(Subject to change; If you have questions on course content, send them to [email protected] and subject “AI in FinTech”)
In recent years, explosion of data, inexpensive computing power and developments in big data processing infrastructure have led to increased use of Machine Learning in all industries. So, financial services incumbents as well as FinTech startups are using Machine Learning and Data Science to improve business economics and maintain/create their competitive advantage. Since data volume is only expected to increase in this digital world, Machine Learning and Artificial Intelligence are expected to get ubiquitous in the coming years with wide range of implications for FinServ and FinTech companies.
This course will cover:
- Basic concepts related to Data Science, Machine Learning and Artificial Intelligence
- History of Machine Learning and AI in Financial Services and FinTech
- Closer look at several ML and AI financial services use cases (B2B and B2C)
- Future trends and its potential impact to the financial services industry - including job displacement and new career options
At the end of this course, you will be familiar with basic concepts of ML and AI and appreciate how they are being used in the Financial Services industry.
This course is recommended for anyone who is interested in learning about application of AI and ML in the financial services industry.
Greg LaBlanc has been teaching at the Haas School of Business and Berkeley Law since 2005. He teaches primarily in the areas of finance and strategy in the MBA and MFE programs and in Executive Education. He has also worked in competitive intelligence and litigation consulting and has advised consulting teams in finance, marketing, and strategy. His research interests lie at the intersection of law, finance, and psychology, in the area of business strategy and risk management. He is the recipient of teaching awards including the Earl F. Cheit Award for Outstanding Teaching, 2009; and the Haas EWMBA Graduate Instructor of the year, 2004-2005.
He received a B.A. (History, Politics, Philosophy, and Economics) and a B.S. Economics (Business Administration) from the University of Pennsylvania, where he continued his education as a University Scholar and graduate fellow, studying in the schools of Arts and Sciences, Business, and Law. He later pursued a J.D. at the George Mason University and an L.L.M at Berkeley’s Boalt Hall. He has taught undergraduate and graduate courses in all areas of business. Prior to arriving at the Haas School in 2005, he taught at Wharton, Duke, and the University of Virginia.
Awards & Honors
- UC Berkeley Presidential Teaching Fellow, 2009
- Earl F. Cheit Award for Outstanding Teaching, 2009
- Haas EWMBA Core Graduate Instructor of the year, 2004-2005
- John Olin Fellow, Boalt Hall, U of California, Berkeley, 2004-2005
- Robert Levy Fellow in Law and Economics, George Mason University School of Law, 1996-1999
- Mellon Fellow, University of Pennsylvania
- University Scholar, University of Pennsylvania