Hotel Pricing Software Antitrust Risk After the 2026 Ruling

Room rates at five Atlantic City casino-hotels rose 22 to 25 percent while occupancy fell 5 to 8 percent, according to a complaint a federal appeals court decided on July 29, 2026 was detailed enough to move forward. The defendants, Caesars, Harrah's, Tropicana, MGM's Borgata, and Hard Rock, all ran their pricing through the same platform, Cendyn's Rainmaker, and the plaintiffs argue it pooled each property's non-public data and pushed back synchronized recommendations the hotels followed roughly 90 percent of the time.

This is not a casino story. It is a question about whether the pricing software running behind your booking engine treats your rate recommendation as yours alone, or blends it with what your competitors are not telling the public. Independent and boutique hotels on a shared revenue management platform inherit a version of the same exposure, and most have never asked their vendor to answer it in writing.

Hotel Pricing Software Faces Legal Risk

A hub-and-spoke pricing conspiracy is an arrangement where competing businesses funnel non-public data through a single third party, which pools it and pushes back coordinated pricing recommendations. That is the theory a federal appeals court let move forward in July 2026, and it is why the software running behind your booking engine is no longer just a revenue question. It is a legal one.

On July 29, 2026, the Third Circuit Court of Appeals reversed a lower court's dismissal in Cornish-Adebiyi v. Caesars Entertainment, Inc., reviving antitrust claims against five Atlantic City casino-hotel operators, Caesars, Harrah's, Tropicana, MGM's Borgata, and Hard Rock. The plaintiffs allege the hotels fed non-public room pricing and occupancy data into Cendyn's Rainmaker platform, which pooled it across competitors and generated pricing recommendations the hotels followed roughly 90 percent of the time.

Bottom line: the ruling does not ban dynamic pricing software. It bans pooling non-public competitor data through a shared vendor to generate synchronized rates, and it lowers the bar for plaintiffs to get that claim in front of a jury.

What Did the Rainmaker Ruling Decide?

The Third Circuit decided that hotels do not need to prove direct competitor-to-competitor communication to face a Sherman Act claim. Feeding non-public data into a shared algorithm that pools it across competitors and returns synchronized pricing recommendations is, on its own, enough to plead an unlawful agreement.

The plaintiffs' complaint pointed to a specific pattern: room rates across the five properties rose 22 to 25 percent while occupancy fell 5 to 8 percent, a combination the complaint called a departure from how these casino-hotels priced before adopting the shared platform. In ordinary competitive conditions, falling occupancy pulls rates down as properties compete for the guests still booking. Rates and occupancy moving in opposite directions, sustained across five competitors on the same software, is what the court treated as a plausible signal of coordination rather than five independent pricing decisions that happened to land in the same place.

The Federal Trade Commission and Department of Justice filed a statement of interest in the case in March 2024 making the underlying point explicit: "Competitors cannot lawfully cooperate to set their prices, whether via their staff or an algorithm, even if the competitors never communicate with each other directly." The agencies also argued that retaining the discretion to override a recommendation does not cure the problem, since "setting or recommending initial starting prices can still violate the antitrust laws even if those are not the prices that consumers ultimately pay."

Bottom line: discretion to override a recommendation is not a legal shield if the recommendation itself was built from pooled competitor data.

Antitrust Risk Starts With Pooled Data

The dividing line the Third Circuit drew is narrower than the headlines suggest. Independently licensing the same software as your competitors, and forecasting only from your own history, your own booking pace, and public market data, does not create a conspiracy claim on its own. The exposure appears when the vendor pools non-public data across competing properties and hands back a recommendation shaped by what your rivals are quietly doing.

That distinction matters because most hotel revenue management systems sit somewhere on a spectrum, not cleanly on one side of it. A system that only ingests your own PMS data, your own channel mix, and publicly available comp-set rate shops is forecasting demand, the same distinction covered in our hotel demand forecasting playbook, and which every RMS on the market claims to do. A system that also ingests non-public rate and occupancy data from named competitors and blends it into your recommendation is doing something closer to what Rainmaker was accused of.

Bottom line: the question that determines your exposure is not "do you use pricing software," it is "does that software's recommendation contain another property's non-public numbers."

Is Your Hotel Sharing Data It Shouldn't?

