Financial Service Industry

STRATEGY

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