Artificial intelligence, machine learning, big data. It’s clear the issue today isn’t information – it’s how to process it most effectively. That is the conundrum facing the federal government as it looks to implement continuous evaluation of security clearance holders. CE is largely seen as the key to reducing the size of the security clearance backlog and improving security clearance process times. And in fact, we’ve already seen major gains in reducing security clearance costs and driving down the backlog – largely enabled through enrolling more security clearance holders due for periodic reinvestigations into the CE program.
But the issue the government faces is – how does it take all of the data available about its workforce (from credit reports to social media postings), and filter or analyze it in meaningful ways?
A new partnership between data and behavior science firm Giant Oak and consumer credit reporting agency TransUnion aims to help the federal government accomplish its personnel security screening mission more efficiently. The partnership enables the kind of continuous vetting process the government sees as crucial to a modern personnel security program. Dr. Gary Shiffman, founder and CEO of Giant Oak and Jonathan McDonald, executive vice president, public sector, TransUnion, recently spoke with ClearedCast about the partnership.
“We understand the growth and proliferation of data, the deluge of data,” said Shiffman. “As humans we’re overwhelmed by that amount of data. So in theory, data makes our jobs easier and it makes us more secure. But in practice, we mostly just get overwhelmed by data and machine-learning is kind of this new generation of technology which allows humans to take advantage of the amount of data in a way that’s human-friendly.”
While data can be an asset – without the right people analyzing it, it can be a liability.
“The mission is critical, the mission is vital and we believe very passionately in the importance of not only having this cadre of cleared and vetted individuals, but in having that system efficient and easy so that the most talented people are actually drawn to, and excited to work in positions of trust in the U.S. government,” said Shiffman. “In order to do that, we need to take advantage of all of the data that we have available. But we have to do that in a way that’s efficient.”
The first step is to access the data – and that’s where TransUnion comes in.
“We have over a billion people in our systems across both, financial and public records information,” said McDonald. “We can help the government prioritize who they look at in terms of who’s most likely to get through the clearance process quickly, so they can put those to the top of the list and quickly get through those.”
McDonald noted how data can be used to help the government streamline cases by quickly flagging which cases will take more investigative and adjudicative work. The system can also work to help clearance holders remove inaccurate records and information.
“The way I like to think about it is, what we’re doing is we’re measuring risk or we’re measuring the absence of risk,” said Shiffman. “If you think about it, most people in positions of trust are not risky. We just need some very efficient way to automate and continuously vet people in positions of trust for the absence of risk and also the measurement of risk.”
Saving Clearance Costs by Saving Investigator Time
In citing the cost benefits of CE, officials from the Defense Security Service frequently cite the benefits of reduced investigator time – every applicant they’re able to enroll in CE eliminates the need for a periodic reinvestigation.
“In my years of work in technology and security, the challenge is always that,” said Shiffman. “How do we look at more data, do it in an automated way so we minimize a backlog of human time doing mundane and boring tasks? Save for the human the tasks that are inherently human – meaning the application of judgment and insight – and let the computer do a million times a second what computers can do, which is rote, quick, and literal work.”
Giant Oak Search Technology (GOST) enters in to help the investigative process determine where those elements are that need human intervention – and where there are issues that merit interest.
“The government, they might not care about a speeding ticket but they might care a lot about a DUI or a criminal event,” noted McDonald.
GOST knows how to flag changes in behavior. Combined with all of the data TransUnion holds, they’re able to do the kind of behavior analysis the government needs, notes Shiffman.
“TransUnion and GOST and Giant Oak are working together, today, in government agencies to find money launderers, terrorist financiers, people involved in child exploitation,” said Shiffman. “We’ve been working together for a number of years and we have a long track record of identifying patterns of threat behavior that otherwise would not be identified.”
