Stanford AFTLab Seeks Innovative Solutions for Financial Industry Problems
A tsunami wave of fintech is hitting the finance industry and bringing new opportunities for both startups and large companies. In order to accelerate research, innovation and thought leadership at this intersection of finance and technology, Stanford MS&E recently established the Advanced Financial Technologies Laboratory (AFTLab).
Advancements in big data analysis and high performance computing allow for machine intelligence applications for a variety of real-world financial issues. These new technologies may eventually transform the way consumers and businesses conduct transactions, gain credit, make business and personal financial decisions, and invest money.
Professor Kay Giesecke, director of AFTLab said, “Our work will have broad relevance to the financial industry, including design of efficient computational and statistical methods for processing and analyzing massive data sets, as well as tools for data-driven pricing, risk management, and business decisions, to name a few.”
To that end, Stanford has pooled the academic talents of several MS&E professors specializing in stochastics, simulation, numerics, optimization, algorithms, financial markets, and economics to create AFTLab.
Participants include Professors Jose Blanchet, Kay Giesecke, Peter Glynn, Gerd Infanger, Markus Pelger and Yinyu Ye. They are joined by more than 10 current Stanford Ph.D.s, and an advisory board that will grow over time, but currently includes Steve Jurvetson (DFJ Ventures), Amir Khosrowshahi (Intel), Robert Sears (BBVA) and W. Scott Simon.
Stanford MS&E has a long history of cross-disciplinary projects. The collaborative atmosphere is frequently referenced as a strong positive by new faculty. (Check out Stanford’s Open Policing Project as another recent example of cross-disciplinary work.)
According to Giesecke, the breadth of expertise will facilitate understanding of the complex issues at the intersection of finance and technology. “Our research shows that machine intelligence is good for much more than creating self-driving cars or smarter social media algorithms. Its real promise is in shedding more light on a wide array of financial issues that ultimately affect millions of people. We are exploring the use of these approaches to better understand financial behavior and perhaps prevent future financial crises.”
Some of the first work to come out of AFTLab includes new methods for assessing mortgage risk. “Our results could help banks develop more effective strategies for dealing with troubled borrowers or manage their risks better,” said Giesecke, who co-authored some of the research with his former Ph.D. students, Justin Sirignano (now at UIUC) and Apaar Sadwani (now at Google Brain.)
Professor Giesecke hopes that AFTLab will promote closer ties between industry and academia. Companies that are interested in the work of AFTLab can become “Affiliate Members.” Members gain access to all AFTLab events, a sponsorship of the annual “AI in Fintech Forum,” an invitation to send a visiting scholar to the Farm, and opportunities to provide feedback on AFTLab’s research agenda and to recruit AFTLab students.
AFTLab’s January event, the “AI in Fintech Forum,” was attended by more than 150 finance professionals and academic researchers. Presenters shared the latest technology advancements and research, discussed use cases, trends and regulatory considerations. The event was designed to establish a model for ongoing collaboration, and to foster partnerships among participants. The roster of presenters included key players in the fintech world. Next year’s event is slated for February 8, 2018. The speakers list is currently under development.
Additionally, weekly AFTLab seminars at Stanford feature some of the latest thinking and scholarship about fintech topics.
If you’re interested in becoming an AFTLab Affiliate Member or learning more about the 2018 “AI in Fintech Forum,” please contact Professor Kay Giesecke at giesecke@stanford.edu.
