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Watson Suits Up For Wall Street Gig

By   /  March 7, 2012  /  No Comments

Watson’s gone into banking: Citi is evaluating ways that IBM’s Deep QA technology can help advance digital banking efforts, through analysis of customer needs and processing tons of up-to-the-minute financial, economic, product and client data, according to a press release.

“We are working to rethink and redesign the various ways in which our customers and clients interact with money. We will collaborate with IBM to explore how we can use the Watson technology to provide our customers with new, secure services designed around their increasingly digital and mobile lives,” said Don Callahan, Citi’s Chief Administrative Officer and Chief Operations & Technology Officer in the press statement. The plan is to use Watson’s NLP capabilities for analyzing human-language questions and drawing upon its interpretations of the query to derive potential answers that it then tests, validates, and scores, to help financial reps sort out options, opportunities and risks targeted to a consumer’s individual circumstances.

Earlier this year, IBM paired up with WellPoint in a strategic partnership in another vertical sector, health care, with the goal of using Watson’s DeepQA to help physicians improve treatment for oncology patients by assessing medical evidence and personal case data to deliver probability-based treatment options.

But financial services has always been discussed as an industry that could benefit from Watson’s brainpower, too. In a video here, Dr. Carl Abrams of IBM Research, Financial Services, says that, “The currency of financial services is information, and the ability to semantically analyze that, to extract from that what the meaning is, and then take that meaning and apply it to something is simply becoming a level playing field.”

Financial services executive Jay Dweck, formerly global head of strategy and technology at Morgan Stanly, notes in the video that data in the sector is growing about 70 percent a year, and that having this much data requires a large range and variety of tools to be able to extract real knowledge from it. “You could put together the logical connections among the disparate pieces of information,” he said.


About the author

Jennifer Zaino is a New York-based freelance writer specializing in business and technology journalism. She has been an executive editor at leading technology publications, including InformationWeek, where she spearheaded an award-winning news section, and Network Computing, where she helped develop online content strategies including review exclusives and analyst reports. Her freelance credentials include being a regular contributor of original content to The Semantic Web Blog; acting as a contributing writer to RFID Journal; and serving as executive editor at the Smart Architect Smart Enterprise Exchange group. Her work also has appeared in publications and on web sites including EdTech (K-12 and Higher Ed), Ingram Micro Channel Advisor, The CMO Site, and Federal Computer Week.

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