… for a financial services company
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
- Event Classification:
Results of the document-load handled and classified by the text analytics software