Computational Antitrust Worldwide: Fourth Cross-Agency Report

Abstract

This fourth-annual report distils insights from 25 antitrust agencies and shows a shared, global move toward data-centered enforcement. Agencies highlight three converging priorities: first, the deployment of AI and advanced analytics that range from bid-rigging screens to graph neural networks to detect cartels, merger risks and other infringements; second, investment in robust data infrastructure such as web-scrape pipelines, procurement databases and secure e-discovery systems that convert vast public and corporate datasets into reliable evidence; and third, deep institutional change led by new digital units, open-source collaborations and practitioner toolkits that embed computational methods in everyday competition policy. Three key challenges stand out: the necessity of secure cloud computing, the need to ensure the explainability of deployed computational tools, and the imperative to improve human-machine interaction.

Details

Author(s):
Publish Date:
June 18, 2025
Publisher:
Stanford Computational Antitrust Project
Format:
Report
Citation(s):
  • Schrepel, Thibault and Groza, Teodora, Computational Antitrust Worldwide: Fourth Cross-Agency Report (June 18, 2025). Available at SSRN: https://ssrn.com/abstract=5305055 or http://dx.doi.org/10.2139/ssrn.5305055
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