJ’s complaint highlights specific regional pricing dynamics [1], particularly in areas with significant rental populations [1]. Legal precedents illustrate the complexities in distinguishing between different algorithmic pricing practices [1], with courts showing a willingness to scrutinize the sharing of confidential information among competitors [3].
The geographical context of the real estate market may also play a crucial role in these legal considerations [1], as it is more pronounced for long-term renters compared to transient hotel guests [1]. The DOJ’s action against RealPage follows a pattern of enforcement actions that emerge after private lawsuits [1], indicating a shift in how antitrust enforcement may be approached in the context of AI technologies [1].
The dual approach of the DOJ [1], combining a per se theory in private actions with a rule of reason in its own case [1], suggests a comprehensive strategy to ensure compliance with the Sherman Act [1]. Companies utilizing AI-driven pricing algorithms [1] [3], particularly those trained on nonpublic data [1], should closely monitor this case [1] [3], as it could significantly influence pricing strategies across various sectors [1] [3]. Additionally, emerging legislative measures [1], such as San Francisco’s ordinance against using nonpublic competitor data for pricing [1], may further complicate the regulatory landscape [1].
Businesses employing pricing algorithms are advised to thoroughly assess their operations [1], document any competitive advantages [1], and ensure they have protections in place against potential investigations [1]. Strategies for navigating these challenges include understanding the functionality of pricing algorithms [5], consulting data experts to uncover collusive practices [5], and staying informed about regulatory developments [5]. Tailored strategies will be essential to mitigate scrutiny in this evolving legal environment [1], and educating clients on their rights under antitrust laws will be crucial in strengthening legal cases and promoting consumer protection [5].
Conclusion
The DOJ’s lawsuit against RealPage Inc underscores the increasing regulatory focus on AI-driven pricing algorithms and their potential to facilitate anticompetitive practices. This case could have significant implications for companies using similar technologies, prompting them to reassess their pricing strategies and compliance with antitrust laws. As legislative measures evolve, businesses must remain vigilant and proactive in understanding the legal landscape to mitigate risks and ensure consumer protection.
References
[1] https://www.lexology.com/library/detail.aspx?g=1af8a3b4-885e-4bb9-b074-f5cac446cdb8
[2] https://www.theracetothebottom.org/rttb/2024/10/29/collusion-by-code-the-dojs-case-against-realpages-pricing-algorithm
[3] https://www.jdsupra.com/legalnews/doj-targets-ai-pricing-algorithms-8887388/
[4] https://www.manatt.com/insights/news/2024/carson-quoted-in-bloomberg-law-article-discussing
[5] https://www.darrow.ai/algorithmic-pricing/
