Merger Investigations: The Benefits of Technology-Assisted Document Review in 2016
Technology Assisted Review (TAR) is a relatively new form of investigative litigation in which a subset of documents are reviewed by attorneys and marked for relevance. Then, specialized software is used to apply the review decisions from the subset of documents to all remaining unreviewed documents. In supervised learning TAR (SLTAR), a type of predictive coding, the software simply identifies similar documents coded as 'relevant'. In active learning TAR (ALTAR), also predictive, a subset of documents is chosen by attorneys and the computer returns samples of potential relevance. Finally, in knowledge engineering TAR (KETAR), software attempts to replicate how an attorney thinks about complex problems and then creates a statistically generated 'decision tree' using artificial intelligence algorithms to determine relevance.
According to a representative of the US DOJ Antitrust Division, they expect that use of TAR in merger and acquisition litigation will increase. Recent research has shown that TAR produces results that are at least comparable to manual review, with ALTAR and KETAR demonstrating 10 percent greater accuracy. However, such predictive coding used to determine relevancy is only as good as the algorithms used and the ability of initial reviewers. Worryingly for the scientifically minded, there is limited robust statistical data on effectiveness, accuracy, and precision.
The Knowledge Group has assembled a panel of key thought leaders to provide the audience with an in-depth review and discussion of Technology-Assisted Document Review (TAR) in Merger Investigations. Speakers will explain the benefits of adopting TAR and its implications for merging parties. The panel also will provide the audience with best practices to avoid common pitfalls and risks in using TAR for merger investigations.
Key topics include:
- Merger Investigations – An Overview
- Technology-Assisted Document Review (TAR)
- TAR in Merger Litigation - Benefits and Implications
- Risks and Pitfalls of using TAR
- Traditional Review vs. TAR
- TAR Requirements, Costs, and Complications
- Statistical Robustness
- Regulatory Updates
- Common types of TAR tools
- Text-based grouping (email threads and near duplicates)
- Content-based grouping (conceptual clusters and categorization)
- Predictive coding (active machine learning, continuous active learning, sample-based learning)
- And their applicability to general scenarios
- Speeding up a brute force review while boosting accuracy and consistency
- Hunting for key documents (known, suspected, or imaginary)
- Exploring an unknown dataset
- Leveraging predictive coding to cull/classify a large, unseen dataset
- Hybrid approaches - layering technologies to compound efficiency/consistency gains
Murphy & McGonigle, PC
- Application of TAR in FTC Anti-Competition Investigations
- Early Data Assessment – Evaluating:
- Search Terms
- Data Sources
- Responding to a Second Request
- Predictive Coding
- Early Data Assessment – Evaluating:
- Application of TAR in Due Diligence Investigations
- Strategies When Time is Short
- Scoping for Known and Unknown Issues
Who Should Attend:
- Legal Counsel
- IT Heads
- Executive Board Members
- Data Security Officers
- Merger & Acquisition Specialists
- Multi-National Companies
- Public and Private Companies
- Other Related/Interested Professionals and Organization
With a background in computer science that includes database design and interface programming, Tobin brings a unique mastery of both the technical and legal aspects of eDiscovery. After receiving his undergraduate degree in computer science, he began his career in public policy which led him to pursue a law degree. In 2008, he focused his career on e-discovery, overseeing dozens of projects for AmLaw 100 law firms, including a 9-month engagement leading a specialized search and analysis team for one of the largest global manufacturers of consumer electronics in a patent dispute. He developed expertise in managing e-discovery and document review workflows and was an early adopter of predictive coding technologies. He has successfully guided numerous clients through the predictive coding process, coaching them through a variety of workflows to achieve the best results for their projects. Tobin holds the Equivio Technical STAR certification and has led CLEs and seminars on predictive coding use cases and best practices. Tobin is a member of the California and District of Columbia Bar Associations.
With a background in computer science that includes database design and interface programming, Tobin brings a unique mastery of both …
Mr. Naylor is an officer and heads the firm’s Strategic Discovery and Information Management practice. He advises clients on issues related to e-discovery, including the preservation, collection, analysis, and production of electronically-stored information in actions ranging from complex litigation to governmental regulatory investigations and requests for information. His practice includes administration of the firm’s document review center, which provides clients with strategic and cost-effective solutions for the analysis and production of documents and electronically-stored information.
Prior to joining Murphy & McGonigle, Mr. Naylor defended Fortune 100 corporations in toxic tort litigation, including the collection, analysis, and production of voluminous documents and electronically-stored information attendant to the subject litigations. He also received the E. Randolph Williams pro bono award four years in a row for his representation of victims of domestic violence in custody and visitation matters. He also has been recognized as a Virginia Rising Star in e-discovery (2015).
Mr. Naylor received his LL.M in Taxation from the University of Denver, his J.D/M.B.A from Samford and his B.A. in Economics from Hampden-Sydney College.
Mr. Naylor is an officer and heads the firm’s Strategic Discovery and Information Management practice. He advises clients on issues …
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NASBA Field of Study:
Specialized Knowledge and Applications
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Discovia provides electronic discovery services to corporations and law firms engaged in litigation, ITC investigations, and internal and regulatory investigations, including HSR Second Requests. Services include onsite and remote data collections, data minimization, data processing and hosting, expert application of leading technology-assisted review tools, document review management, and document productions. Discovia is one of the only eDiscovery services providers to achieve ISO 27001 certification and HIPAA/HITECH compliance for data security according to third-party auditors. Discovia is the first to publish its accuracy rate – 99.7 percent, and typically achieves data culling rates of 95 percent for repeat clients. Discovia is the first eDiscovery services firm to deliver a fixed-price managed services solution, enabling corporate legal departments and law firms to gain a world-class eDiscovery function with complete cost predictability. More information is available at 415-392-2900 or www.discovia.com.
About Murphy & McGonigle, PC
Murphy & McGonigle serves the litigation, enforcement defense, and regulatory counseling needs of clients across the full spectrum of the financial services industry – from national banks, broker-dealers, investment advisers, and hedge funds, to national and international securities markets and exchanges. Many of the firm’s partners formerly served in senior positions at the U.S. Department of Justice, SEC, FINRA, and CFTC and several served in senior executive positions in major financial institutions on Wall Street.
Murphy & McGonigle, founded in 2010, was created based on an innovative law firm model that rigorously controls overhead while providing its attorneys and clients with state-of-the-art technology and litigation support to ensure both world-class service and maximum cost-efficiency.
Murphy & McGonigle operates out of offices in New York, Washington, D.C., and Richmond, Virginia.
For more information about the firm, please visit www.mmlawus.com.