A Talk by
Monday, April 8th
5:45 PM Registration
6:00 PM Seminar Begins 7:30 PM Reception
Abstract
In this talk, I describe a variety of machine learning models that I have built and applied to problems in business and finance. I begin with an historical introduction to neural networks, including brief descriptions of the perceptron, and methods of gradient descent, backpropagation and regularization. I then describe single hidden-layer perceptrons built in the early 1990s to detect fraud on credit card portfolios, identify customers who will give up their credit cards, and later, for trading US Treasury bonds. I then describe recent work with deep learning networks that predict spread changes for corporate bonds, price moves from trade flows, and a natural language processing model that predicts market moves from sentiment data. Finally, I provide some thoughts on how artificial intelligence/machine learning is changing the fixed income trading business.
Biography
Terry Benzschawel has recently left a thirty-year career on Wall Street to start his own firm. Prior to that, Terry was a Managing Director in Citigroup's Institutional Clients Business. Terry headed the Quantitative Credit Trading group which developed quantitative tools and strategies for credit market trading and risk management, both for Citi's clients and for in-house applications.
Terry received a Ph.D. in Experimental Psychology from Indiana University (1980) and his B.A. (with Distinction) from the University of Wisconsin (1975). His Ph.D. thesis concerned development of a neural network model of the human visual system. Terry has done post-doctoral fellowships in Optometry at the University of California at Berkeley and in Ophthalmology at the Johns Hopkins University School of Medicine. He also was a visiting scientist at the IBM Thomas J. Watson Research Center prior to embarking on a career in finance. He currently serves on the steering committees of the Masters of Financial Engineering (MFE) Programs at the University of California at Berkeley and serves there as an Executive in Residence.
In 1988, Terry began his financial career at Chase Manhattan Bank, training genetic algorithms to predict corporate bankruptcy. In 1990, he was hired by Citibank to build neural network models to detect fraudulent card transactions and to predict credit card attrition. In 1992 he moved to investment banking at Salomon Brothers where he built models for proprietary trading for Salomon's Fixed Income Arbitrage Group. In 1998, he moved to the fixed income strategy as a credit strategist with a focus on client-oriented solutions across all credit markets and has worked in related roles since then. Terry was promoted to Managing Director at Citi in 2008.
Terry is a frequent speaker at industry conferences and events and has lectured on credit modelling at major universities. In addition, he has published over a dozen articles in refereed journals and has authored two books: CREDIT MODELLING: FACTS, THEORIES AND APPLICATIONS and CREDIT MODELLING: ADVANCED TOPICS. In addition, Terry has been the instructor for courses in credit modelling for Incisive Media, the Centre for Finance Professionals, the Machine Learning Institute and has taught in UCLA’s MFE program last Fall. Finally, Terry has taught a course on credit modelling at Russia's Sberbank in Moscow.
Acknowledgments
Special thanks to the Fordham University Gabelli School of Business for hosting and sponsoring the seminar.
