Insights From The Inevitable: When The Odds Are Against You: Antitrust Merger Review

Insights From The Inevitable: When The Odds Are Against You: Antitrust Merger Review

On August 27th, as part of our The Inevitable 2020 Series, Text IQ co-founder Omar Haroun sat down with Dentons’ Ausra Deluard to get her insights on the use of cutting-edge technologies like predictive coding and artificial intelligence (AI) to efficiently and cost-effectively manage HSR Second Request reviews.

A member of Dentons’ national Health Care practice group, Ausra Deluard is highly experienced in high-stakes antitrust litigations and investigations within the context of M&A in highly-regulated consumer industries. Ausra has handled numerous DOJ and FTC Second Requests for clients in the cannabis, tobacco, healthcare, and tech sectors.

A Burdensome and Costly Subpoena

“Setting aside substantive advocacy, when you're talking about just the technical process of producing the documents and data that is necessary in responding to the interrogatories: the starting price for a second request... seven figures.”

M&A antitrust investigations are focused on large mergers that can impact markets and potentially harm consumers by reducing competition. Under Hart-Scott-Rodino (1976), the FTC and DOJ can review the transaction to determine if it violates antitrust law. This requires a comprehensive production of documents (potentially tens of millions) and that must be completed in 30 to 60 days.

“While there have been efforts by the agencies to try to reduce the burden of second request, unfortunately, the proliferation of emails and text messages, and...the data that we keep...have contributed to an incredible increase in the burden that parties face when responding to second request.”

 

Reducing the Burden, Risk, and Cost

Predictive Coding, widely used in litigation document reviews, is particularly effective in second request because of the broad nature of the categories of responsiveness. The problem though is that predictive coding isn't a good solution for privilege, says Deluard:

“I've tried, I've tried, to use predictive coding [for] privilege, but privilege isn't necessarily captured just by the content that's within the four corners of the document...what drives privilege, primarily, is the relationships of the people and the roles that those people play in an organization.”

Using technology like Text IQ for privilege review has reduced our risk because we've been able to identify documents that we otherwise would not have captured, notes Deluard. She elucidates a core challenge with privilege that not only cannot be managed with current predictive coding techniques, but is also missed with the traditional “eyes on paper” reviewer:

“We had our initial attorney's names look list, our initial case assessment. We had no idea that that project name was something that was highly privileged. We had no idea that a businessperson was someone who is integrally involved in privileged communications [and] that that businessperson was then forwarding on legal communications that otherwise didn't have any indication of privilege...

The Text IQ analysis is a very different analysis because it's much more focused on the relationships between all of the different recipients and the documents. It's not just identifying what's potentially privileged, but it's also, helping to automate and quickly be able to QC a privilege log.

Another “increasing pain point” is the need to redact sensitive information like personally identifiable information (PII) and information subject to HIPPA protections, protected health information (PHI), and identify sensitive information.

“Being able to quickly identify [sensitive information] in a way that search terms aren't very efficient at doing really gives us a leg up. So while we're doing the predictive coding process, I’ll run it through Text IQ, to be able to really quickly identify what is potentially privileged, and what has PII in it. And then also, you know, what might be sensitive, right?

So what are the documents that we need to start looking at because that might dictate some of our case strategy. So the Text IQ process gave me that insight into the documents that I need to focus my attention on.”

Ausra provides a wealth of insight and fresh perspective of the interplay – and interdependencies – among attorneys and technology that deserves a listen. Her expert deployment of technologies purpose-fit to the challenges of HSR Second Requests puts her at the forefront of her field and serves her clients exceptionally well.

"When I was sworn in, as an attorney, I took an oath to take on the cares and concerns of my clients as my own. So when I was confronted with the traditional way of doing a second request, and...saw the total cost of that, I realized that just could not be the way...”

You will find the full discussion here and The Inevitable 2020 Series lineup here.

Find more information on how AI can transform HSR Second Request Compliance here