FinTech and AI

This course provides an introduction to the evolving use of technology in financial markets and applications. One area of focus is “blockchain” technology in financial transactions, markets, permanent historical records and cryptocurrencies. The other major area of focus is innovations such as peer-to-peer transactions and the use of artificial intelligence in evaluating and funding investments. Throughout we will consider the prospects for the success of the new technologies, asking questions such as: How revolutionary are the various parts of Fintech? What are the hidden pitfalls of the technology/business models to individuals, companies and/or society? How will major financial institutions and governments react? What changes are required in legal rules (including internationally) to accommodate Fintech? The course will require working with large data sets (the blockchain) and specific cryptocurrency implementations. While computer programming skills are not required as a pre-requisite, success in the course will require that students learn the basics of the computer science concepts of public-key cryptography, data verification, and simple programming structures (loops, branching).

The objective of this course is to equip you with the frameworks, tools, and methodologies necessary to build and/or be an educated user of quantitative models for financial decision making. The course is suitable for students seeking a career in finance, but also for students with broader interests who wish to strengthen their general modeling skills, and it does not require any quantitative background other than what is covered in the MBA core courses. Master mod¬eling frameworks such as regression analysis, Monte-Carlo simulation, opti¬mization, and binomial trees. Learn how to apply these frameworks in financial contexts such as portfolio management, term-structure estimation, capital budgeting, risk measurement, risk analysis in discounted cash flow models, and pricing of European, American, exotic, and real options. The modeling tools will be illustrated by applying them to a variety of real-world cases.
 

This class introduces students to AI models at the conceptual level and teaches how recent advances in AI can spur financial innovation for startups and corporations. The class relies on an analytical framework that combines financial frictions analysis and AI applications. Financial frictions provide opportunities for AI-driven FinTech solutions. The class covers the evolution of deep learning models in the last decade, discusses the cutting-edge AI applications, and helps students to identify new opportunities for value creation.