The Making of An Antitrust API: Proof of Concept
Stanford University CodeX Research Paper Series 2022 3 Stan. Computational Antitrust 22 (2023)
14 Pages Posted: 18 Oct 2022 Last revised: 28 Feb 2023
Date Written: October 12, 2022
Abstract
Computational antitrust promises not only to help antitrust agencies preside over increasingly complex and dynamic markets but also to provide companies with the tools to assess and enforce their compliance with antitrust laws. If research in the space has been primarily dedicated to supporting antitrust agencies, this article fills the gap by offering an innovative solution for companies. Specifically, this article serves as a proof of concept whose aim is to guide antitrust agencies in creating a decision-trees based antitrust compliance API intended for market players. It includes an open-access prototype of the API, which automates compliance with Article 102 TFEU by providing companies with access to the legality tests behind the most common practices. Finally, the article discusses the API limitations and lessons learned.
Keywords: antitrust, computational antitrust, antitrust api, antitrust compliance, computational law, competition law, monopolization, dominance, abuses of dominance
JEL Classification: K21, L12, L22, L20, L40, L41, L44, L50, D11, D20, D85, K24, L10, K24, K20, K39, K30, K23, K29, K00
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