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Ernst & Young : Predictive Coding for eDiscovery, Investigations

By Rob Starr, Content Manager,

Ernst & Young, a leading provider of assurance and advisory services, recently announced the release of the Automated Predictive Coding platform to help legal counsel improve the quality, speed and cost-effectiveness of eDiscovery and document review. The end-to-end application is fully integrated within kCura’s Relativity™ review platform so there is no need to port data from one system into another. Users can take advantage of the predictive results through the use of boolean searching, batching and imaging capabilities already provided within Relativity.

State-of-the-art data modeling automatically parses each document into hundreds of topics and assigns a different relevance score to each topic per unique document. This differs from other systems that identify only the preponderance of words within a document.  When the topics are correlated with attorney sampling decisions using the Ernst & Young sophisticated voting schema, the system can detect highly nuanced differences even between documents that contain a statistically high degree of similarity or nearness.

While technology-assisted review has been used successfully, it has remained shrouded in uncertainty with opaque explanations of competing vendor technologies and approaches. With its latest release, Ernst & Young has replaced guesswork with transparent, defensible processes and tools that can be used in any type of investigation or litigation, regardless of industry vertical or data volume.



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