Thomson Reuters Enables Financial Services Industry to Manage Big Data Challenges with Intelligent Tagging Offering

Intelligent Tagging is designed to empower clients to better tag, extract meaning and derive insights through an enhanced unstructured (text) data tagging solution
NEW YORK/LONDON – Thomson Reuters Intelligent Tagging clients can now deploy its capabilities behind their secure firewalls, enabling them to manage and potentially extract meaning and value out of massive amounts of data, and possibly more efficiently draw intelligence from them.
Launched in July 2015, Intelligent Tagging provides a fast and powerful way to enrich existing textual content to increase its value and accessibility to turn the big and unrestricted data challenge into a precise advantage. Since the launch, Thomson Reuters clients have indicated a desire to have a deployed version of the product. Accordingly, Deployed Intelligent Tagging now delivers the capability for companies to potentially better harvest valuable insights in form of entities and topics hidden in the vast wealth of unstructured and untapped textual content all within their own security firewalls.
“Our clients seeking to thrive in today’s data economy can easily find themselves buried under a flood of information,” said Ranjit Tinaikar, managing director, advisory and investment management, Thomson Reuters. “Thomson Reuters Intelligent Tagging puts our clients in the driver’s seat to meet this challenge with a tagging solution that helps identify entities, topics and relationships between and among data sets, likely leading to greater insight to generate alpha, manage risk and bolster research platforms. This represents the next step in the evolution of Thomson Reuters open platform strategy.”
During comprehensive discussions with clients, Thomson Reuters found that a significant number of buy and sell side institutions are increasingly looking for better ways to tag and extract meaning out of their internal unstructured (text) content as well as external content (news, blogs, social media, etc.). Intelligent Tagging uses natural language processing algorithms, text analytics, and data-mining technologies while also leveraging Thomson Reuters content, all designed to derive meaning from unstructured information – including news articles, blog posts, other publicly available text content as well as customer’s proprietary and TR unstructured content such as: fillings, earnings & transcripts and permissioned research.
Intelligent Tagging also appends a Thomson Reuters Permanent Identifier (PermID), a well-established and complete identifier than spans a wide variety of entity types including but not limited to organizations, instruments, funds, issuers, events and people. The information model leveraging PermID is designed to ensure that linkages across the entity types are comprehensive and well managed, irrespective of the information source. Such a comprehensive information model in combination with Intelligent tagging will likely further enable TR clients to more seamlessly ingest, link and manage 3rd party content, Thomson Reuters content and their own proprietary content.
Intelligent Tagging (Deployed) allows users to leverage the power of Intelligent Tagging on premise, when compliance and security policies so require. The deployed solution is also scalable to handle the greater volumes and throughputs that Thomson Reuters clients typically request for this type of product.