Uncovering Critical Historical Data to Progress a Complex Legal Case

As part of a major court case, a U.S.-based law firm needed access to key data covering two decades from a multinational corporation in the United Arab Emirates (UAE). With $95 million (mn) at stake, it was critical that as much relevant data as possible was identified. However, this was proving extremely challenging as the information required was historical, with much of it stored in a warehouse in the UAE. Added to this, potentially valuable email data was no longer accessible due to changes in systems and staff.

Despite these challenges, Kroll was able to locate and analyze more than 10 terabytes of data, completing a highly complex data mapping process that enabled the law firm to gain the information it required and ensuring that a highly sensitive and high-value case moves closer to a satisfactory resolution for all parties.

The Challenge

As part of a matter in dispute in the courts, a U.S.-based law firm needed to collect critical data spanning decades from a multinational corporation in the UAE. The discovery exercise was initially stalled on a jurisdictional basis, but voluntary cooperation was agreed. Discovery later underwent further delays as the law firm was unable to access the detailed historical data it required to inform the case and resolve the issue. This was because the company had significant concerns about the investigation, and the majority of the documentation required was stored in a warehouse in Dubai or was inaccessible due to system changes within the company. An additional obstacle to the process was that most of the company’s current employees lacked knowledge of its  historic IT infrastructure.

Kroll's Solution

The law firm engaged Kroll to develop a productive working relationship with the company and gain an initial understanding of the scale and location of the required data. This was a complex process that entailed the Kroll team visiting the company in person on several occasions to gain the trust of the company’s CEO and convince them to provide access to key historical information. Kroll helped outline the law firm’s discovery requirements, why the data was needed, how the process could be managed, and the privacy and security mechanisms that would be implemented. This was followed by a structured data mapping process which included:

• Investigating initial data sets to establish the likely presence of additional data within legacy systems
• Attending the company’s extensive storage site in person to locate relevant paper documents and large bound documents and files, before logging and photographing them and engaging a local vendor to complete a major scanning exercise
• Investigating the location of electronic data and emails to understand the company’s current and historical IT and email exchange infrastructure and reconstruct past systems and actions
• Contacting past company employees to help identify the location of email data
• Searching for company laptops and old servers that could provide relevant data
• Completing a major forensic imaging exercise for the forensic collection of data once all the relevant data was tracked down
• Writing contemporaneous notes to accurately document every stage

After collecting more than 10 terabytes of data, the team moved it into Kroll’s Dubai cyber lab facility. Following some triage by Kroll and lawyers from the U.S. firm, 1.3 terabytes of data were then staged and added to the Kroll RelativityOne platform, which streamlines discovery processes to allow legal professionals to store and control millions of documents across devices and jurisdictions from one single interface. As part of this, optical character recognition (OCR) was applied to the data to translate images of text, such as scanned and redacted documents, into actual text characters, ensuring that no key data was missed.

RelativityOne’s AI completed key analytical processes to reduce the quantity of documents requiring review by the lawyers. The 1.3 million documents (including paper-based documents made up 100,000 pages and 75,000 paper files) that were first added to the RelativityOne system were reduced to 250,000 by the searches.

RelativityOne analyzed these remaining documents and then used that insight to search for other data that might have been relevant, allowing the team to make a statistically-informed decision about when to stop reviewing. This ended up saving time and costs for the law firm. The implementation of active learning and statistics also helped to reduce the costs of the review. Of the 250,000 documents, around 40,000 of them were identified as key and used as a priority in the search for evidence.