Competition Law and Self-Executing Commercial Agreements and Antitrust

1. Introduction

Self-executing commercial agreements are contractual arrangements in which performance occurs automatically once predefined conditions are satisfied. They may be implemented through software, smart contracts, automated payment systems, pricing algorithms, blockchain protocols, APIs, or other forms of programmed execution.

A conventional contract might state:

“If the market price falls below X, the supplier shall reduce its price by Y%.”

A self-executing arrangement may instead contain code that automatically changes the price, transfers funds, restricts access, adjusts supply, or imposes a commercial consequence when the condition is triggered.

From a competition-law perspective, automation does not change the underlying legal character of conduct. If competitors use software or code to implement price fixing, market allocation, output restrictions, discriminatory access, or exclusionary arrangements, competition authorities can examine the underlying coordination rather than treating the conduct as lawful merely because a computer executed it.

EU antitrust law principally prohibits restrictive agreements and concerted practices under Article 101 TFEU, while Article 102 addresses abusive conduct by dominant undertakings.

In the United States, Section 1 of the Sherman Act similarly addresses concerted restraints of trade. Recent U.S. enforcement has specifically emphasized that competitors cannot avoid antitrust liability by delegating pricing decisions to algorithms.

2. Meaning of Self-Executing Commercial Agreements

A self-executing agreement generally contains four elements:

1. Underlying commercial agreement
2. Predefined conditions
3. Automated decision or execution mechanism
4. Automatic commercial consequence

For example:

Competitors agree → code is deployed → specified market condition occurs → algorithm changes prices → transactions execute automatically.

The technology may involve:

• smart contracts;
• blockchain;
• distributed ledgers;
• algorithmic pricing;
• automated bidding;
• electronic trading systems;
• API-based contracts;
• automated rebates;
• dynamic pricing;
• automated exclusivity mechanisms;
• automated supply allocation;
• digital payment systems.

The central antitrust question is therefore not:

“Did a human manually perform the prohibited act?”

but rather:

“Did independent economic actors coordinate their competitive conduct, and did the automated mechanism implement or facilitate that coordination?”

3. Why Self-Execution Creates Competition-Law Problems

A. Automation can make collusion easier

Traditional cartel enforcement often looks for:

• meetings;
• emails;
• telephone calls;
• written agreements;
• price discussions.

Self-executing arrangements can reduce the need for continuing human communication.

Competitors could potentially establish:

Agreement → algorithm/code → automatic implementation → continuous coordination.

The U.S. Department of Justice's Topkins prosecution is particularly significant because the government described the pricing conspiracy as being implemented through algorithms, with the conspiracy becoming largely self-executing once the algorithms were operational.

B. The code may continue operating after the original agreement

A major legal difficulty arises when the original human decision occurs at time T1, but the competitive effects continue automatically at T2, T3 and T4.

For example:

• Competitors agree in January.
• Smart-contract code is deployed in February.
• The parties cease communicating.
• The code automatically maintains agreed prices throughout the year.

The absence of continuing communication does not necessarily eliminate the underlying agreement.

The important evidence may include:

• the original agreement;
• source code;
• deployment records;
• transaction history;
• API calls;
• algorithmic rules;
• pricing outputs;
• blockchain records;
• communications concerning the code.

4. Self-Execution and the Concept of Agreement

A self-executing contract can create a particularly difficult distinction between:

Contractual agreement

The parties expressly agree to use a particular mechanism.

Concerted practice

The parties coordinate their market behaviour without necessarily having a traditional written contract.

Unilateral algorithmic behaviour

A company independently programs its system without communicating or coordinating with competitors.

The third category is not automatically unlawful merely because an algorithm produces parallel prices.

Therefore, algorithmic price similarity alone should not be equated automatically with cartelisation.

The legal inquiry must establish the relevant elements of concerted conduct.

5. Important Competition-Law Risks

5.1 Automated Price Fixing

The most obvious risk is using software to maintain agreed prices.

