BUS-F355 Topics in Finance: Applied FinTech

• 16 weeks
• 3 credits
• Prerequisite(s): BUS-F 370 or BUS-F 304 with a grade of C or higher

This class introduces students to the world of fintech. The course begins by discussing the value of information in financial markets and compares the role of information in traditional banking vs. fintech banking. Students will then learn how to predict a range of financial outcomes, especially home prices and loan defaults, by applying common machine learning techniques such as: (i) K-means, (ii) principal components, (iii) linear regressions, (iv) logistic regressions, (v) regularization, (vi) k-nearest neighbors, and (vii) decision trees. The class concludes with an overview of the fintech landscape and the role of management in the fintech sector. Students will learn to apply their knowledge through both data analysis projects and case studies.