[January 21, 2014]

The Next Great Frontier for Capital Markets Text Analytics is Proprietary Data, Says TABB

In new research published today, "Inner Voices: Harvesting Text Analytics from Proprietary Data," TABB Group believes the next great frontier for text analytics is proprietary data, but if capital markets firms expect to find broadly applicable value in the growing fire hose of unstructured content, they are going to need an enterprise-ready platform and industrial-strength solutions.

According to the report's co-authors, research analyst Valerie Bogard and senior analyst Paul Rowady, early adoption of text analytics tools has been limited to machine-readable news feeds targeted at ultra-low latency trading strategies, but the breadth of use cases and the profiles of buyers are expanding rapidly to new areas. However, the main challenge to expansion has been the lack of an enterprise-ready platform but with the increasing breadth of applicability and its power to harvest actionable insights from unstructured big data, enterprise text analytics solutions should be on the short list of candidates that will see an increase in spend, says Rowady.

Internally generated and disseminated unstructured data holds a high value for customized intelligence, but as Bogard points out, it has so far remained untapped. "Enhancing the technology already mining social media and news and applying it to this new dataset is the next step in the megatrend of machine-readable content that should be in every market data arsenal, despite the challenges."

High-level challenges associated with textual analytics include storage architecture, security, apturing new formats of content and incorporating the contextual nuances of content. These issues are increasingly being addressed and improved, leading to greater applicability to risk, operations and compliance areas. Ensuring that the technology is flexible enough to allow for any user to manipulate and configure any data set to their needs is an ambitious project, Rowady cautions, that intrinsically requires a complex system of collection, preparation, processing and publishing.

This complex procedure uses reference data, metadata tagging, sentiment analysis and methods of classification and extraction to create an end product capable of being consumed by machines and humans alike. But as the two authors explain, to make text analytics solutions easier to implement and utilize, they must include four key attributes: digest a comprehensive array of data sources, a growing bulk of which are proprietary; offer flexible modeling and output formats; be highly scalable; and offer lower-cost / higher-speed encryption.

This may loom as a challenge for a technology still in its early stages of development but TABB Group believes the writing is on the wall: the functionality to securely ingest any unstructured data, perform any filtering routine, configure the right output and scale to enterprise-level needs is converging quickly. In time, says Rowady, we expect more datasets to be automatically enhanced with more granular metadata to prepare it for later detailed analytics.

The 15-page report with 8 exhibits is available for download by TABB Group Research Alliance Equities and Data and Analytics clients and pre-qualified media at http://www.tabbgroup.com/Login.aspx. For the Executive Summary or to purchase the research, go to http://www.tabbgroup.com/PublicationDetail.aspx?PublicationID=1442&MenuID=44&ParentMenuID=2&PageID=43 or write to [email protected].

About TABB Group

Based in New York and London, TABB is the only research and consulting firm focused exclusively on capital markets, based on the interview-based, "first-person knowledge" research methodology developed by Larry Tabb. For more information, visit www.tabbgroup.com. In 2010, TABB launched TabbFORUM, the online capital markets community for peer-to-peer contributed opinion and analysis covering current industry issues, tracked daily by 18,000-plus professionals; in October, 2013, QuantFORUM, a new online channel for the global quantitative investing community, went live.

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