A multinational bank was faced with a government investigation and ensuing litigation over commissions charged on foreign exchange funds and the timing of trades. Terabytes of data, representing tens of millions of documents over several years from multiple data type sources, were initially gathered and required extensive filtering.
Following consultation and development of a best practices workflow, we employed a predictive coding approach using Brainspace analytics. In conjunction with subject matter experts, data was segregated into three buckets: responsive, potentially responsive, and non-responsive. This process took less than a week and removed nearly eight million documents from the review pool, saving the client millions in potential attorney costs.
We assembled a team of more than 100 document review attorneys to review the two million+ documents that existed in the responsive/potentially responsive categories. With outside counsel and our project management team, we began the review of the remaining documents and statistical sample QC review of the non-responsive data.
This approach, along with Cimplifi’s competitive pricing and application of technology, resulted in an estimated $10 million in savings over traditional approaches.Download Case Study