Competition Litigation Update - September 2023
Sign Up for PublicationsTHE RISKS OF Algorithmic Pricing
What is algorithmic pricing?
Algorithmic pricing refers to a collection of pricing rules or strategies that are predetermined and used to establish prices. Algorithmic pricing software utilizes historical patterns and current data within a specific market to provide pricing recommendations that align with the preferences and objectives of the end-user (i.e., the price-setter). Recently, the term algorithmic pricing has been more commonly used to refer to the use of computer systems to apply a pricing strategy that automatically determines prices, with little or no manual intervention. Although this practice can lead to more efficient pricing and better market outcomes, it has also raised competition law concerns.
With algorithmic pricing, there is potential for collusion or price-fixing among competitors, even without the competitors specifically knowing of the collusion. This is because if algorithms are programmed to monitor competitors’ prices and automatically adjust their own prices in response, it may lead to artificially inflated prices and reduced competition.
DOJ and FTC’s Treatment of Algorithmic Pricing
The Department of Justice (“DOJ”) and the U.S. Federal Trade Commission (“FTC”) have been somewhat conservative in their treatment of algorithmic pricing. They proposed that when examining cases involving pricing algorithms used by competitors, the focus should be on determining whether PRICES REFLECT AN ILLEGAL AGREEMENT, AS OPPOSED TO… there is an illegal agreement between prices, as opposed to mere “conscious parallelism.”
Overall, there is limited precedent from regulatory authorities concerning algorithmic pricing in the United States. In 2015, the DOJ announced its first prosecution specifically targeting internet commerce and the use of pricing algorithms in United States v. Topkins, No. 15-cr-00201, criminal information filed (N.D. Cal. Apr. 6, 2015). The defendant, David Topkins, was a seller of wall posters on Amazon’s Marketplace and was accused of conspiring with other poster sellers to fix the prices of posters sold online. To coordinate and enforce the price-fixing conspiracy, Topkins and his co-conspirators agreed to use pricing algorithms that were designed to monitor and match each other’s prices. In this conspiracy, one company would program an algorithm to search for the lowest price offered by a non-conspiring competitor on particular posters, and to set that company’s price for that poster just below the non-conspiring competitor’s price. Meanwhile, another conspiring company programmed its algorithm to match the first company’s prices. Topkins shortly pled guilty to one count of price-fixing, a violation of the Sherman Antitrust Act, which prohibits anti-competitive agreements among competitors. According to the DOJ’s press release, Topkins agreed to pay a $20,000 fine and to cooperate with the ongoing investigation into the price-fixing conspiracy. “Former E-Commerce Executive Charged with Price Fixing in the Antitrust Division’s First Online Marketplace Prosecution,” April 6, 2020, available at https://www.justice.gov/opa/pr/former-e-commerce-executive-charged-price-fixing-antitrust-divisions-first-online-marketplace (last accessed April 12, 2023). Although Topkins involved a relatively simple pricing algorithm and a human agreement to collude, it is significant because it demonstrates that the DOJ is willing to pursue antitrust enforcement actions against individuals and companies using pricing algorithms to facilitate collusion or engage in other anti-competitive practices.
The FTC, however, did not indicate that this was any change in its antitrust approach. In 2017, the then Acting Chairman of the FTC, Maureen Ohlhausen, said in a speech that “[f]rom an antitrust perspective, the expanding use of algorithms raises familiar issues that are well within the existing canon,” and that “[t]his is just not a place where antitrust needs to impose new rules in response to new tools.” Should We Fear The Things That Go Beep In the Night? Some Initial Thoughts on the Intersection of Antitrust Law and Algorithmic Pricing,” Maureen K. Ohlhausen, May 23, 2017, available at https://www.ftc.gov/public-statements/2017/05/should-we-fear-things-go-beep-night-some-initial-thoughts-intersection (last accessed April 13, 2023), at 2, 7-8 (“Ohlhausen”). She said that in a free market, individual actors are free to set their prices based on all the information that is legally available to them. Ohlhausen however also asked important questions: “Are there opportunities for mischief in the black box nature of all this? Will the use of pricing algorithms allow firms to collude or increase prices in ways that will ultimately go undetected by the enforcement agencies? Does antitrust doctrine need to change in important ways to reflect the greater use of automated decision-making across markets?” Id.