Example:

Competitor A and Competitor B agree that neither will sell below ₹1,000. Their smart contracts automatically reject transactions below ₹1,000.

The automated execution mechanism strengthens the evidence of implementation but does not itself create the unlawful agreement.

5.2 Algorithmic Market Allocation

A smart contract could automatically allocate customers between competitors:

• Customer group A → Firm X
• Customer group B → Firm Y
• Geographic territory A → Firm X
• Geographic territory B → Firm Y

Such arrangements may amount to market or customer allocation.

5.3 Automated Output Restrictions

Competitors might program systems to:

• restrict production;
• limit available inventory;
• automatically withdraw supply;
• impose capacity ceilings.

The fact that production restrictions are technically executed by code would not immunize the underlying coordination.

5.4 Automated Bid Coordination

Self-executing systems could theoretically determine:

• which participant submits a winning bid;
• minimum bid levels;
• allocation of contracts;
• rotation of winning suppliers.

This creates obvious cartel and bid-rigging concerns.

5.5 Automated Information Exchange

A smart-contract ecosystem can continuously exchange:

• prices;
• inventory;
• production capacity;
• demand forecasts;
• customer information;
• future pricing intentions.

The competitive significance depends heavily on:

• who receives the information;
• whether competitors obtain it;
• its sensitivity;
• frequency;
• degree of aggregation;
• purpose;
• market structure.

6. At Least Six Important Case Laws

Case 1: United States v. Topkins (2015)

This is one of the most directly relevant authorities for automated commercial arrangements.

The DOJ prosecuted an online-marketplace price-fixing conspiracy involving sellers of posters on Amazon Marketplace. The conspirators agreed on pricing and implemented the arrangement through pricing algorithms.

The government explained that the algorithms were programmed to coordinate prices and that the conspiracy became largely self-executing once the algorithms were operational.

Principle

Computer code does not transform an anticompetitive agreement into independent competitive conduct.

Importance

This case provides a powerful analogy for smart contracts:

Human agreement + automated execution = potentially automated implementation of a cartel.

Case 2: Eturas UAB and Others v Lietuvos Respublikos konkurencijos taryba, Case C-74/14

The CJEU dealt with travel agencies using a common computerized booking system.

The system administrator sent a communication concerning restrictions on discounts, and the system automatically limited the discounts available to participating travel agencies. The Court considered whether the circumstances could constitute a concerted practice under EU competition law.

Principle

A common technological system can be relevant evidence of coordination between competitors.

Importantly, the case illustrates that the operation of a common computerized system can become part of the evidentiary framework for establishing concerted conduct.

Application to smart contracts

If competitors use a common smart-contract infrastructure to implement commercially restrictive rules, investigators can examine:

• communications;
• participation;
• awareness;
• system operation;
• transactions;
• code;
• economic effects.

Case 3: AC-Treuhand AG v European Commission, Case C-194/14 P

In AC-Treuhand, a consultancy firm that was not itself operating in the relevant product markets helped organize and facilitate cartel activities.

The CJEU upheld the application of EU competition rules to the facilitator.

Principle

An undertaking does not necessarily escape Article 101 liability merely because it is not itself competing in the market affected by the cartel.

Importance for self-executing agreements

This principle has considerable relevance to:

• blockchain developers;
• algorithm providers;
• smart-contract operators;
• centralized platforms;
• data intermediaries;
• automated pricing providers.

If an intermediary knowingly facilitates anticompetitive coordination, its role may become legally significant.

The precise liability of a technology provider would, however, depend on the facts and applicable jurisdiction.

Case 4: Groupement des cartes bancaires (CB) v European Commission, Case C-67/13 P

This case concerned pricing mechanisms within a payment-card system.

The CJEU emphasized that a restriction can be characterized as a restriction “by object” only where the coordination reveals a sufficient degree of harm to competition. The assessment requires consideration of the content, objectives, and economic and legal context.

Importance

Self-executing commercial mechanisms may contain highly sophisticated formulas.

