Sanjiv Das is the William and Janice Terry Professor of Finance at Santa Clara University’s Leavey School of Business. He was previously Associate Professor at Harvard Business School and UC Berkeley. He holds post-graduate degrees in Finance (M.Phil and Ph.D. from New York University), Computer Science (M.S. from UC Berkeley), an MBA from the Indian Institute of Management, and is a qualified Cost and Works Accountant. He edits several academic journals. Prior to being an academic, he worked in the derivatives business as a Vice-President at Citibank. His current research interests include: the modeling of default risk, machine learning, social networks, derivatives pricing models, portfolio theory, and venture capital. He has published over ninety articles in academic journals, and won numerous awards for research and teaching. His recent book “Derivatives: Principles and Practice” was published in May 2010. He currently also serves as a Senior Fellow at the FDIC Center for Financial Research.
AI-Machine Learning and Deep Learning in FinTech
In This talk we define and characterize the business of FinTech by identifying 10 salient areas of influence. We then analyse one area, namely AI, and examine how it is changing the landscape of finance through FinTech applications.
♦ What is FinTech?
♦ Example of AI in FinTech.
♦ Predicting markets with AI.
♦ The transformation of data use with AI.
♦ The future of labor markets in the finance industry