Financial Mathematics

Course Information

BSc (Hons) (NFQ Level 8)

Full Time - Undergraduate Studies

CAO Code: DN200 MPG
CAO Points Range 2016: 510 - 625
Length of Course: 4 Years
Average Intake: 402

Leaving Certificate:

Passes in six subjects including English, Irish, Mathematics (Min O3/H6 in LC or equivalent), one laboratory science subject (Min O3/H6 in LC or equivalent.) Applied Mathematics or Geography may be used instead of a laboratory science subject) & two other recognised subjects.

You must obtain a minimum of Grade H5 in two subjects and a minimum of Grade O6/H7 in the remaining four subjects.

Special Entry Recommendations: We recommend that all students in Financial Mathematics should have a minimum Grade H3 in Leaving Certificate Higher Level Mathematics or equivalent.

Click below for equivalent entry requirements information for:

Why is this course for me?

If you have a strong interest in Mathematics, enjoy problem solving and are interested in how Mathematics is used in business and finance, this degree in Financial Mathematics will give you an understanding of the mathematical theories that underpin financial models, as well as computational expertise in the algorithms that price financial products. One example of a financial model included in the course is the Black-Scholes option pricing model, dating from 1973, which is one of the earliest equations developed and used to price options. Implementations of these models, including computer programming, form a key part of the course.

Career & Graduate Study Opportunities

Graduates with training in Financial Mathematics work in fields as diverse as:

  • Quantitative positions in the financial sector
  • Risk modeling in banking and insurance
  • Computing in business, technology, research and academia

Graduates can also pursue a range of MSc or PhD programmes such as the MSc in Actuarial Science, MSc in Quantitative Finance, or an MSc in Statistics.

What Will I Study

This is a sample pathway for a degree in Financial Mathematics. Sample topics include probability theory, statistical modelling, computational science, fundamentals of actuarial and financial mathematics, advanced corporate finance, stochastic analysis and actuarial statistics.

First Year

  • Statistics
  • Applied & Computational Mathematics
  • Mathematics
  • Optional Science modules
  • Elective modules

Second Year

  • Applied & Computational Mathematics
  • Mathematics
  • Statistics
  • Finance
  • 1 other Science subject
  • Elective modules

Third Year

  • Financial Mathematics
  • Elective modules

Fourth Year

  • Financial Mathematics (modules include computational finance, stochastic models, Bayesian analysis, and advanced corporate finance)

All Science courses are full time, with many student timetables running from 9.00am to 5.00pm or later. Depending on the subject choices, a weekly timetable can include lectures, practicals and tutorials.

Assessment varies with each module but may comprise continuous assessment of practicals, written exams and online learning activities.

First Year

Second Year

International Study Opportunities

Students may apply to study abroad for a semester or year in third year in a range of worldwide universities. Potential universities include:

  • University of Texas at Austin, USA
  • University of California, USA
  • University of Perugia, Italy
  • University of Konstanz, Germany


“Security of financial transactions is extremely important in today’s society. My research interests include the area of Elliptic Curve Cryptography, which uses the mathematical theory of elliptic curves in real-world applications of cryptography. I am the Director of the Claude Shannon Institute, where we have a team doing cutting-edge research in cryptography and coding theory. My research team recently set a world record cryptographic break, which demonstrated possible vulnerabilities in encryption technology used in areas such as financial transactions. This degree in Financial Mathematics is taught by mathematicians and statisticians with a broad range of expertise, such as Bayesian statistics and stochastic analysis, topics which are used constantly in the financial sector.”
Professor Gary McGuire, Head of UCD School of Mathematics & Statistics