E-discovery has become challenging and expensive in this era of big data. KPMG LLP, the audit, tax and advisory firm, today announced upgrades to its discovery management technology, Discovery Radar®, which helps corporate law departments and law firms cut e-discovery costs and simplify management of large, complex litigation.
The proprietary KPMG system, Discovery Radar 5.0, integrates critical steps in the e-discovery process including processing information, early case assessment, technology-assisted review (TAR) and statistical sampling. All of these steps help ensure that electronically stored documents gathered are relevant to a case.
KPMG’s analysis of client cases revealed that integrating the steps in e-discovery can reduce the number of days and amount of money it takes to manage large volumes of electronically stored information by more than 50 percent.
Additional features include
“Discovery Radar 5.0 can significantly cut the time required to process discovery documents and make them available to the legal team for analysis and review,” said Kelli J. Brooks, KPMG’s U.S. co-leader for Forensic Technology Services. “Integrating these new capabilities with our leading-edge machine learning and our advanced statistical sampling further reduces the potential for undetected human error while reducing the time involved and the total cost of eDiscovery.”
Discovery Radar uses KPMG’s proprietary Global Evidence Tracking System, delivered through a secure software-as-a-service cloud environment. The software is designed to help improve process and project management from the identification through production phases of the Electronic-Discovery Reference Model. Electronic-Discovery Reference Model was created by the legal industry to help develop guidelines and standards for e-discovery consumers and providers.
More information about KPMG’s forensic technology can be found here.
KPMG recently released a white paper, Quality Control for Predictive Coding in eDiscovery, that offers additional insights about eDiscovery leading practices that legal professionals can use to help manage large volumes of data, reduce discovery costs and maintain quality and accuracy. The paper can be found here.