Naveen Jindal School of Management
Master of Science in Financial Technology and Analytics
36 semester credit hours minimum
Faculty
Professors: Alain Bensoussan, Umit G. Gurun, Vikram Nanda, Suresh Radhakrishnan, Michael J. Rebello, Harold Zhang, Zhiqiang (Eric) Zheng
Associate Professors: Nina Baranchuk, Zhonglan Dai, Michael Hasler, Robert L. Kieschnick Jr., Harpreet Singh, Han (Victor) Xia, Yexiao Xu, Feng Zhao
Assistant Professor: Hongchang Wang
Clinical Professor: John Barden
Clinical Associate Professor: Carolyn Reichert
Clinical Assistant Professor: Liping Ma
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 covering 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 Foundations of Finance
FTEC 6303 Asset Pricing and Management
FTEC 6305 Mathematics in Finance
FTEC 6307 InsurTech Foundations and Applications
FTEC 6310 Financial Information and Analytics
FTEC 6311 Robotics and Financial Technology
FTEC 6312 Financial Applications of Blockchain Technology
FTEC 6313 Cloud Computing and Data Engineering
FTEC 6314 Financial Applications of Web Technologies
FTEC 6319 Foundations of Machine Learning
FTEC 6320 Statistical Methods for Financial Analytics
FTEC 6331 Risk Evaluation and Management
FTEC 6334 Financial Applications of Machine Learning
FTEC 6335 Applications of Machine Learning and AI in Insurance
FTEC 6340 Decentralized Insurance
FTEC 6V95 Special Topics in InsurTech and Analytics
FTEC 6V96 Special Topics in Financial Data Analytics
FTEC 6V97 Special Topics in Financial Technology
FTEC 6V98 Financial Technology and Analytics Internship
FTEC 6V99 Special Topics in Financial Technology and Analytics
Graduate Certificates
Graduate Certificate in Fintech
12 semester credit hours
Faculty
Overview
The Graduate Certificate in Fintech (Financial Technology) focuses on certain key financial technologies: blockchain technologies and various types of robotic technologies. These technologies are becoming ever more important in financial markets. Students learn how to apply these technologies to provide various financial services.
Course Requirements
Students interested in just the Graduate Certificate in Fintech can enroll in the Master of Science of Financial Technology and Analytics program as a part-time student. However, they would need to identify this interest in this certificate in their application. Students earn this certificate by completing four of the following courses, in consultation with the program director, with a "B" or better.
FTEC 6310 Financial Information and Analytics
FTEC 6311 Robotics and Financial Technology
FTEC 6312 Financial Applications of Blockchain Technology
FTEC 6313 Cloud Computing and Data Engineering
FTEC 6314 Financial Applications of Web Technologies
FTEC 6340 Decentralized Insurance
FTEC 6V97 Special Topics in Financial Technology
FTEC 6V99 Special Topics in Financial Technology and Analytics
Academic certification programs follow the same application and admission processes as graduate degree programs. All dates and deadlines can be located in the UTD Academic Calendar. Failure to register in advance and on-time results in a late fee. Students may contact the director of the M.S. in Financial Technology and Analytics for more details.
Graduate Certificate in Financial Data Science
12 semester credit hours
Faculty
Overview
The Graduate Certificate in Financial Data Science focuses on the analytical technologies applied to the analysis of financial data for decision making. These technologies include SQL and NoSQL databases, Natural Language Processing, Econometrics, and Machine Learning. These technologies are becoming ever more important in the provision of financial services. Students learn how to use these technologies to analyze financial data in support of financial decisions.
Course Requirements
Students interested in just the Graduate Certificate in Financial Data Science can enroll in the Master of Science of Financial Technology and Analytics program as a part-time student. However, they would need to identify this interest in this certificate in their application. Students earn this certificate by completing four of the following courses, in consultation with the program director, with a "B" or better.
FTEC 6310 Financial Information and Analytics
FTEC 6319 Foundation of Machine Learning
FTEC 6320 Statistical Analysis for Financial Analysis
FTEC 6334 Financial Applications of Machine Learning
FTEC 6335 Applications of Machine Learning and AI in Insurance
FTEC 6V96 Special Topics in Financial Data Analytics
FTEC 6V99 Special Topics in Financial Technology and Analytics
Academic certification programs follow the same application and admission processes as graduate degree programs. All dates and deadlines can be located in the UTD Academic Calendar. Failure to register in advance and on-time results in a late fee. Students may contact the JSOM advising office for details.
Graduate Certificate in Insurance Technology and Analytics
12 semester credit hours
Faculty
Overview
The Graduate Certificate in Insurance Technology and Analytics (InsurTech) focuses on the analytical technologies applied to the analysis and provision of insurance. These technologies are becoming ever more important in the pricing and provision of insurance products. These technologies range from artificial intelligence, Internet of Things, blockchains, and cybersecurity. Students learn how to use these technologies to support the provision, design, and pricing of insurance products and services.
Requirements
Students interested in just the Graduate Certificate in Insurance Technology and Analytics can enroll in this program as part-time students in the Master of Science of Financial Technology and Analytics program. However, they would need to identify this interest in their application and demonstrate a sufficient background to profit from pursuing this certificate. Students lacking an exposure to computer programming and statistics may be asked to fill in their gaps before taking the course work to complete the certificate.
Students earn this certificate by completing the courses proscribed by the program director at the beginning of their program with a "B" or better.
FTEC 6307 InsurTech Foundations and Applications
FTEC 6310 Financial Information and Analytics
FTEC 6319 Foundation of Machine Learning
FTEC 6335 Applications of Machine Learning and AI in Insurance
FTEC 6340 Decentralized Insurance
FTEC 6V95 Special Topics in InsurTech and Analytics
Academic certification programs follow the same application and admission processes as graduate degree programs. All dates and deadlines can be located in the UTD Academic Calendar. Failure to register in advance and on-time results in a late fee. Students may contact the director of the M.S. in Financial Technology and Analytics for more details.