Naveen Jindal School of Management
Master of Science in Financial Technology and Analytics
36 semester credit hours minimum
Faculty
Professors: Ashiq Ali , Alain Bensoussan , Theodore E. Day , Vikram Nanda , Suresh Radhakrishnan , Michael J. Rebello , Harold Zhang , Zhiqiang (Eric) Zheng
Associate Professors: Nina Baranchuk , Zhonglan Dai , Robert L. Kieschnick Jr. , Kelsey D. Wei , Han (Victor) Xia , Yexiao Xu , Yuan Zhang
Assistant Professor: Xiaoxiao Tang
Clinical Professors: John Barden , Randall S. Guttery , Jeffrey Manzi
Clinical Associate Professor: Carolyn Reichert
Clinical Assistant Professor: Liping Ma
Senior Lecturer: Debra Richardson
Degree Requirements
The Master of Science in Financial Technology and Analytics (MS FTEC) at the Naveen Jindal School of Management is a STEM (Science, Technology, Engineering and Mathematics) cohort degree program that requires a minimum of 36 semester credit hours. This Fintech program provides students with the practical and theoretical knowledge needed to pursue careers involving digital financial technologies and financial data analytics. The program is designed for students with or without previous educational background in finance, but with a proclivity toward more computer-based approaches to financial issues.
Students completing this program will gain a knowledge of both finance and the key digital and analytical technologies used in finance. For example, students completing the program will know how use robotic process agents, build blockchains with smart contracts, create cryptocurrencies or tokens for payment systems, use statistical methods for analyzing financial data, and apply machine learning to financial issues. While the full-time program is a cohort program, a part-time program for working professionals is also offered. Both programs only begin each fall. Special tuition, fees and admissions requirements apply since the program is supported entirely by participant tuition/fees.
To apply for this degree program, an undergraduate degree is required (all majors are considered). Students must maintain a cumulative 3.0 grade-point average (GPA) in all graduate courses taken in the degree program, excluding program prerequisites, to qualify for the MS degree.
Prerequisites
Students pursuing the Master of Science in Financial Technology and Analytics degree program are required to have completed course work in calculus, linear algebra, probability/statistics, and programming with a grade of "B" or better. Applicants who have not satisfied these requirements will be considered on a case-by-case basis.
Course Requirements
Core Courses: 36 semester credit hours
Program director develops a program of study for students each term based on courses listed below.
FTEC 6002 Financial Analytics Training and Internship
FTEC 6301 Financial Accounting Information and Analysis
FTEC 6302 Financial Markets and Institutions
FTEC 6303 Asset Pricing and Management
FTEC 6304 Corporate Finance and Risk Management
FTEC 6305 Introduction to Mathematics in Finance
FTEC 6306 Advanced Mathematics in Finance
FTEC 6310 Financial Information and Analytics
FTEC 6311 Financial Technology I
FTEC 6312 Financial Technology II
FTEC 6313 Cloud Computing and Cyber Security
FTEC 6319 Mathematics for Financial Analytics
FTEC 6320 Statistical Methods for Financial Analytics
FTEC 6321 Advanced Statistical Methods for Financial Analytics
FTEC 6331 Risk Evaluation and Management
FTEC 6334 Financial Applications of Machine Learning
FTEC 6V98 Financial Technology and Analytics Internship
FTEC 6V99 Special Topics in Financial Technology and Analytics