11 days 15 hrs 14 min
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Strategies for Handling Data in U.S. Antitrust Merger Reviews

Strategies for Handling Data in U.S. Antitrust Merger Reviews

Strategies for Handling Data in US Antitrust Merger Reviews_675

This one-hour CLE program discusses best practices for handling data in US Second Requests issued by the DOJ and FTC. The program covers the following areas:

  • Forensics – focus on emerging data sources and the impact of hybrid work environments, as well as responding effectively to the Government’s forensics questionnaire, the importance of timing in the process.
  • Data Processing – understanding and complying with the detailed requirements of the regulators’ ESI protocols, handling specific data types, and managing foreign language components.
  • Technology Assisted Review (TAR)/Artificial Intelligence (AI) – understanding the regulators’ approaches to TAR and AI, standard workflows, counsel’s involvement in the training process, and reporting requirements.
  • Document Review – strategies for handling the review component efficiently and cost-effectively, complying with the regulators’ requirements around the treatment of privileged documents, deploying AI tools to streamline the process.
  • Post-Production/Advocacy Support – strategies for managing data post-compliance, for client depositions/hearings and possible litigation challenges.  

Speakers

Devon Avallone-Graves, Esq., Senior Forensics Project Manager, Antitrust & Global Investigations

Brett Beeman, Senior Director, Advanced Technologies, Antitrust & Global Investigations

Edward Burke, Esq., Managing Director, Antitrust & Global Investigations Practice Group

Jason Butler, Esq., Senior Director, Antitrust & Global Investigations, Document Review

Brett Irizarry, Senior Director, Client Services, Antitrust & Global Investigations

Erin Toomey, Vice-President and Managing Director, Global Investigations Practice Group Leader

Published Date:
  • April 23, 2025
Format:
  • Online On-Demand
Product Code:
  • VPX64
Skills Credit(s):
  • 1.0
Total Credit(s):
  • 1.0