Big Data

Justice taps big data in investigations

Analytics_digital_graph 

In the last few days, top Justice Department officials have unveiled two task forces that rely on analyzing complex sets of big data to crack down on financial fraudsters and dark web drug dealers.

Both programs, said the officials, illustrate the increasing importance of the capability to sift through mountains of data to stop large-scale, secretive crimes that might otherwise be difficult to see.

On Jan. 29, Attorney General Jeff Session announced another portion of the department’s stepped-up effort to track down illicit opioid sales. Sessions said the Joint Criminal Opioid Darknet Enforcement (J-CODE) team would go after online “darknet” opioid dealers.

“Criminals think that they are safe on the darknet, but they are in for a rude awakening,” Sessions said in an announcement in front of the U.S. Courthouse in Pittsburgh. Agents from the FBI and Justice Department and intelligence analysts will work on the J-CODE team, he said, to further infiltrate secretive online opioid sellers.

Sessions told local reporters he chose Pittsburgh because the FBI’s office there has been “impressive” in combatting the deadly and cheap opioid fentanyl sold from the Internet’s dark shadows. “The J-CODE team will help us continue to shut down the online marketplaces that drug traffickers use and ultimately that will help us reduce addiction and overdoses across the nation,” he said.

J-CODE will more than double the FBI’s investment in fighting online opioid trafficking. Sessions said the FBI is dedicating dozens more special agents, intelligence analysts, and professional staff to J-CODE so that they can focus on this one issue.

The new J-Code team is likely to work alongside another team of big data analysts unveiled by the Justice Department a few months ago. The Opioid Fraud and Abuse Detection Unit, announced by Sessions last August, uses prescription data to identify and prosecute individuals who are contributing to the opioid crisis.

Last August Sessions said that team would sort through prescription data that physicians submit to the Drug Enforcement Agency on opioid subscriptions, to find tell-tale data points, such as physicians writing opioid prescriptions at rates that far exceeds their peers; how many of a doctor's patients died within 60 days of an opioid prescription; the average age of the patients receiving these prescriptions; pharmacies dispensing disproportionately large amounts of opioids; and regional hot spots for opioid issues.

Both teams will be keys to a 45-day crackdown on prescription drug diversion from pharmacies and prescribers that dispense “unusual or disproportionate amounts of drugs,” Sessions said.

DEA said it collects around 80 million transaction reports every year from manufacturers and distributors of prescription drugs. Sessions said the DEA will aggregate to find patterns, trends, statistical outliers—and put them into targeting packages.

In a separate announcement on Jan. 29, another top Justice Department official said agency investigators leveraged big data analytics to crack down on sprawling financial fraud activity.

Acting Assistant Attorney General John Cronan said in a statement that data analytics could be an equalizer in finding “identity spoofing” in an ocean of data from financial markets, and called this effort largest futures market criminal enforcement action in the criminal division’s history.

Cronan said DOJ's data analysis had led to charges against eight people in six different cases, across three federal districts. The charges concern alleged roles in manipulating futures markets for precious metals, as well as S&P 500, Dow Jones Industrial Average, and NASDAQ E-mini futures contracts.

In financial markets, “spoofing” is an illegal order for a futures contract that the trader never intended to be executed. Spoofed orders are mostly immediately cancelled–sometimes within seconds – and are never filled.

However, the action artificially stirs the market and spurs trade by other traders, skewing markets, according to the department. The trades are hidden by an ocean of other trades and can be hard to detect. New data capabilities, Cronan said, allowed the agency to winnow that data down and find the alleged manipulators "through sophisticated analysis of market-level data."

About the Author

Mark Rockwell is a senior staff writer at FCW, whose beat focuses on acquisition, the Department of Homeland Security and the Department of Energy.

Before joining FCW, Rockwell was Washington correspondent for Government Security News, where he covered all aspects of homeland security from IT to detection dogs and border security. Over the last 25 years in Washington as a reporter, editor and correspondent, he has covered an increasingly wide array of high-tech issues for publications like Communications Week, Internet Week, Fiber Optics News, tele.com magazine and Wireless Week.

Rockwell received a Jesse H. Neal Award for his work covering telecommunications issues, and is a graduate of James Madison University.

Click here for previous articles by Rockwell. Contact him at mrockwell@fcw.com or follow him on Twitter at @MRockwell4.


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