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Financial Service Industry

Financial Service Industry


An information retrieval system for the financial services industry using Natural Language Processing techniques.

We helped them with:

  • Enable users to get insights from the information filed by companies with the United States Securities and Exchange Commission in the last 25 years (a corpus of about 13+ million documents).


Solution scope included:

  • Created models that extract text from unstructured/structured text either to guess the topic or identify entities.
  • Analyzing linguistic structure in the text including parsing and semantic analysis
  • Syntactic analysis or parsing is done to, examine text using basic grammatical rules to determine sentence structure, word organization, and word relationships.
  • You can extract pre-defined information from text using text extraction which helps analyze securities data easily.


  • Process massive amounts of data in seconds or minutes.
  • Gain a better understanding of your target market
  • Can instantly scale up or down to match your demands, giving you as much or as little computational power as you require.
  • Get a more objective and precise assessment.
  • Aids in the extraction of data-driven, real-world, immediately actionable insights from unstructured text.
  • High scalability is achieved through a decoupled architecture,
  • Increased efficiency through collocation.
  • A sea change quality of deliverables


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