Using technology-assisted review to uncover suspicious transactions

A global corporation with operations in Latin America, West Africa and Eastern Europe was being investigated by the U.S. Department of Justice (DOJ) for alleged violations under the Foreign Corrupt Practices Act (FCPA). In coordination with outside counsel and its forensic accounting service provider, the corporation applied technology-assisted review (TAR) techniques to payment transactions, reducing the DOJ’s $30 million in bribery and corruption allegations to less than $8 million and allowing them to settle the case out of court. Did I get your attention?

In this column I’ll describe a fictionalized version of that actual case, where TAR was indeed used as a defense strategy on a real governmental investigation (I’ve changed the numbers and details). The DOJ alleged the company was making improper payments in the form of bribes to government officials, including customs agents, via the use of multiple third-party vendors. The DOJ asserted that more than two dozen vendors had made over $30 million in alleged bribes and it was up to the company to prove them wrong.

For the sake of calculating costs, assume it takes 30 minutes, on average, to manually trace and review each of the 75,000 invoices that make up the $30 million in alleged bribes from among two dozen vendors. That’s 37,500 hours for attorneys and forensic accountants, at an average $400 per hour professional rate (volume discounted, of course), to manually review these invoices — resulting in a whopping $15 million cost to the company. Given the high-stakes nature of the case, potential reputational damage, and potential fines and/or monitorship facing the company, its board of directors actually agreed, albeit hesitantly, to pay the $15 million. But wait! Along came the forensic data analytics heroes and CFEs to the rescue, with a pitch to the company: What if we used TAR, a concept often used in e-discovery and document review, to efficiently and cost-effectively train a model to statistically predict the likelihood of a potential improper payment?

The Sedona Conference, a nonprofit research and educational institute dedicated to the advanced study of law and policy in the areas of antitrust law, complex litigation, intellectual property rights, data security and privacy, defines e-discovery as: “The process of identifying, locating, preserving, collecting, preparing, reviewing, and producing electronically stored information (ESI) in the context of the legal process.” (See “The Perfect Elevator Pitch for What We Do is Elusive: eDiscovery Trends,” by Doug Austin, eDiscovery Today, March 14, 2022.)