Financial Technology Major with Concentration in Financial Mathematics

Mathematics (5/3 units)

Mathematics must include 2/3 units Calculus, 2/3 units Statistics and 1/3 unit from MA 2071 Matrices and Linear Algebra I, MA 2072 Accelerated Matrices and Linear Algebra I, or MA 2073 Matrices and Linear Algebra II.

Computer Science (1/3 Unit)

Computer Science – CS 1004, CS 1101 or CS 1102 is recommended. (CS 2022 and CS 3034 are not accepted)

Basic Science (2/3 Unit)

Biology, Chemistry, Geology, Physics

Social Science (2/3 unit)

ECON 1110 and ECON 1120 required.

Business Foundation Courses (4/3 Units)

FinTech Foundation Courses (3/3 Unit)

The FinTech component of the curriculum is designed to provide foundational financial courses that will give students the financial preparation needed for the technical areas of the program. The FinTech core courses also introduces the student to technologies (FIN 3300) and analytical tools (FIN 3310) that firms in the financial services industry can use to disrupt the traditional delivery of financial services.

Technical Courses (3/3 Unit)

The Technical component equips students with a working knowledge of Artificial Intelligence (AI – MIS 3730), Machine learning (ML – MIS 3787), Blockchain technologies (MIS 2300), and an understanding of how these technologies can revolutionize finance. Banks and firms can use AI and ML in the rapidly growing FinTech industry to predict customer behavior or habits via Apps that integrate various AI and ML techniques. These courses also discuss ethical uses of these technologies and tools so that students learn to use them appropriately. These tools allow the user to gain detailed insights into their customers.

Analytical Courses (3/3 Unit)

The Analytical core introduces students to popular data analysis tools for decision-making. The Analytical component equips students with the applied statistical and modeling techniques needed to analyze and make predictions and inferences from complex real-world financial data. The empirical tools developed in the Analytical core - regression, classification/clustering; sampling methods (bootstrap and cross-validation); and decision tree learning will be vital skills needed for the respective concentrations.

Select two from: ETR 1100, MIS 3010, 0BC 1010 or OBC 4367

Select four from: MA 2210, MA 2211, MA 2212, MA 2621, MA 3231, MA 3233, MA 4235, MA 4237, MA 4365, MA 464X.

The MQP must have a business focus related to FinTech.