… for a financial services company

 

Text analyt 2

Business Challenge

  • Reduce manual efforts and turn around time in analyzing:
    • More than 20,000 sources of text information (Regulatory Filings, Company Websites, e-mails, 3rd party sources, etc..)
    • More than 3.5 Million documents/yr to process
    • 70+ events to cover
    • Multilingual content
    • Diversity & noise in data sets

Analytics Approach

  • Natural Language Processing (NLP) and Machine Learning algorithms developed to scan text sources to classify events and extract key information

Impact

  • Our solution saved ~5000 Person hours of effort per year for the client
    • Event Classification:
      • 94.3% Precision (True positives)
      • 93.5% Recall (ratio of the number of relevant records to the total number of relevant records)
    • Key Information extraction:
      • 90-98% Precision
      • 93.5% Recall

Results of the document-load handled and classified by the text analytics software

Text- info extract 2