Master’s degree in Financial Mathematics and Technology – FinTech
The field of finance today is based on analyzing large volumes of data, making decisions under uncertainty, and using advanced computational tools. This requires a combination of economic understanding, mathematical depth, and computational ability. Such a combination makes it possible not only to analyze financial reality, but also to build models that explain it and operate within it with precision.
The Master’s program in Financial Mathematics and Technology is designed to meet this need and to train experts who understand both the economic and social aspects of financial activity and the mathematical and computational tools that underpin it. Today, financial mathematics plays a central role in financial, banking, and insurance institutions, investment firms, corporations, and public bodies that rely on mathematical models, stochastic processes, and computational methods for risk management and decision-making.
With the increasing use of artificial intelligence and big-data analysis methods, the need for deep mathematical knowledge in areas such as statistics, stochastic mathematics, optimization, and machine learning has grown stronger. The curriculum in financial mathematics combines theoretical depth with applied training: on the one hand, emphasizing complex mathematical foundations, and on the other, maintaining a direct connection to economic, financial, and technological applications.
The program is offered in a non-thesis track and in a thesis-based research track, with both theoretical and technological (FinTech) specializations. It is intended for graduates of exact sciences and engineering, as well as graduates of economics, accounting, and business administration. The structure of the studies is also adapted for working professionals, with classes concentrated on Sunday afternoons and Friday mornings.
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- What are the employment and career opportunities?
Graduates of the program integrate into institutions that employ mathematical and computational models for analysis, forecasting, and risk management, including:
• Financial and banking institutions
• Investment and insurance companies
• Corporations and government agencies
• FinTech, data analysis, and financial computing sectors- How is the curriculum structured?
The master’s program in Financial Mathematics and Technology (FinTech) includes 47 credits and is offered in a flexible structure that allows adaptation for students from various academic backgrounds.
The master’s program in Financial Mathematics includes 46 credits (this program has not been offered since the 2025–2026 academic year).
All students begin in the academic (non-thesis) track, while outstanding students who wish to do so may transfer to the research track (with thesis) after the first year, subject to approval by the program director or academic advisor.
The first semester of the program serves as a bridging semester: graduates of exact sciences or engineering take foundational courses in economics and management, whereas graduates of economics, accounting, or business administration complete core courses in applied mathematics. This structure allows all students to acquire a shared foundation and progress to advanced studies from a balanced starting point.
Program tracks:
- Theoretical track – focuses on mathematical methods and models in areas such as risk management and actuarial science.
- Technological track (FinTech) – emphasizes working with big data, data analysis and processing, and machine learning in a financial context.
Research track (with thesis):
- Financial Mathematics: 37 credit points of coursework (exempt from courses 88638, 88652, 88654, and one elective course). This program has not been offered since the 2025–2026 academic year
- Financial Mathematics and Technology: 39 credit points of coursework (exempt from courses 88650, 886210, 88636)
- Thesis (Financial Mathematics – registration for the thesis course 88-3000, formally 9 credit points
Financial Mathematics and Technology – registration for the thesis course 883001, formally 8 credit points
In addition, students are required to take foundational courses in Judaism and English according to the regulations of the Master’s Committee (recommended in the first year).
Note: Some courses are recognized for research ranking in the IDF and may be counted as a fourth year of study for research ranking purposes. For details, contact the program director.
Specialized courses:
Numerical Methods for Financial Mathematics – computational tools for fitting financial models to real data.
- Which courses are included in the degree?
Study Program for Students with a Bachelor’s Degree in Economics, Accounting, or Business Administration
Year 1
Course No. Course Name Semester A – Lec. Semester A – Ex. Semester B – Lec. Semester B – Ex. 88622 Introduction to Probability and Statistics 3 2 88625 Mathematics for Finance 3 2 886960 Introduction to Programming in Python (*) 2 2 886200 Financial Models 3 1 88623 Stochastic Processes 3 1 88629 Option Pricing 2 1 Year 2
Course No. Course Name Semester A – Lec. Semester A – Ex. Semester B – Lec. Semester B – Ex. 88624 Statistics and Data Analysis 2 1 88650 Seminar in Financial Mathematics 2 886210 Risk Management and Time Series 2 886970 Data Processing, Analysis, and Presentation 2 1 886972 Big Data Analysis and Processing 2 88636 Numerical Methods for Finance 3 1 88656 Seminar in Financial Technology 2 886971 Applied Machine Learning 2 1 (*) Students with prior Python programming experience may replace course 886960 with “Python Workshop” 886961 (2 credits) plus elective courses totaling 2 credits (subject to approval by the program head or academic advisor).
Study Program for Students with a Bachelor’s Degree in Exact Sciences or Engineering
Year 1
Course No. Course Name Semester A – Lec. Semester A – Ex. Semester B – Lec. Semester B – Ex. 88627 Introduction to Finance 2 2 886280 Introduction to Microeconomics 1 1 886281 Introduction to Macroeconomics 1 1 886960 Introduction to Programming in Python (*) 2 2 88631 Introduction to Probability and Statistics (**) 1 88632 Mathematics for Finance (**) 1 886200 Financial Models 3 1 88623 Stochastic Processes 3 1 88629 Option Pricing 2 1 Year 2
Course No. Course Name Semester A – Lec. Semester A – Ex. Semester B – Lec. Semester B – Ex. 88624 Statistics and Data Analysis 2 1 88650 Seminar in Financial Mathematics 2 886210 Risk Management and Time Series 2 886970 Data Processing, Analysis, and Presentation 2 1 886972 Big Data Analysis and Processing 2 88636 Numerical Methods for Finance 3 1 88656 Seminar in Financial Technology 2 886971 Applied Machine Learning 2 1 (*) Same substitution option as above.
(**) Self-study courses. Grades are usually based on a final paper.
- What practical experiences are included in the degree studies?
As part of the program, there is an experts’ workshop in which you will meet weekly with specialists from academia and industry. The workshop provides exposure to current applications of financial mathematics, fintech, risk management, and the analysis of economic systems, and connects the material learned in class with real-world professional challenges.
- What are the admission requirements?
Admission requirements for the non-thesis track: a bachelor's degree in the exact sciences (including mathematics) or in economics and business administration (single-major or major), with a GPA of 80 or above.”
- How can you contact us?
Interested in learning more about the Master’s program in Financial Mathematics and Technology – FinTech
Program Advisor: Prof. Baruch Barzel – baruchbarzel@gmail.com
Graduate Degrees Coordinator: Dan Rotkevich – rotkovd@biu.ac.il
Phone: +972-3-5318408
