COVID-19, Data Analytics & The FCA: Big Response, Big Data, Big Risk

This article was co-authored by: Jim Dowden, Ryan Rohlfsen, Kendall Dacey, and Kendall Scott Cowles of Ropes & Gray in collaboration with Matt Bedan, Jen Baskin, Neil Goradia, and William Mui of Forensic Risk Alliance. Further information about FRA is available here.

Abstract

The U.S. federal government's record $2.2 trillion response to the Covid-19 crisis will inevitably bring with it heightened scrutiny from government and private watchdogs, and a corresponding wave of False Claims Act (FCA) enforcement. Litigation trends in the FCA space over the past decade indicate this wave of enforcement will be heavily data-driven, with whistleblowers and privately funded relators filing the large majority of lawsuits. These parties will rely heavily on advanced data mining and analytics techniques to spot potential indicators of fraud ("anomalous data") in publicly available data sets. Concurrently, the turmoil naturally caused by a public health crisis this widespread