IDS 690 / MATH 590-02 – Special Topics: Case Studies in Quantitative Finance

Course topic for Fall, 2023: Data Science in Retail Banking

The purpose of this course is to introduce students to various applications of data science and quantitative techniques in the banking and financial industry. Through hands-on case studies, students will be exposed to real-world projects, the most pressing problems and the latest innovations in the field of quantitative finance and understand how machine learning/data science techniques and other computational skills are combined with optimization methods to solve real-word finance problems. Students will experience the whole process of solving quantitative problems in banking and finance from start to finish, i.e., from problem formulation, data structuring, predictive learning and estimation, strategy and decision optimization to solution evaluation, proposal communication and results monitoring.

Because quantitative finance is such a broad subject, topics will rotate each semester. In 2023 fall semester, this course will focus on retail and commercial banking and lending. It aims to bridge the gap between relevant college courses and practices in banking and lending. Topics covered in the course may include assessing risk and profit in bank’s credit card, mortgage and other consumer lending products. Students will receive real-world quantitative training by undertaking real business projects and solving real business problems in a simulated work environment similar to the real world of the banking and lending industry.

Students are expected to have some knowledge of machine learning, statistical methods, data coding and economics, but this is not required. Intellectual curiosity, desire to learn and independent study habits are the most important prerequisites. Hands-on team projects will account for the major part of a student’s final grade.

The course will be taught by Dr. Hengzhong Liu who has held senior and executive level roles at Bank of America, Citigroup and two other major US banks, where he managed decision science and quantitative risk teams in the retail as well as wholesale sectors. He received his PhD in Financial Economics from the Graduate Center of City University of New York. His publications include books and papers in English and Chinese on financial markets, economics, and the Chinese economy.