Feds Using Data Analytics to Turbocharge Insider Trading Enforcement

The U.S. Department of Justice (DOJ) and Securities and Exchange Commission (SEC) have three words for executives tempted to trade on inside information and make a quick buck in the stock market: “We’re watching you.”

Federal securities enforcement officials are using data analytics to streamline their insider trading investigations, helping them bring cases faster and with more precision than ever before.

Speaking late last month at Securities Enforcement Forum West near Stanford University, the SEC’s Rahul Kolhatkar said the agency’s ability to more quickly identify aberrant trading helped lead to the successful prosecution late last year of Brazilian national Romero Cabral Da Costa Neto.

The DOJ and SEC said Neto got wind that one of the firm’s biopharma clients was going to be acquired and traded on that information before the merger announcement in late May 2023. He was charged in August, pleaded guilty in November, and was sentenced to two months in federal prison in December.

“This action was brought maybe three months after the trading at issue, and that’s simply not possible without data analytics identifying the issue,” said Kolhatkar, an assistant regional director for the SEC’s Division of Enforcement.

Analytics also allowed the SEC to pull off the feat of charging 13 defendants in four separate insider trading schemes in one day.

One of those cases involved former Pfizer employee Amit Dagar, who got caught trading in advance of the 2021 announcement of positive clinical results for the company’s Covid-19 drug Paxlovid. The good news caused Pfizer shares to shoot up nearly 11 percent, the biggest percentage gain since 2009. In January, a jury convicted Dagar of securities fraud and conspiracy to commit securities fraud. He is scheduled for sentencing next month.

Dagar also had tipped off a friend and business partner, and together they made more than $274,000 in illegal profits, authorities said. Kolhatkar said the pair purchased short-term, out-of-the-money call options, “which is sort of a telltale sign that there was potentially riskier trading.”

That data analytics can yield promising investigative leads is especially valuable given the fact-specific and resource-intensive nature of insider trading investigations. “We’re trying to select the best cases that are going to have the highest impact and have a big deterrent impact,” Benjamin Kingsley, chief of the Oakland, California, branch of the U.S. Attorney’s Office, said at Securities Enforcement Forum West.

“Obviously, the vast majority of things that are going to be identified through data analytics are not going to be a criminal case, and many of them probably aren’t going to be an SEC case because there are lots of reasons data can show things. But it’s going to give us a broader field of cases to work from,” Kingsley said.

He said the analytics push also signals to the marketplace that “we’re watching you. And while we can’t prosecute every single case, there is going to be a broad set of information that’s flowing into the SEC, that’s flowing into Main Justice and going to the U.S. attorney’s offices, and we’re looking for cases that are really egregious and are worth putting in our resources.”

Data analytics also helped the DOJ last year bring its first-ever criminal case over 10b5-1 trading plans. Such plans allow executives to schedule trades in advance, including during periods when blackout periods would otherwise bar insider sales.

Authorities allege that Terren Peizer, chairman and former CEO of healthcare company Ontrak, dumped more than $20 million in company stock between May 2021 and August 2021 based on inside knowledge that it was about to lose a contract with Cigna. Text messages reveal that Peizer knew that the relationship with Cigna was deteriorating and that the insurer was planning to terminate its contract with Ontrak. Peizer, who faces securities fraud and insider trading charges, denies wrongdoing. His trial in Los Angeles federal court is scheduled to start Tuesday.

Just as data analytics can help enforcers detect insider trading, it can also help companies and their employees avoid trouble, said Shannon Eagan, partner in charge and head of the business litigation practice for Cooley’s Palo Alto office. Eagan, who also spoke on the panel, said that white-collar defense lawyers should be making sure their clients “understand that there are very powerful tools out there that the government is using, and they’re clearly going to get better and better.” Companies should also be using their own data analytics “to suss out anything that’s wrong.”

Another panelist, Christopher Frey, former head of the Justice Department’s Criminal Division, said the recent raft of insider trading cases presents a teaching opportunity for compliance personnel “to instill fear and obedience” in employees and executives.

“The government’s efficiency and precision in bringing these cases is just increasing,” he said. “It’s just incredibly important to be extra vigilant.”

From: Corporate Counsel