Most independent and boutique hotels are not sharing non-public data with competitors on purpose. The risk is usually structural: a revenue management platform sold on "market intelligence" that turns out to include other subscribers' actual rate and occupancy figures, not just public rate shops, bundled into the same dashboard without a clear label on which numbers came from where.

In our own portfolio reviews, the most common finding is not a hotel deliberately pooling data. It is a hotel that never asked the question, because the sales conversation focused entirely on RevPAR lift and never touched where the "competitive intelligence" tab's numbers actually originate. A vendor contract that says data is "aggregated" or "anonymized" is not the same as a guarantee that no non-public competitor figures reach your recommendation engine, and courts in 2026 are not treating that language as a defense.

Bottom line: ask your vendor, in writing, whether your recommendation is generated from your data plus public rate shops, or from your data plus other subscribers' non-public figures. If they cannot answer clearly, that ambiguity is itself the risk.

Antitrust Risk by the Numbers

The Cornish-Adebiyi complaint's own figures show why regulators and courts are paying attention. A 22 to 25 percent rate increase paired with a 5 to 8 percent occupancy decline is not automatically illegal on its own, but it is the kind of pattern that turns a routine RMS lawsuit into one that survives a motion to dismiss.

Run the arithmetic on a hypothetical 150-room property at a $180 average daily rate (ADR) and 72 percent occupancy. RevPAR starts at $129.60. Apply the complaint's alleged midpoint, a 23.5 percent rate increase to $222.30 and a 6.5 percent occupancy decline to 67.3 percent. RevPAR moves to $149.60, a 15.4 percent gain on paper. That gain is exactly the pattern regulators flagged: a property posting stronger RevPAR while pricing in a way that only makes sense if it expected competitors to hold their rates too, rather than undercut it as occupancy fell, the opposite of the sell-through math in our hotel compression pricing piece, where rate lift is only defensible against your own occupancy curve.

Separately, the Department of Justice's proposed settlement with RealPage, covering algorithmic rent pricing in multifamily housing and reported by NPR in November 2025, put new limits on sharing non-public competitor data through a pricing algorithm in a different sector entirely. Two federal actions in two different industries, both targeting the same mechanism, is a signal this is a pattern of enforcement, not a one-off casino case.

Bottom line: a RevPAR gain that only holds up if every competitor on the same software also held its rate is not a pricing win. It is the fact pattern regulators are now actively litigating.

The Compliance Checklist for Hoteliers

A hotel does not need outside counsel to run a first-pass check on its own pricing setup. Six questions cover most of what Cornish-Adebiyi turns on.

• Does your RMS contract disclose, in plain language, whether your forecast model uses other subscribers' non-public rate or occupancy data?
• Can you name, specifically, which data sources feed your daily rate recommendation?
• Does your comp-set data come only from public rate shops (OTA-visible prices), rather than a vendor-side data pool?
• Has your rate and occupancy trend moved in the same direction as your named comp set's, closely enough that it would be hard to explain as independent decisions?
• Do you retain, and actually use, the discretion to deviate from the software's recommendation?
• Would you be comfortable showing a regulator exactly what inputs produced last week's rate change?

Bottom line: if you cannot answer the first question today, that is the finding, and it is worth resolving before a plaintiff's attorney asks it for you.

What a Safe Pricing Setup Looks Like

A defensible pricing setup for an independent or boutique hotel in 2026 rests on three things: forecasting from your own data and public market signals, a named person accountable for every rate decision, and a paper trail showing why a rate moved. None of those three require abandoning dynamic pricing.

The properties we work with price from their own PMS history, their own booking pace, and publicly visible OTA rate shops, the same comp-set research any revenue manager has always done. What changes is that a dedicated strategist reviews the recommendation before it goes live, documents the reasoning, and can explain any given Tuesday's rate without pointing at a black box that also serves five competitors down the street, the same gap we quantify in RMS software versus managed dynamic pricing. That is a meaningfully different exposure profile than a shared vendor pooling non-public figures across a market.

Bottom line: the fix is not less pricing sophistication, it is a pricing process you can explain, sourced from data you actually own the rights to see.

Frequently Asked Questions

Conclusion

Cornish-Adebiyi does not mean dynamic pricing is dead for hotels. It means the industry's easy assumption, that any RMS with a good RevPAR pitch is automatically safe, no longer holds. The properties with the least exposure in 2026 are the ones that can say exactly what data built today's rate and who signed off on it.

If you cannot currently answer that question about your own pricing software, get in touch and we will walk through your setup with you.