Computational Finance MSc

London, Bloomsbury

The rising sophistication of the financial sector is bringing a great demand for experts with skills across mathematics, finance, statistics and computer science. The Computational Finance MSc produces talented quantitative analysts or ‘quants’ in these areas, in just one year. This fast-paced and innovative programme is taught at UCL Computer Science, a renowned centre of academic excellence, with world-class credentials in computational statistics and machine learning.

UK students International students
Study mode
UK tuition fees (2024/25)
Overseas tuition fees (2024/25)
1 calendar year
Programme starts
September 2024
Applications accepted
Applicants who require a visa: 16 Oct 2023 – 05 Apr 2024

Applications closed

Applicants who do not require a visa: 16 Oct 2023 – 30 Aug 2024
Applications close at 5pm UK time

Applications open

Entry requirements

A minimum of an upper second-class UK Bachelor's degree (or an international qualification of an equivalent standard) in a relevant discipline with a strong quantitative component evidenced by good performance in mathematics and statistics examinations. Good performance is defined as scores in these subjects not falling below a UK upper second-class or international equivalent level. There is not an exhaustive list of relevant disciplines, but individuals with a background in mathematics, statistics, physics, computer science, engineering, economics, or finance are encouraged to apply.

The English language level for this programme is: Level 2

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

Further information can be found on our English language requirements page.

This programme is suitable for international students on a Student visa – study must be full-time, face-to-face, starting September.

Equivalent qualifications

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.

International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree

As a student on the Computational Finance MSc, you will learn advanced quantitative, modelling and programming skills, which are essential for quant roles in trading, research, regulation, and risk. This applied taught postgraduate programme is distinctive in that it provides a combination of finance, mathematics, statistics, and computer science.

Computational finance is at the intersection of mathematics, statistics, computer science, finance and economics. Elevating your skills in these disciplines is essential if you want to make your mark as a quant in a large bank, hedge fund or financial regulator, or in the world of fintech and innovative start-ups.

You will learn from our world-leading experts in this field. The syllabus is constantly reviewed to stay ahead of the trends; core modules span financial engineering and numerical methods for finance, to data science and machine learning for finance.

Optional modules allow you to dive deeper into specific areas of interest, such as algorithmic trading, market microstructure, blockchain technologies, the management of markets, systemic and operational risk, numerical optimisation, and financial market modelling and analysis. You will conclude your experience with a project that brings an opportunity to work with an industry partner on a real-world problem, or to delve into a research project supervised by one of our leading academics.

This programme gives you key skills that will enable you to pursue a career as a ‘quant’, while you immerse yourself in London life and the benefits of living in a global financial centre.

Who this course is for

The Computational Finance MSc requires previous studies in a quantitative subject which includes exams in mathematics. This should cover calculus and linear algebra, and optionally also differential equations, probability, statistics, econometrics and similar.

Typically, applicants’ undergraduate degrees are in mathematics, statistics, physics, engineering, computer science (with exams in mathematics), economics or finance. If you aim to work as a ‘quant’ in finance, you will need a desire to extend your skillset with an applied, computational focus.

What this course will give you

UCL is ranked 9th globally in the latest QS World University Rankings (2024), giving you an exciting opportunity to study at one of the world’s best universities.

UCL Computer Science is recognised as a world leader in teaching and research. The department was ranked 1st in England and 2nd in the UK for research power in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF) You will learn from leading experts at the forefront of computer science innovation.

Additionally, the UCL Computational Finance MSc has been ranked 2nd in the UK, 6th in Europe and 24th in the world in the 2023 Quant Finance Master’s Guide, which assesses the quality of quantitative finance programmes around the world.

The location in the global financial centre of London coupled with the Department’s extensive links with industry in the City give you ample opportunities for contact with potential future employers, as well as opportunities for practical, hands-on experience with these companies through the UCL Industry Exchange Network (IXN).

The foundation of your career

Graduates of this programme go on to work as quantitative analysts, quantitative traders or quantitative developers, plus a range of other jobs in asset allocation, risk management, fintech, regulation, or research for a large spectrum of employers.

They work for large banks such as Credit Suisse and JP Morgan, regulators such as the Bank of England and the Financial Conduct Authority, hedge funds and fintech companies, or they stay in academia to pursue a PhD. Altogether, the options for graduates of the Computational Finance MSc are exciting and varied.


In a programme that embraces mathematics, statistics, finance and computer science in equal measure, you can expect to acquire a combination of highly sought-after skills currently needed in the financial industry. You will graduate with advanced quantitative, modelling and programming skills, which are essential for ‘quant’ roles in trading, asset allocation, risk management, fintech, regulation and research.


UCL is proud to support innovation and link our students and research directly to real-world business applications. From internships to solving complex problems with commercial partners, UCL Engineering has a collaborative, innovative spirit at its core.

As a student and later as a graduate, you will have access to a UCL Engineering careers events programme, connecting you with employers and alumni. This programme provides invaluable insight into the reality of different roles, sectors, and current application processes.

