by Jay Leib on November 15, 2013
In this installment of his interview series, Jay Leib—one of our resident computer-assisted review experts at Relativity—interviews Nigel Tabaee of Deloitte Financial Advisory Services LLP’s Discovery practice about the use of computer-assisted review in investigations. Nigel is a senior manager at Deloitte and a member of their national discovery standards committee.
Jay: Can you describe your role at Deloitte?
Nigel: I’m a senior manager in our discovery practice, focused on helping our clients develop document review workflows, which incorporate early data assessments, analytics, and advanced reporting. As a member of our national discovery standards committee, I also help develop leading practices for the Deloitte U.S. firms.
How does Deloitte’s deep history in accounting interplay with Deloitte Discovery? Are you ever brought in for fraud investigation?
Yes. Many of our service lines work together, so we’re often asked to assist not only with fraud matters, but also with many of Deloitte’s other service lines, such as anti-money laundering, FCPA (Foreign Corrupt Practices Act), or transactional investigations. Our computer forensic team can assist our forensic accounting team with collections, for example, where our forensic accounting team is assisting clients with an investigation. In those cases, we’re there to help our forensic accounting team navigate through the data, clean and normalize it, and allow them to perform their functions effectively.
When we’re asked to assist with an FCPA matter, the forensic accounting team and client will leverage our experience and global reach to help identify where the data is, collect it, and get it ready for investigation. It may be a transactional analysis or an account analysis—whatever the case, we can usually help facilitate the job at hand.
From an e-discovery perspective, what would be the difference between an investigation and civil litigation?
Investigations, as opposed to civil litigations, are often exploratory with limited budgets, but could be very time sensitive. Understanding the matter and the data set—for instance, identifying foreign languages, atypical file types, etc.—and conducting interviews are typically very beneficial for a more tactical and targeted collection and review strategy, with the goal of identifying and promoting high-value records as efficiently as possible.
To that end, we help determine what types of analytics—such as clustering or Relativity Assisted Review—may be beneficial to help our clients get a better understanding of the data set to make strategic decisions.
With the compressed time frame and the need to keep budgets low, investigations sound like a good fit for Assisted Review and other Relativity Analytics workflows. Is that correct?
Yes. Often Assisted Review and Relativity Analytics can be very advantageous to an investigation. Analytics can help our clients both understand big data and assist with the identification of topics, clusters, and records that may not have been identified using the more traditional keyword approach.
While it may not be necessary to review entire populations during investigations, Assisted Review can be extremely helpful in prioritizing documents to review. Essentially, it can be used to explore relevance and find similar documents. Relativity Analytics also includes technologies such as near-duplicate detection and clustering, which can also be very helpful when leveraged appropriately during investigations.
While Analytics can provide a wealth of tools to assist with big data and large investigations, one shouldn’t forgo some of the more traditional metadata analysis used to determine communication, domain analysis, and even date examination. Often, the data contains high-value records that have no text, such as voicemails, or very limited text, such as text messages, that require both approaches. But, computer-assisted review is often times beneficial to help identify what isn’t known. If some documents are identified as very valuable to a case, these technologies can be used to identify similar or conceptually related documents.
As a practice at Deloitte, we often use some sort of analytics in almost every engagement. Even if the engagement involves utilizing keywords to identify a population or performing a very basic linear review, Analytics or Assisted Review can be utilized to prioritize or perform validation, such as near-duplicate checks. With cost pressure and these growing data populations, Assisted Review will often be required in some fashion to assist with identifying patterns and transactions, and, ultimately, with reviewing these populations.
Do clients often request the use of analytics and Assisted Review in your practice?
Yes. A lot of the features in the analytics umbrella may help us understand data and identify high-value documents, while others—like Assisted Review—typically foster a more conscientious and systematic review. At Deloitte, we’re very committed to using these types of technologies in many aspects—not only in investigations, but also with document review teams to help increase efficiency, as well as for quality control of productions. We’re seeing that Analytics can be useful for myriad reasons and circumstances, and we’re committed to taking advantage of those benefits in a wide variety of processes.
Posted by advice@kCura on November 15, 2013.
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