Property management company Greystar has reached a $7 million settlement with the state of California as part of an ongoing antitrust lawsuit against software company RealPage, the California Department of Justice announced in a Nov. 19 press release.
In a January 2025 complaint, the California attorney general’s office alleged that Greystar and other landlords shared competitively sensitive data to generate pricing recommendations using RealPage’s algorithms. RealPage uses algorithmic models to recommend price increases to subscribers. Greystar and other landlords discussed competitively sensitive topics – including pricing strategies and rents with each other, the attorney general’s office said. The information allowed RealPage to know what competing landlords were charging and could increase profits for landlords by using that information to recommend that landlords set or raise their prices uniformly, eliminating competition and leaving renters no choice but to pay artificially high prices, the attorney general’s office said.
According to the Greystar website, there are seven apartments for rent in Mountain View operated by the property management company.
“Whether it’s through smoke-filled backroom deals or through an algorithm on your computer screen, colluding to drive up prices is illegal,” Attorney General Rob Bonta was quoted in a press release. “Families across the country are staring down an affordability crisis. Companies that intentionally fuel this unaffordability by raising prices to line their own pockets can be sure I will use the full force of my office to hold them accountable. California is stronger when we protect tenants and a competitive economy.”
Greystar is the largest landlord in the United States, managing nearly 950,000 rental units nationwide. It also manages approximately 333 multifamily rental properties in California that use RealPage’s pricing software.
Under the settlement agreement, Greystar, among other requirements, must refrain from using any anticompetitive algorithm that generates pricing recommendations using its rivals’ competitively sensitive data or that incorporates certain anticompetitive features.
