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KE Public Lecture on Machine and Deep Learning in Financial Modeling

Publishing Date: 21/02/2018      (Last Update: 21/02/2018)

Event Details

Date2018-03-22
Time6:00pm - 7:00pm
VenueKK102, K. K. Leung Building, HKU

Dr. Agus Sudjianto
Executive Vice President, Head of Corporate Model Risk, Wells Fargo, USA

Date: March 22, 2018 (Thursday)
Time: 6:00pm - 7:00pm
Venue: Room 102, K. K. Leung Building, HKU

Mathematical models are extensively used by financial institutions for various purposes such as to run the business or to fulfill regulatory requirements. Among the most critical usage of mathematical models is the evaluation of a bank’s financial health and its ability to sustain adverse economic scenarios. Mathematical models are also used to perform credit underwriting, portfolio management, derivative valuation and pricing, risk measurement and to prevent financial crime.

Historically, banks have employed traditional mathematical and statistical models. More recently, machine learning algorithms have gained strong adoption particularly due to their ability to deal with very large structured and unstructured data sets. In this talk, I will discuss the breadth of mathematical modeling applications in financial institutions, the role of machine and deep learning, and current challenges.

About the Speaker
Agus Sudjianto is an executive  vice president and head of Corporate Model Risk for Wells Fargo, where he is responsible for enterprise model risk management and serves as the Chair of the Model Risk Committee. Prior to his current position, he was the modeling and analytics director and chief model risk officer at Lloyds Banking Group in the United Kingdom. Before joining Lloyds, he was a senior credit risk executive and head of Quantitative Risk at Bank of America.

Dr. Sudjianto holds several U.S. patents in finance and in engineering.  He has published numerous technical papers and is the co-author of the book: Design and Modeling for Computer Experiments. His technical expertise and interests include quantitative risk management, credit risk modeling, machine learning and computational statistics.

Dr. Sudjianto holds a masters degree in management from M.I.T. and a Ph.D. in engineering from Wayne State University.


Registration: http://www.fbe.hku.hk/go/ke-Sudjianto
Enquiries:
Faculty of Busiess and Economics                             (852) 3917 4047 / fbecomm@hku.hk
Big Data Research Cluster, Faculty of Science         (852) 3917 2466 / saas@hku.hk