Key Takeaways
Pricing software that learns from competitors’ non-public data poses a compliance risk.
Companies operating in the EU must establish robust compliance policies for the pricing software they use.
Pricing practices that are illegal when implemented offline are also likely to be illegal when implemented online.
Software-based pricing is quickly becoming the industry standard. At the same time, competition authorities are recalibrating their enforcement tools to potentially tackle a new form of cartel activity. With the recent proposed settlement between the U.S. Department of Justice (DOJ) and RealPage, the antitrust risks associated with software-based pricing have become a focus of attention. In the proposed settlement, the DOJ provided a blueprint for how authorities can dismantle the sharing of algorithmic information. For companies operating in the EU, the challenge is even more complex due to the strict interpretation of Article 101 TFEU regarding “concerted practices”. Companies must now proactively monitor the operation of their digital pricing tools to ensure antitrust compliance. This update analyzes current international regulatory trends and outlines essential compliance frameworks for companies navigating the EU’s tough competition regime.
RealPage: Hub-and-spoke risk
The U.S. Department of Justice has filed a proposed settlement in the RealPage litigation, likely the most prominent dispute to date over software-based algorithmic pricing. The case concerns several property managers and landlords who allegedly calculated their rents using RealPage software. The software was based on non-public, competitively sensitive information (CSI). According to the DOJ, use of the software resulted in a hub-and-spoke cartel because the shared service provider’s software, used by competitors, coordinated prices upward for all of them. There was no need for competitors to communicate directly with each other.
Key elements of the proposed settlement
The settlement does not ban the software itself, but imposes extremely narrow guardrails:
- Prohibition on using CSI at runtime: RealPage should not use CSI during the ‘runtime operation’. This applies to both current and historical data.
- In the real estate context, CSI includes all data that can be used to determine current or future availability, demand (e.g. vacancy information), pricing, including pricing formulas, and pricing strategies (e.g. rental concessions).
- Why is RealPage also not allowed to use historical data? The DOJ likely wants to prevent the algorithm from “reverse-engineering” competitors’ current strategies based on past patterns. In this sector, even older data can increase transparency.
- Strict rules for AI training: For model training, RealPage may only use CSI that is at least 12 months old and does not refer to geographic areas smaller than national data.
- Ban on nudging: In addition, RealPage is prohibited from using market research data, aggregate supply/demand curves for competitors in the same region, and features that encourage users to accept price recommendations, among other things.
- External monitor: RealPage must submit to supervision by a court-appointed external supervisor.
EU perspective: Is there a safe harbour?
Many aspects of the proposed settlement reflect the general approach currently taken by the European Commission in software-based pricing cases. However, there are subtle differences that are crucial for companies operating in Europe.
- Making CSI less risky: EU competition law requires a high degree of caution when pricing software uses competitors’ CSI, especially with regard to prices and capacity. To mitigate antitrust risks, companies should prioritize using neutralized information, such as anonymized, aggregated, or sufficiently historical data sets, rather than detailed, real-time input.
- In the EU, data older than twelve months is often considered “historical” and therefore less problematic. However, competition authorities consistently emphasize the need for a case-by-case assessment. In a rapidly changing market, even six months old data can be considered historical, while in a market with long-term contracts, even eighteen months old data can still be considered strategically valuable and therefore CSI.
- As in the US, EU competition law also considers the exchange of sufficient aggregated information to be less critical. This is especially true when data cannot – or only with difficulty – be attributed to individual companies, or when information is aggregated across different products, especially if they belong to different markets. For the real estate sector, this is the case for data that refers to national information rather than to smaller geographical units.
- Training vs. Execution: It is essential to distinguish between the (more market-oriented) training of an AI and its (more market-oriented) deployment. The logic of the settlement is compelling: collusion risks arise mainly where AI can directly influence market behavior.
- Be careful with ready-made solutions for industry: While the use of publicly available data in pricing algorithms is generally permitted under EU competition law, companies must remain vigilant against tacit collusion. This can happen when a common software vendor implements a standardized pricing or discount formula for a specific industry. Before an “industry standard” instrument is adopted, a rigorous antitrust review is required to ensure that it does not facilitate horizontal coordination.
Enforcement is increasing in the EU
The ongoing RealPage procedure symbolizes the increased enforcement that can also be expected on this side of the Atlantic Ocean. Evidence includes not only statements from authorities, such as DG Competition Deputy Director General Linsey McCallum’s confirmation in July 2025 that several EU-level investigations into algorithmic pricing are underway. Testament is also the changing regulations. Two regulatory heavyweights now flank traditional competition law.
- The AI law: Since August 1, 2024, the EU AI Act has mandated a new level of transparency between regulators. Article 74(2) requires AI market surveillance authorities in all Member States to share competition-relevant matters with antitrust authorities and the European Commission on an annual basis. For companies, this translates into an increased risk of discovery: an investigation into the security or transparency of an algorithm can now seamlessly lead to a parallel antitrust investigation. Note that the European Commission has just published guidelines on the definition of AI systems.
- D.M.A.: According to many policymakers, generative AI services should be classified as standalone core platform services in the future. They may also already fall under existing DMA categories (such as online search engines, virtual assistants or cloud computing). A year ago, the European Commission clarified Policy overview “Competition in generative AI and virtual worlds” that it views competition law and the DMA as complementary tools for generative AI.
Business Checklist: How to Secure Your Pricing Software
To avoid compliance risks, companies should subject their pricing instruments to an “antitrust compliance audit”:
- Please note when using CSI: Software price and discount recommendations should not be based on non-public competitor data.
- Contract design with software suppliers: When purchasing pricing software, contractual arrangements should be carefully assessed for antitrust risks (e.g., clear provisions on access rights, data use limitations, and audit rights).
- Compliance by Design: It is advisable to assess the functionality of the software. Can the software technically access and input competitors’ CSI? What is being advertised? Insist on implementing technical limitations if necessary. If detailed and/or up-to-date competitor data is used for AI training, strict separation of data pools is essential.
- Right to intervene: Avoid automatic underwriting features in your pricing software.
- To monitor recommended retail prices (RRP): When your software comes into contact with your distributors, antitrust compliance is critical. In particular, ensure that “recommended” prices do not become mandatory in practice. If your software automatically monitors retailers and triggers ‘punishments’ such as automated warning letters or lower search results if you deviate from the recommended retail price, this could likely amount to price fixing. The German Federal Cartel Office has just banned prevents a major online platform from applying so-called price control mechanisms.
Conclusion: The RealPage settlement and the recent intensification of EU enforcement send a clear message: the black box defense (“We didn’t know what the software did”) doesn’t work. If pricing practices are illegal when implemented offline, chances are they will also be illegal when implemented online. Proactive, continuous monitoring of pricing algorithms is no longer a nice-to-have; it is a fundamental pillar of modern corporate compliance.
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