The Making of An Antitrust API: Proof of Concept

Research output: Contribution to JournalArticleAcademicpeer-review

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.
Original languageEnglish
JournalStanford Computational Antitrust
Early online date18 Oct 2022
Publication statusPublished - 28 Feb 2023

Bibliographical note

Cite as: Schrepel, Thibault, The Making of An Antitrust API: Proof of Concept (October 12, 2022). Stanford University CodeX Research Paper Series 2022 3 Stan. Computational Antitrust 22 (2023), Available at SSRN: https://ssrn.com/abstract=4241927

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