Prosecutors claimed the software allowed landlords to set higher rents
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RealPage Inc. agrees to a major settlement with the U.S. Department of Justice to resolve allegations that its rent-pricing software facilitated illegal algorithmic collusion among landlords.
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Federal prosecutors argued the software allowed competing property owners to coordinate rental prices, inflating rates for millions of tenants nationwide.
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The settlement imposes strict compliance requirements and increased oversight, though RealPage continues to deny wrongdoing.
RealPage Inc., a major provider of rent-pricing software used by some of the nations largest landlords, has reached a settlement with federal prosecutors to end a high-profile investigation into what critics have described as algorithmic collusion in the housing market.
The agreement resolves claims that RealPages flagship product, an algorithm-driven platform designed to recommend optimal rental rates, enabled property owners to coordinate prices in ways that reduced competition and drove up rents.
The Department of Justice (DOJ) had been looking into whether the software effectively acted as a hub for information-sharing among competitors, allowing them to move prices in lockstep without the need for explicit communication.
RealPages rent-optimization tool, used across hundreds of thousands of multifamily units, relies on aggregated data from participating landlords to suggest daily rental prices and occupancy targets. Critics, including tenant advocates and antitrust scholars, argued the system created a de facto cartel by aligning pricing strategies among firms that would otherwise be competing.
The governments case
Federal prosecutors said the practice amounted to an anticompetitive scheme. By feeding confidential pricing and occupancy data into a centralized algorithm, landlords could collectively tighten supply and raise rates while maintaining plausible deniability that any coordination was intentional.
Algorithms cannot be used as a shield for collusion, a DOJ official said in announcing the settlement. Competition laws apply whether coordination happens in a boardroom or in a line of code.
RealPage denies wrongdoing
In the settlement, RealPage did not admit liability but agreed to a set of compliance measures designed to prevent future antitrust violations. These include restrictions on how the company can collect and use competitor data, mandatory monitoring of algorithmic outputs, and regular reporting to federal regulators.
The company said in a statement that its software was never intended to suppress competition and argued that its recommendations were designed to help clients operate more efficiently, not to raise rents artificially. Still, RealPage acknowledged that resolving this matter allows us to focus on serving our customers and improving transparency in our technology.
Broader scrutiny of algorithmic pricing
The RealPage case has become a flashpoint in a broader debate about the growing use of algorithmic pricing tools across industries, from airlines to online retail. Regulators in the U.S. and abroad have warned that advanced analytics and real-time data sharing can enable collusive outcomes even without direct communication among competitors.
Competing companies must make independent pricing decisions, and with the rise of algorithmic and artificial intelligence tools, we will remain at the forefront of vigorous antitrust enforcement, said Assistant Attorney General Abigail Slater of the Justice Departments Antitrust Division.
Housing advocates welcomed the settlement but said it does not go far enough. Some tenant groups are pushing for outright bans on algorithmic rent-setting tools, arguing that they distort the housing market and disproportionately harm low-income renters.
The settlement is expected to influence ongoing civil litigation, including class-action lawsuits filed by renters who allege they paid inflated prices because of RealPages software. It may also trigger closer regulatory scrutiny of similar pricing technologies used in other markets.
Posted: 2025-11-26 12:24:16















