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USC Marshall Convenes Workshop on Fintech and Big Data




(MENAFN - PR Newswire) LOS ANGELES, Aug. 13, 2019 /PRNewswire/ -- The University of Southern California's Marshall School of Business convened a workshop on the latest developments and future prospects arising from the convergence of banking and financial technology, or "fintech." The event was co-sponsored by the Institute for Outlier Research in Business (iORB -https://www.marshall.usc.edu/faculty-research/institute-outlier-research-business ), Lexant Advisors ( https://www.lexantadvisors.com/ ) and Berkeley Research Group ( https://www.thinkbrg.com/ ).

"This revolutionary event brought together bankers, academic researchers, and leaders at pioneering fintech companies to collaborate and address some of the most challenging business and big data issues facing our rapidly evolving sector," said Gerard Hoberg, Professor of Finance and Business Economics at USC Marshall.

Professor Hoberg's comments were echoed by K.Y. Cheng, Chairman of Lexant Advisors and a retired banker, who addressed the opportunities and challenges confronting the 5,500 community banks and the fintech marketplace. He sees a symbiotic relationship between the two, but both need to reconcile their unique business cultures to make it a win-win situation.

Walt Mix, Managing Director and Financial Services Practice Leader with Berkeley Research Group, kicked off the corporate presentations with a description of the big picture on the regulatory, business, and fintech environment. He discussed the rise of fintech and its impact on the financial world.

Additional program highlights included:

- Jeff Keltner, Head of Business Development for Upstart Finance ( https://www.upstart.com/ ), shared how the company has successfully developed and deployed machine learning to extend consumer loans, now reaching $4 billion while meeting regulatory requirements;- Daniel Mason, VP Strategy and Operations of Spring Labs ( https://www.springlabs.com/ ), described the challenges facing the credit score business and suggested some technological solutions;- Victor Ardulov, CSO of Calypso AI ( https://calypsoai.com/ ), shared his years of experience in helping financial institutions by using big data to meet and even surpass compliance requirements;- Rich Finkelman, Partner with Vista Analytics ( http://vista-analytics.com/ ), updated the latest R & D on mashing learning and AI.- Juan Suarez, VP Legal with Coinbase ( https://www.coinbase.com/ ) – a leading bit coin company in the United States – shared with the audience the latest developments in block chain operations, financial data mining, and bitcoin trading.

The session concluded with a robust discussion covering a wide ranging subjects from the core themes of the conference to international business issues with active audience participation. The panel of practitioners featured:

- Noor Menai, President and CEO, CTBC Bank ( https://www.ctbcbankusa.com/ )- Walt Mix, Managing Director and Financial Services Practice Leader, Berkeley Research Group- Larry Harris, Fred V. Keenan Chair in Finance and Professor of Finance and Business Economics, USC Marshall- Jinchi Lv, McAlister Associate Professor in Business Administration and Professor of Data Sciences and Operation, USC Marshall- Rodney Ramcharan, Associate Professor of Finance and Business Economics, USC Marshall

"As banks, non-bank lenders, and fintech converge, discussions like the one today will become even more important to understand and continue to grow this sector of the financial marketplace," said co-organizers K.Y. Cheng and Walt Mix in a joint statement. "We look forward to joining future events with Marshall and other schools and universities contributing to this understanding and growth."

For more information about USC Marshall, iORB, and fintech research, visitmarshall.usc.edu .

Contact: Matthew SimmonsUSC Marshall Media RelationsPhone: 213-821-9868Email:

SOURCE USC Marshall School of Business



Related Links

http://www.marshall.usc.edu


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USC Marshall Convenes Workshop on Fintech and Big Data

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