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Computational Finance MSc

London, Bloomsbury

Help build a successful career as a quantitative analyst on this one-year MSc programme in Computational Finance. You'll benefit from UCL’s renowned expertise in computational statistics and machine learning to acquire the advanced quantitative, modelling and programming skills essential for ‘quant’ roles in trading, research, regulation and risk management.

UK students International students
Study mode
Full-time
UK tuition fees (2025/26)
£33,000
Overseas tuition fees (2025/26)
£47,100
Duration
1 calendar year
Programme starts
September 2025
Applications accepted
Applicants who require a visa: 14 Oct 2024 – 04 Apr 2025
Applications close at 5pm UK time

Applications open

Applicants who do not require a visa: 14 Oct 2024 – 29 Aug 2025
Applications close at 5pm UK time

Applications open

Apply for this course

Entry requirements

A minimum of an upper second-class UK bachelor's degree (or international qualification of an equivalent standard) in a relevant discipline with a strong quantitative component evidenced by good performance in mathematics and statistics exams, i.e. with marks in these subjects not 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, physics, statistics, 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 the financial sector becomes increasingly sophisticated, there is a growing demand for experts with skills spanning mathematics, finance, statistics, and computer science. 

Join us on this fast-paced MSc to lay the groundwork for a fulfilling career as a quantitative analyst or quant in just a year.

You join the UCL Computer Science community — a world-renowned centre in computational statistics and machine learning — to learn advanced quantitative, modelling and programming skills alongside our experts. 

The syllabus is constantly reviewed to stay ahead of trends. Modules include financial engineering, numerical methods, data science, and machine learning for finance, with optional modules in algorithmic trading, market microstructure, numerical optimisation, networks and systemic risk, and blockchain technologies. 

This programme is distinctive in that it covers a mix of mathematics, finance, statistics and computer science. Computational finance sits at the intersection of these subjects. Elevating your skills in all these areas will put you one step ahead when going for quant jobs.

Who this course is for

This programme is ideal for you if you have an undergraduate degree in mathematics, statistics, physics, engineering, computer science (with exams in mathematics), economics or finance. 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.

If you aim to work as a ‘quant’ in finance, you will need a desire to extend your skillset with an applied, computational focus.

Read about what it takes to study for a Master's at UCL

What this course will give you

This programme offers you the following benefits and opportunities. 

Top-ranked MSc programme: Our Computational Finance MSc has been ranked 3rd in the UK (QuantNet), 6th in Europe, and 24th globally (2023 Risk.net Quant Finance Master’s Guide). These rankings aim to assess the quality of quantitative finance programmes. 

Recognition from a top-ranked university: UCL is consistently ranked among the best universities globally (ranked 9th in the QS World University Rankings 2025), providing you with a prestigious qualification that is highly regarded by employers worldwide. UCL was named The Times and Sunday Times University of the Year 2024.

High-quality education from leading experts: Learn from world-renowned academics who are at the forefront of computer science innovation. UCL Computer Science is recognised for its research excellence, ranked first in England and second in the UK for research power in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF 2021). 

Real-world experience through project work: Apply your knowledge and skills in practical settings with a substantial research or engineering project. Many of these projects are conducted in collaboration with industry partners, giving you valuable hands-on experience and industry insights.

Strong employability with high employment rates and starting salaries: Our graduates are highly sought after in the job market, thanks to UCL's strong reputation and the practical, industry-focused skills gained during the programme. You'll be well-prepared to enter a variety of high-demand roles in Computational Finance.

Enhanced research skills: The research-based components of the programme will equip you with strong analytical and problem-solving abilities, preparing you for potential doctoral studies or research-intensive roles in industry.

Location and industry links: Situated in the global financial hub of London and benefiting from the department's extensive industry connections in the City, you will have numerous opportunities to connect with potential future employers.

Read about what you'll get out of a graduate programme

The foundation of your career

Graduates have found employment with 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.

During my course, I had the chance to work with the International Swaps and Derivatives Association (ISDA) for my Master's project industry placement. This role offered me the experience of working in their offices, engaging with their staff, and gaining direct insights into the industry.

Headshot of alumni student Finn on black background

Finn Casey Fierro

MSc Computational Finance

Read more about Finn

Employability

You can expect to acquire a combination of highly sought-after skills currently needed in the financial industry on this programme, which embraces mathematics, statistics, finance and computer science in equal measure.

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.

Networking

You’ll have regular opportunities to connect, collaborate and network with peers and members of academia and industry as part of your Master’s, particularly through collaborative project work and research seminars.

  • As a student and later as a graduate, you will have access to the UCL 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. 
  • UCL also has a large number of clubs and societies, which can be an effective way to connect with peers who share similar interests and career goals. 
  • Be part of a university where entrepreneurial minds thrive. Our academic and industrial networks provide a safe and supportive environment if you want to grow your own company. 
  • London’s Tech scene is vibrant and has regular networking events.

Teaching and learning

This programme is delivered through a combination of lectures, tutorials, lab classes. Your self-directed learning is supported by online resources.

You will be assessed through various methods, including coursework, projects, exams, and a final research project/dissertation.

For full-time students, typical contact hours are approximately 16-18 contact  hours per teaching week, depending on module selections and timetabling. These contact hours include lectures, seminars, workshops, and tutorials, office hours and other events.

Outside of these sessions, students are expected to engage in significant self-directed study and complete assessments. Formal teaching and self-directed study together amount to a workload comparable to a full-time job, roughly 35-40 hours per week in total.

Modules

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.

Compulsory modules







Optional modules












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.

Accessibility

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 Services team.

Where you'll study

Two small wheeled remote control vehicles on floor with group of students in background

UCL Computer Science boasts state-of-the-art facilities that are designed to enhance your learning experience. Our recently renovated labs, with 55 high-performance PCs, ample laptop space, and versatile power options, create an optimal study environment. UCL East is home to our Intelligent Robotics Lab, a hub of innovation and cutting-edge technology. Facilities include the new Innovation Lab, which combines a computer cluster, advanced manufacturing equipment (such as 3D printers, laser cutters, and power tools), and an electronics manufacturing and testing area, all within a single space. The lab also features a motion capture system for conducting experiments on robot and human movement. Additionally, UCL boasts an award-winning Student Centre and 18 specialist libraries, ensuring you have access to top-tier resources and study spaces.

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Fees and funding

Fees for this course

UK students International students
Fee description Full-time
Tuition fees (2025/26) £33,000
Tuition fees (2025/26) £47,100

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: ucl.ac.uk/students/fees.

Additional costs

For Full-time and Part-time offer holders a fee deposit will be charged at 10% of the first year fee.

Further information can be found in the Tuition fee deposits section on this page: Tuition fees.

Students will require a modern computer (PC or Mac) with minimum specifications of 8GB RAM and 500GB SSD storage with a camera and microphone. However, we recommend at least 16GB RAM and 0.5-1 TB SSD storage. If you are considering undertaking a machine learning project, there will be computational capability available to you from within the Computer Science department, but you may nevertheless find it helpful to have a capable GPU in addition to the above.

UCL’s main teaching locations are in zones 1 (Bloomsbury) and zones 2/3 (UCL East). The cost of a monthly 18+ Oyster travel card for zones 1-2 is £114.50. This price was published by TfL in 2024. For more information on additional costs for prospective students and the cost of living in London, please view our estimated cost of essential expenditure at UCL's cost of living guide.

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.

See all the ways you can fund your studies

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. 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: 2025-2026

Apply for this course

Got questions? Get in touch

Computer Science
Computer Science

cs.pgt-admissions@ucl.ac.uk

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