The fact that a formula automatically produces a particular result does not automatically establish a restriction by object.

Authorities must still examine:

• what the mechanism actually does;
• its objective;
• market context;
• economic structure;
• network effects;
• competitive consequences.

This is particularly important for automated systems because apparently technical formulas can have significant competitive consequences.

Case 5: Fleer Corp. v Topps Chewing Gum, Inc.

The litigation concerning Topps involved exclusive licensing arrangements for baseball-player images and their cumulative effect on competition in baseball trading cards.

The court examined interconnected agreements and their effect on market foreclosure.

Relevance

Although this is not a blockchain case, it demonstrates an important principle:

Several individually structured contractual arrangements may need to be examined collectively when assessing their competitive effect.

This is particularly relevant to automated commercial ecosystems.

For example:

• Agreement A controls access;
• Agreement B controls pricing;
• Agreement C controls data;
• smart contract D automatically enforces all three.

The analysis should not necessarily stop at the formal separation of the agreements.

Case 6: Cornish-Adebiyi v Caesars Entertainment

This is a significant modern U.S. development involving algorithmic pricing.

The FTC and DOJ filed a statement of interest concerning alleged algorithmic price fixing in hotel-room pricing. The agencies emphasized that competitors cannot lawfully coordinate prices merely because the coordination occurs through an algorithm rather than through direct human communication.

The agencies also explained that competitors may face Section 1 issues where they jointly delegate important pricing decisions to a common algorithm.

Principle

Delegating competitive decision-making to software does not necessarily eliminate concerted-action concerns.

Relevance

This is especially important for:

• smart contracts;
• AI pricing systems;
• automated revenue management;
• autonomous bidding systems;
• blockchain-based marketplaces.

Case 7: In re RealPage, Inc. Rental Software Antitrust Litigation

RealPage provides another important modern example.

The U.S. DOJ alleged that competing landlords supplied non-public, competitively sensitive information to RealPage and used its pricing software to generate rental-price recommendations. The government alleged violations of Sections 1 and 2 of the Sherman Act.

The U.S. government has specifically argued that competitors can engage in concerted action by jointly delegating important aspects of decision-making to a common algorithm.

Importance

This illustrates a broader principle:

Competition law can focus on the delegation of strategic decisions to a common technological mechanism rather than on traditional face-to-face cartel communications.

The RealPage proceedings are particularly useful for understanding the developing law of algorithmic coordination.

7. Self-Executing Agreements and Article 101 TFEU

Under Article 101 TFEU, three broad categories are important:

A. Agreements

A smart contract can constitute the technological implementation of an underlying agreement.

B. Decisions of associations of undertakings

An industry platform or association could potentially establish standardized automated rules.

C. Concerted practices

Coordinated conduct may exist even without a traditional contractual document.

Therefore:

Digital execution ≠ exemption from Article 101.

The Commission expressly identifies agreements between independent market operators that restrict competition as falling within Article 101.

8. Self-Executing Agreements and Article 102 TFEU

Article 102 becomes particularly important when a dominant platform controls the smart-contract infrastructure.

Potential abuses include:

1. Self-preferencing

The dominant platform automatically prioritizes its own products.

2. Exclusionary conditions

The smart contract automatically prevents competitors from accessing customers.

3. Discriminatory access

Different competitors receive automatically different contractual terms.

4. Loyalty restrictions

The code automatically penalizes customers or suppliers who deal with competing platforms.

5. Interoperability restrictions

APIs or smart contracts prevent competitors from connecting to the infrastructure.

6. Refusal of access

A dominant infrastructure provider automatically rejects transactions from rival systems.

The legal analysis would depend upon dominance, market definition, effects, objective justification, and the particular form of conduct.

9. Smart Contracts and Blockchain

Smart contracts create additional competition-law issues because blockchain systems may make transactions:

• transparent;
• immutable;
• automatically executed;
• pseudonymous;
• difficult to reverse;
• continuously observable.

