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CASE STUDY

Canopy Reduces Review Population by 89%, Saving Response Team 2,000 Hours

The Challenge

A U.S.-based online retailer experienced a business email compromise (BEC) resulting in 186,479 compromised documents. The response team first tried data mining via traditional ediscovery methods, which flagged 48% of the data set for PII Review. The project lead suspected this number was too high and did not want to review potentially thousands of unnecessary documents.

The Solution

The team enlisted Canopy's Data Breach Response software. Its advanced machine learning models automatically detected and validated over 70 different types of personally identifiable information (PII). The application’s powerful image and document classification tools helped further guide the response team’s strategy and focus their review efforts.

Original Data Set: 186,479 Documents

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The Result

  • Detected and validated over 70 types of potentially-reportable PII elements
  • Clearly indicated which documents contained PII
  • Image and document classification tools provided insight beyond the detection of concrete PII elements
  • Correctly flagged just 10,106 documents as needing PII Review — 89% fewer than were initially flagged by ediscovery methods
  • Saved response team 2,000 review hours

Zero in on PII to Save Time & Notify Faster

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79,894 documents

incorrectly flagged via ediscovery methods

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90 seconds

average time to review each document

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2,000 hours

saved with Canopy

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