Entrepreneurial minds thrive at UCL. For example, UCL’s IDEALondon was the first innovation centre led by a university in London, and incubates companies post-seed to reach technical and business milestones. Our academic and industrial networks provide a safe and supportive environment to grow a company.

Teaching and learning

The programme’s core curriculum is typically delivered through a combination of lectures, tutorials, and lab classes, as well as directed and self-directed learning supported by teaching materials and resources, published through each module’s online virtual learning environment. Each module employs a teaching strategy that aligns with and supports its intended learning outcomes.

You will be assessed through a range of methods across the programme, which will vary depending on any optional or elective module choices. The programme’s core curriculum is typically assessed by methods including coursework, programming tests, individual and group projects, class tests, written exams, oral assessments, and a final research project/dissertation.

Contact time takes various forms, including lectures, seminars, tutorials, project supervisions, demonstrations, practical classes and workshops, visits, placements, office hours (where staff are available for consultation), email, videoconferencing, or other media, and situations where feedback on assessed work is given (one-to-one or in a group).

Each module has a credit value that indicates the total notional learning hours a learner will spend to achieve its learning outcomes. One credit is considered equal to 10 hours of notional learning, which includes all contact time, self-directed study, and assessment.

The contact time for each of your 15 credit taught modules will typically include 22-30 hours of teaching activity over the term of its delivery, with the balance then comprised of self-directed learning and working on your assessments. You will have ongoing contact with teaching staff via each module’s online discussion forum, which is typically used for discussing and clarifying concepts or assessment matters and will have the opportunity to access additional support via regular office hours with module leaders and programme directors.

Your research project/dissertation module is 60 credits and will include regular contact with your project supervisor(s), who will guide and support you throughout your project. You will dedicate most of your time on this module to carrying out research in connection with your project and writing up your final report.


The Computational Finance MSc is a one-year programme.

In term 1, you will be introduced to financial engineering and to numerical methods in finance. You will choose from optional topics which include probability theory and stochastic processes, market risk and portfolio theory, market microstructure, operational risk management for financial institutions, financial institutions and markets, and blockchain technologies.

In term 2, you will study data science and machine learning with applications in finance. You will choose from optional topics that include algorithmic trading, networks and systemic risk, applied computational finance, financial market modelling and analysis, numerical optimisation, and advanced machine learning in finance. You will also begin preparation for your final research project/dissertation.

In term 3, you will focus on any examinations that take place in the main examination period and undertake your final research project/dissertation; the project is usually done within a placement organised by UCL at a bank, hedge fund, fintech, or other financial services firm located in London, or sometimes at a regulatory authority.

Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability are subject to change. Modules that are in use for the current academic year are linked for further information. Where no link is present, further information is not yet available.

Students undertake modules to the value of 180 credits. Upon successful completion of 180 credits, you will be awarded an MSc in Computational Finance.


Details of the accessibility of UCL buildings can be obtained from AccessAble Further information can also be obtained from the UCL Student Support and Wellbeing team.

Online - Open day

Graduate Open Events: Department of Computer Science

Join us for a live online information session to hear from Computer Science staff. We will cover areas such as the general admission process, careers support, and industry links/placements. There will also be an opportunity for you to ask staff and current students any questions you may have. Two sessions will run for this event. These sessions are the same and are repeated to cater to people in different time zones.

Fees and funding

Fees for this course

UK students International students
Fee description Full-time
Tuition fees (2024/25) £31,100
Tuition fees (2024/25) £44,400

The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website:

Additional costs

All full time students are required to pay a fee deposit of £2,000 for this programme. All part-time students are required to pay a fee deposit of £1,000.

Students will require a modern computer (PC or Mac) with minimum specifications 8GB RAM and 500GB SSD storage. A computer with the stated specifications is estimated to cost £500 or greater.

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs.

Funding your studies

For more information about funding opportunities for UCL Computer Science taught postgraduate programmes, please see the department's scholarships webpage.

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

Squarepoint Bursary in Computational Finance

Value: £20,000 (1 year)
Criteria Based on financial need
Eligibility: UK

UCL East London Scholarship

Value: Tuition fees plus £15,700 stipend ()
Criteria Based on financial need
Eligibility: UK

UCL Friends & Alumni Association scholarship for Machine Learning

Deadline: 3 June 2024
Value: $20,000 (1 year)
Criteria Based on both academic merit and financial need
Eligibility: EU, Overseas

Next steps

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

There is an application processing fee for this programme of £90 for online applications and £115 for paper applications. Further information can be found at Application fees.

When we assess your application we would like to learn:

  • why you want to study Computational Finance at graduate level
  • why you want to study Computational Finance at UCL
  • what particularly attracts you to the chosen programme
  • how do your academic and professional background and skills meet the demands of this challenging programme
  • where would you like to go professionally with your degree

Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.

Due to competition for places on this programme, no late applications will be considered. Students with visa requirements or applying for scholarships are advised to apply early.

Please note that you may submit applications for a maximum of two graduate programmes (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2024-2025

Got questions? Get in touch

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