Potential advantages

Self-execution can:

• reduce transaction costs;
• reduce opportunistic behaviour;
• increase transparency;
• improve contract enforcement;
• reduce intermediary costs;
• facilitate market entry.

These can produce genuine pro-competitive benefits.

Potential risks

The same characteristics can:

• make coordination easier;
• facilitate monitoring of rivals;
• stabilize cartel prices;
• automatically punish deviation;
• make collusive arrangements more durable.

Thus, the technology is competition-neutral; its legal significance depends on how it is designed and used.

10. The Problem of “Code Is Law”

One common misconception is:

“The code automatically executes, therefore the code itself is merely technical and cannot constitute an antitrust violation.”

This is incorrect as a general proposition.

Competition law generally focuses on economic conduct and coordination, not merely the physical mechanism through which the conduct occurs.

The distinction is:

Lawful

Independent competitors independently program their systems to respond to market conditions.

Potentially unlawful

Competitors agree that their systems will follow the same artificially restrictive pricing rule.

Higher-risk structure

Competitors collectively delegate pricing decisions to a common algorithm that uses their commercially sensitive information.

11. Intentional Versus Autonomous Algorithmic Collusion

A useful distinction is:

12. Evidence in Self-Executing Agreement Cases

Traditional evidence may be supplemented by technological evidence.

Traditional evidence

• emails;
• WhatsApp messages;
• meeting records;
• contracts;
• board minutes;
• witness testimony.

Digital evidence

• source code;
• smart-contract bytecode;
• blockchain transactions;
• wallet addresses;
• deployment records;
• API logs;
• algorithmic outputs;
• version histories;
• Git repositories;
• database records;
• system-access logs.

Economic evidence

• parallel pricing;
• abnormal price stability;
• reduced price dispersion;
• synchronized price changes;
• reduced output;
• market allocation;
• unusual margins.

The Eturas decision is particularly useful because it demonstrates how the operation of a common computerized system can interact with traditional evidence when authorities assess concerted practices.

13. Liability of Developers and Technology Providers

A difficult issue is whether the developer of the smart contract can be liable.

A distinction should be drawn between:

Neutral technology provider

Develops general-purpose software without knowledge of an unlawful arrangement.

Customized facilitator

Designs the system specifically to implement competitors' anticompetitive agreement.

Active facilitator

Participates in:

• coordinating competitors;
• collecting sensitive information;
• designing cartel rules;
• monitoring compliance;
• enforcing deviations.

The AC-Treuhand judgment is relevant because EU competition law can reach a facilitator that contributes to cartel implementation even though it does not itself operate in the affected product market.

14. Self-Executing Agreements and Vertical Restraints

Not every automated restriction involves competitors.

For example:

Manufacturer → Distributor → Retailer

A manufacturer could automatically:

• restrict resale prices;
• restrict territories;
• restrict customers;
• impose parity requirements;
• withdraw rebates;
• terminate access.

These arrangements may raise vertical-restraint questions.

The legality depends upon:

• market power;
• nature of the restriction;
• duration;
• foreclosure;
• efficiency justification;
• applicable block exemptions;
• jurisdiction.

Therefore, smart-contract automation does not eliminate the distinction between horizontal and vertical restraints.

15. Efficiency and Pro-Competitive Justifications

Self-executing agreements can generate legitimate efficiencies.

Examples include:

Lower transaction costs

Automatic settlement reduces administrative expenses.

Faster payments

Blockchain settlement can eliminate unnecessary intermediaries.

Reduced fraud

Predefined execution conditions can reduce opportunistic behaviour.

Better supply-chain coordination

Automated ordering can reduce inventory costs.

Interoperability

Standardized smart contracts can allow smaller firms to participate in a market.

Increased market transparency

Publicly verifiable transactions may reduce information asymmetry.

However, an efficiency claim does not automatically validate an otherwise restrictive arrangement.

