The Intersection of Finance, Cryptography and AI with Professor Andrew W. Lo

In this episode

Professor Andrew W. Lo shares insight into the collaborative research efforts of MIT CSAIL and MIT Sloan School of Management within the three distinct areas of cryptography, machine learning and AI, as well as discusses the progress of blockchain technology and cryptocurrency. He also offers a glimpse into the future of banking and finance and reveals the emerging technology of secured multi-party computation.

How is it the case that technology can actually help us make better financial decisions? In order to understand that, we actually have to understand how people make decisions. Artificial intelligence is really a key part of that.
Andrew Lo
Charles E. and Susan T. Harris Professor, MIT Sloan School of Management

About the speakers

Faculty Co-Director, FinTech@CSAIL
Charles E. and Susan T. Harris Professor, MIT Sloan School of Management
Director, MIT Laboratory for Financial Engineering

Andrew Lo obtained his A.M. and PhD in economics from Harvard University in 1984, his B.A. in economics from Yale University in 1980, and graduated from the Bronx High School of Science in 1977. Lo began his academic career at the University of Pennsylvania’s Wharton School, where he was an assistant and associate professor from 1984 to 1988. Now, Lo is the Charles E. and Susan T. Harris Professor at the MIT Sloan School of Management and the director of MIT’s Laboratory for Financial Engineering. He later joined the MIT Computer Science and Artificial Intelligence Laboratory as a principal investigator. Some of his awards include: Batterymarch, Guggenheim, and Sloan Fellowships; the Paul A. Samuelson Award; the Eugene Fama Prize; and the IAFE-SunGard Financial Engineer of the Year.

Industry Impact
Andrew Lo’s current research spans on five areas:

  • Evolutionary models of Investor behavior and adaptive markets
  • Systemic risk and financial regulation
  • Quantitative models of financial markets
  • Financial applications of machine-learning techniques and secure multi-party computation
  • Healthcare finance

With the development of commerce and corporate governance, the use of financial engineering is a tool and a model for tending to the growth of organizations that have become important therefore raising the level for competitiveness and efficiency. Financial engineering helps to create, design, and implement new financial models and processes in order to find solutions for problems. This system helps to discover new financial opportunities: preparing models that require a great amount of research and rely on in-depth data analysis, simulations, risk analysis and stochastics. With that said, financial engineering can benefit organizations in seeking new solutions to various problems that include risk management, scenario simulation, and new product development.