Case Study: Codefendants Reduce Huge Data Set in a Price Fixing Class Action

Client need

Create manageable review populations

In a large-scale class-action matter, the client faced highly complex negotiations in the course of responding to production requests from approximately 1,300 plaintiff entities against 15 codefendant banks. The data set of 2,391,461 documents from 30+ custodians required extensive culling to create a manageable review population of likely-relevant documents.

Client solution

Identify non-relevant emails to create a likely-relevant review population.

Working solely with the metadata and extracted text, the Case Insights^TM ECA team created exclusion categories to cull 1,866,885 irrelevant documents from the population. Then they applied multiple variations of sampling analysis search terms (e.g., changing proximity conditions, adding carve-outs) to identify problematic or redundant syntactic strings. Finally, they ran a search term analysis on the remaining 524,576 documents to remove an additional 81,547 records, reducing the initial 2,391,461 documents to 447,648.

Why Epiq

Epiq’s Case Insights^TM team has a proven track record for using data analytics to reduce large data sets to manageable review sets.