The legal analysis must consider the applicable competition-law framework and whether the claimed efficiency benefits are real, relevant, and sufficiently connected to the restrictive conduct.

16. Key Compliance Principles

Businesses using self-executing commercial agreements should adopt the following safeguards.

1. Competition-law review before deployment

The code should be reviewed before implementation.

2. Independent pricing decisions

Competitors should not delegate strategic pricing decisions to a common system without appropriate legal analysis.

3. Limit competitively sensitive information

Avoid unnecessary sharing of:

• future prices;
• discounts;
• output;
• costs;
• customer information;
• strategic plans.

4. Audit the code

Maintain records of:

• who wrote the code;
• who approved it;
• changes made;
• deployment dates;
• decision-making process.

5. Human override mechanisms

Where commercially appropriate, maintain the ability to suspend or modify problematic automated conduct.

6. Competition-law testing

Test whether the automated mechanism could:

• fix prices;
• allocate markets;
• exclude rivals;
• discriminate between competitors;
• restrict output;
• facilitate information exchange.

7. Monitor third-party algorithm providers

Companies should understand whether a common provider is receiving and processing competitors' sensitive information.

17. A Practical Legal Test

A useful analytical framework is:

Step 1 — Identify the agreement

What exactly did the parties agree to?

↓

Step 2 — Identify the technology

Is execution performed through:

• smart contract;
• algorithm;
• API;
• blockchain;
• automated pricing system?

↓

Step 3 — Identify the competitive parameter

Does the mechanism affect:

• price;
• output;
• customers;
• territory;
• supply;
• access;
• innovation?

↓

Step 4 — Identify coordination

Did independent undertakings coordinate their decisions?

↓

Step 5 — Examine object

Does the arrangement reveal a sufficient degree of harm to competition?

The Cartes Bancaires judgment emphasizes that an alleged restriction by object must be assessed in light of the content, objectives, and economic and legal context rather than simply inferred from technical wording.

↓

Step 6 — Examine effects

If necessary, assess actual or likely effects on:

• prices;
• output;
• quality;
• innovation;
• entry;
• consumer choice.

↓

Step 7 — Assess market power

Particularly for unilateral or platform conduct.

↓

Step 8 — Consider efficiencies

Determine whether legitimate efficiencies exist.

↓

Step 9 — Identify responsible actors

Consider:

• contracting parties;
• platform;
• algorithm provider;
• developer;
• intermediary;
• association.

↓

Step 10 — Examine remedies

Possible responses may include:

• termination;
• modification of code;
• access remedies;
• information restrictions;
• compliance monitoring;
• fines;
• damages;
• injunctions.

18. Relationship Between the Six Core Cases and Self-Executing Agreements

The Topkins, Eturas, AC-Treuhand, Cartes Bancaires, Cornish-Adebiyi, and RealPage authorities together demonstrate that competition law increasingly examines the economic substance and technological architecture of coordination rather than requiring traditional paper agreements or direct human price negotiations.

19. Conclusion

Self-executing commercial agreements are not inherently anti-competitive. They can substantially improve commercial efficiency by automating payment, settlement, supply-chain management, compliance and other contractual processes.

The competition-law difficulty arises when automation becomes the mechanism through which independent businesses coordinate competitive behaviour.

The central principle is therefore:

Automation changes the method of execution, not necessarily the legal character of the underlying conduct.

A price-fixing agreement does not cease to be price fixing merely because software implements it. Similarly, a legitimate commercial arrangement does not become unlawful merely because it is automated.

The most important issues for modern antitrust analysis are therefore:

1. Who designed the automated mechanism?
2. Who agreed to use it?
3. What competitive decisions were delegated to it?
4. What information does it receive?
5. Does it coordinate independent competitors?
6. Does it restrict price, output, customers, access or innovation?
7. Does a dominant undertaking control the mechanism?
8. Are there legitimate efficiencies?
9. Can the mechanism facilitate monitoring or punishment of deviation?
10. Can competition authorities reconstruct the arrangement from code and digital records?