FTC officials did indicate in public statements that the rise in “robo-sellers” employing pricing algorithms to establish their prices could complicate distinguishing between intentional collusion and conscious parallelism: “a number of current inquiries used to distinguish conscious parallelism from express collusion will be of limited use in the machine context. Concepts such as ‘intent’ and ‘meeting of the minds’ . . . ‘presuppose quintessentially human mental states’ and thus ‘may prove less useful in dealing with computer software and hardware.’” Terrell McSweeny and Brian O’Dea, “The Implications of Algorithmic Pricing for Coordinated Effects Analysis and Price Discrimination Markets in Antitrust Enforcement,” American Bar Association, Antitrust, Vol. 32, No. 1 (Fall 2017), available at https://www.ftc.gov/system/files/documents/public_statements/1286183/mcsweeny_and_odea_-_implications_of_algorithmic_pricing_antitrust_fall_2017_0.pdf at 75 (“McSweeny and O’Dea”).
More recently, in 2020, Deputy Assistant Attorney General Richard A. Powers said that “the U.S. legal standard for a criminal antitrust violation remains constant; it requires proof beyond a reasonable doubt of an agreement among two or more competitors to fix prices, rig bids, or allocate markets, that occurs in, or affects, interstate commerce…. Criminal prosecution is typically limited to bid rigging, price fixing, and allocation agreements, and the Antitrust Division has significant experience prosecuting anticompetitive conspiracies carried out by a range of means and methods, and that could include using pricing algorithms.” “Deputy Assistant Attorney General Richard A. Powers Delivers Remarks at Cartel Working Group Plenary: Big Data and Cartelization, 2020 International Competition Network Annual Conference” Washington, D.C., Sept. 17, 2020, available at https://www.justice.gov/opa/speech/deputy-assistant-attorney-general-richard-powers-delivers-remarks-cartel-working-group (last accessed April 14, 2023). Powers further explained that in the context of collusive agreements, the U.S. will prosecute any involved intermediaries as well: “[I]f an intermediary, such as a programmer or platform, facilitates a conspiracy among competitors to use a common pricing algorithm for the purpose of fixing prices, under U.S. law, we could prosecute both the competitors and the intermediary who facilitated the illegal agreement.” Id.
However, at the 21st Annual International Competition Network Conference in 2022, Assistant Attorney General Jonathan Kanter, who oversees DOJ’s Antitrust Division, seemed to indicate that organizations might need to take proactive steps relating to algorithmic pricing. According to Kanter, “Whether you use a smoke-filled room in a basement or you’re using AI and an API, it’s still the same thing. It’s still collusion.” He suggested that there is a role for corporate compliance programs preventing collusion by algorithms, and that companies proactively design and train algorithms and AI programs to avoid collusion, in a similar way to how they train employees to comply with other legal requirements.
Claims Brought Against Algorithmic Pricing in U.S. Courts By Private Plaintiffs
Plaintiffs have filed a number of suits alleging that algorithmic pricing is a violation of Section 1 of the Sherman Act. These suits are currently in the initial stages of litigation within federal courts around the U.S., and none of them has gone to verdict. These suits contend that the competitors and their software provider participate in a “hub and spoke” conspiracy to establish fixed prices. “Hub and spoke” conspiracies refer to a type of antitrust violation where a central firm, or “hub,” coordinates a price-fixing or collusion scheme among multiple competitors, the “spokes.” In this type of model, the hub acts as an intermediary, enabling the spokes to engage in anti-competitive behavior without directly communicating with each other.
As an example, in a recent lawsuit filed in U.S. District Court in Las Vegas, hotel guests are pursuing class-action damages, claiming excessive room charges resulting from an anticompetitive scheme. Gibson v. MGM Resorts Int’l, Case No. 2:23-cv-00140-MMD-DJA. The plaintiffs assert that major Las Vegas Strip hotel-casinos engaged in price-fixing by using a third-party vendor to set their hotel room prices. The complaint alleges that the vendor facilitated "algorithmic-driven price-fixing" by collecting competitor pricing data and providing unlawful room rate recommendations for hotel operators' profit maximization.
In summary, the utilization of algorithmic pricing can be used to improve market efficiency and outcomes. However, for any business using algorithmic pricing, it is important to recognize the accompanying risk of being accused of collusion and price-fixing when algorithms monitor and adjust prices in response to competitors.