| Course Level: | Master's | |
|---|---|---|
| Course Duration: | 2 Years | |
| Course Language | English | |
| Required Degree | 3 Year Bachelor’s Degree | |
Korea University’s MS in Financial Engineering offers a rigorous, interdisciplinary curriculum combining finance, mathematics, statistics, and computer science to develop strong quantitative and analytical skills. As one of South Korea’s top universities, it provides access to cutting-edge research, experienced faculty, and state-of-the-art resources. Located in Seoul, a global financial hub, students benefit from proximity to leading financial institutions, internship opportunities, and industry connections. The program emphasizes practical applications in risk management, derivatives, and financial modeling, preparing graduates for careers in investment banking, asset management, fintech, and consulting. Its global reputation and strong alumni network enhance career prospects worldwide.
Category |
Details |
|---|---|
|
Program Name |
Master of Science (MS) in Financial Engineering |
|
Degree Awarded |
MS in Financial Engineering |
|
Course Duration |
2 years (4 semesters, full-time) |
|
Language of Instruction |
English (some elective courses may be offered in Korean) |
|
Yearly Tuition Fees |
Approx. USD 7,000 – 8,500 (KRW 9–11 million) |
|
Total Tuition Fees |
Approx. USD 14,000 – 17,000 (KRW 18–22 million) |
|
Total Program Cost |
Around USD 16,000 – 20,000 including living expenses |
|
Eligibility |
Bachelor’s degree in finance, economics, mathematics, statistics, engineering, or related fields |
|
Admission Requirements |
Online application, academic transcripts, bachelor’s degree certificate, English proficiency test (TOEFL/IELTS), recommendation letters, statement of purpose, CV/resume, and sometimes GRE/GMAT (recommended but not always mandatory) |
|
Application Intake |
Spring (March) & Fall (September) |
|
Scholarship |
KU Graduate School Scholarships (tuition reduction based on academic merit); Korean Government Scholarship (KGSP) opportunities available |
|
Career Prospects |
Quantitative analyst, risk manager, investment banker, asset manager, data analyst, fintech specialist, financial consultant, academic researcher |
|
Curriculum Structure |
Core courses: Financial Mathematics, Stochastic Processes, Derivatives Pricing, Risk Management, Computational Finance. Electives: Machine Learning in Finance, Big Data Analytics, Portfolio Theory, Financial Econometrics. Includes research thesis or project. |
