New Ruling Clarifies Algorithmic Price-Fixing Antitrust Risk

A recent decision from the Superior Court in Alameda County, California, sheds new light on the antitrust implications of competitors using the same third-party pricing algorithm. The ruling is the latest in a growing wave of cases testing algorithmic price-fixing claims, following similar challenges in industries ranging from pork processing to healthcare.

In Mach v. Yardi Systems, Inc., plaintiffs alleged that Yardi Systems and competing rental property owners or managers engaged in a price-fixing scheme by using Yardi’s algorithmic software to set rental rates. They claimed this conduct violated California’s antitrust law and Unfair Competition Law. The court, however, granted summary judgment in favor of Yardi and the property owner/manager defendants.

Plaintiffs alleged this was a “give-to-get” scheme: rental property owners and managers provided Yardi with confidential pricing data, knowing competitors did the same. Yardi used this information in its algorithm to set the highest possible rental rates in the market, they claimed. Plaintiffs alternatively alleged that, even without sharing confidential information, each owner and manager defendant agreed to adopt Yardi’s common rental-pricing algorithm.

A “hub-and-spoke” conspiracy

The court characterized the plaintiffs’ theory as a “hub-and-spoke” conspiracy, with Yardi as the hub and its licensing agreements with property owners and managers as the spokes. It held that to establish horizontal price-fixing, plaintiffs must show an agreement among competing property owners/managers—not just separate agreements with Yardi. That agreement would entail competitors jointly using Yardi’s software, sharing confidential data for algorithmic pricing recommendations, and implementing those recommendations with a shared understanding that Yardi would set rents above competitive levels. 

In short, there must be a “rim” connecting the spokes: a horizontal agreement among competitors. The court noted that such an agreement could be established by explicit or implicit evidence or both.

The court found, however, that there was no agreement, explicit or implicit, between any of the spokes.  In other words, there was no rim.

Significantly, Yardi produced its algorithm’s source code to both the court and the plaintiffs. Yardi’s expert testified that the code showed no sharing of confidential pricing information among competing property owners or managers using the platform, even though users did input data into the system. The court found undisputed evidence that competitors had not agreed to cooperate or to share commercially sensitive rental pricing data to obtain price recommendations. It emphasized that owners and managers were neither providing pricing information to competitors through Yardi nor receiving recommendations based on competitors’ confidential data.

The “subterfuge” element

The court noted that the Yardi algorithm did use aggregated system-wide data that created nationwide coefficients applied as weights to an individual property owner’s data. In other words, the algorithm used nationwide trends in connection with an owner’s/manager’s own data.

The court also noted that Yardi employed agents to cold-call local owners/managers pretending to be potential renters to obtain pricing and occupancy data. The court noted that obtaining information in this manner may be a “subterfuge,” but it does not create an explicit or implicit agreement among competitors.

The court also relied on Supreme Court and federal appellate precedent holding that, absent an agreement among competitors to fix prices, information sharing can be procompetitive and is therefore analyzed under the Rule of Reason. Under that framework, courts weigh a practice’s procompetitive benefits against its potential anticompetitive effects.

Finally, the court held that the independent decision of each rental property owner/manager to use the same algorithm was not by itself an antitrust violation. The court cited other decisions holding that an agreement in which algorithm developers provide rental price recommendations to users does not, by itself, restrict a user’s ability to set rental prices as it chooses. This would be true even if the owners/managers decided to use the recommendation. There must be something more.

The Yardi decision by the Alameda County Court used fundamental antitrust principles as to analyze the common use of a pricing algorithm. These principles make it easier to assess whether using a pricing algorithm raises antitrust concerns and help companies avoid violating the law.