A multinational corporation needed to investigate a potential compliance violation. An employee in a foreign office allegedly accepted free travel and hotel accommodations from vendors.
The company’s representative turned to Control Risks to get to the bottom of the issue. Control Risks needed to take a deep dive into the data to see if the employee’s actions were cause for dismissal.
Pivoting Off the Data
Control Risks first had to get their hands on the employee’s data. A Control Risks forensics analyst collected and imaged the employee’s laptop and mobile phone. Then, the team uploaded the data into RelativityOne.
After processing the data, Control Risks had 100,000 documents to analyze. Their client wanted no stone left unturned. They didn’t want to miss any documents showing misconduct or tangential activity implicating other employees.
The team used various analytics tools in RelativityOne. This way, they could narrow the document list without missing crucial information.
“We knew from the onset that analytics would power us through this investigation,” said Nancy Stephenson, partner at Control Risks.
Maximizing their Analytics Toolbox
Control Risks needed to wade through the mass amounts of information. So, they used clustering in RelativityOne to drill down into topics. This could include communications on travel, entertainment, flights, and hotels.
“We wanted to find anything out of the ordinary,” Nancy noted. “We focused on any areas where the concepts veered off of our expectations.”
Control Risks was aware of specific industry conferences where the custodian allegedly accepted improper benefits. The team compared that information to the clusters to see if relevant concepts surfaced. The team also used email threading to cut redundant content.
Adding Something New to the Mix
The team was well versed in using clustering and email threading on their matters. For this case, they decided to use a new tool: communication analysis. Using communication analysis, the team quickly identified key players’ names and email domains. From there, Control Risks had access to a consolidated view of the activity.
“We pivoted on information and drilled down into relevant subsets of communications by entity,” Nancy noted. “We identified domains that we had not expected, which was crucial.”
The team further used communication analysis to uncover leads. They also expanded the search to substantiate their findings. Ultimately, this combination of tools reduced the data set in focus from 100,000 documents to just 600 emails.
Finding the Unexpected
The team used a communication map to investigate the employee’s interactions.
Using the map, the team found personal communications on the employee’s device. The team looked into the interactions and found that the employee potentially bought flights and hotels for their significant other.
“Communication analysis lets us take a microscope to the data,” Nancy said. “This turns a review from linear to geometric.”
“Communication analysis lets us take a microscope to the data. This turns a review from linear to geometric.”
NANCY STEPHENSON, Partner
Relativity Analytics provided a list of terms that were prevalent in the communications. Then, it ranked the terms by frequency.
“If the team deemed a term provocative enough and it had merit, they ran it on a broader level across the document population,” Nancy said.
This way, the team could determine if the term was often used in other conversations and get more context. They could also see if the employee was using code names with other parties.
Control Risks found information verifying their earlier findings that the employee booked travel for their significant other. Worse yet, it was on the company’s dime.
“Our client confirmed our findings were highly relevant,” Nancy said.
From collection to the company taking action, the process took only one week.
Planning for Growing Data Volumes
Without communication analysis, the team’s investigation would have taken longer—and it would have cost more. Control Risks plans to use the tool to analyze matters as effectively as possible.
“With evolving privacy and regulatory policies, we need advanced tools to handle names and communication,” Nancy said. “These tools are instrumental in navigating the increasing volumes of data we encounter.”