Financial Risk Management MSc

London, Bloomsbury

Finance is driven by technology. Becoming an expert in both will enable you to thrive in risk management roles in the financial sector. Our Financial Risk Management MSc brings together traditional theories in finance, data analytics, quantitative and computational modelling techniques – designed to produce talented practitioners in this field.

UK students International students
Study mode
Full-time
UK tuition fees (2026/27)
£34,700
Overseas tuition fees (2026/27)
£50,600
Duration
1 calendar year
Programme starts
September 2026
Applications accepted
Applicants who require a visa: 20 Oct 2025 – 27 Mar 2026
Applications close at 5pm UK time

Applications open

Applicants who do not require a visa: 20 Oct 2025 – 28 Aug 2026
Applications close at 5pm UK time

Applications open

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 course 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 course 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



A distinctive finance programme taught from a computer science perspective, the Financial Risk Management MSc trains you to become an expert in computing, quantitative finance, and technology to manage and predict financial risk. 

You'll experience an innovative programme that combines core financial concepts with cutting-edge computational techniques and technologies, through topics such as machine learning, algorithmic trading and blockchain. 

Learning from renowned lecturers who also undertake research or are practitioners in the finance industry, you'll gain a core understanding of market risk, credit risk, operational risk, systemic risk, and financial engineering, complemented by topics that range from market microstructure to probability, stochastic processes, and data-driven modelling.  

You'll also combine knowledge about how the financial system works with computational techniques. 

You'll undertake a substantial project as part of your programme, bringing opportunities to work with an industry partner on a real-world problem, or to embark on an academic research project supervised by one of our leading academics. 

This programme gives you key skills to become a professional in financial markets and related technical aspects, while you immerse yourself in London life and the benefits of living in a global financial centre. 

Who this course is for

This programme is ideal for you if you have a first degree in mathematics, finance, economics, physics, or computing and wish to gain the skills necessary to work within quantitative risk management. 

You will be expected to have established competency in probability, statistics, differential equations, and the use of a computer to solve numerical problems.

What this course will give you

This programme offers you the following benefits and opportunities:

Recognition from a top-ranked university: UCL is consistently ranked among the best universities globally (ranked 9th in the QS World University Rankings 2026), providing you with a prestigious qualification that is highly regarded by employers worldwide.

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 project. Many of these projects are conducted in collaboration with industry partners via the IXN Industry Exchange Network, giving you valuable hands-on experience and industry insights. 

Strong employability with high employment rates and starting salaries: the Graduate Outcomes survey data shows that UCL Computer Science 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 financial risk management.

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.

Strategic location: Studying in London, a global financial and technology hub, places you in proximity to top technology companies, entrepreneurial projects, and industry practitioners, enhancing your learning and career opportunities.

The foundation of your career

Some graduates from this programme have pursued careers in the accountancy and financial services sectors, while others have gone into IT, technology and telecoms, p consultancy, logistics and distribution.

According to recent Graduate Outcomes survey data, employers include Accenture, Bank of Montreal, China Construction Bank, CICC, Credit Suisse, Deloitte, Deutsche Bank, , Google, JP Morgan Chase, Moody’s Analytics, Morgan Stanley and UBS.

If you're interested in learning more about the academic and professional journeys of UCL Computer Science students and graduates, please visit our Student Experiences page. While some of these testimonials feature alumni working in industry or research, we also interview students during their studies.

One of the highlights of my MSc programme was the module on Machine Learning with Applications in Finance, where I learned so many technical analysis skills and applied machine learning algorithms to predict financial market trends.

Qimeng Liu holding flowers at graduation

Qimeng Liu

MSc Financial Risk Management

Employability

A programme with exceptional relevance in the modern world, graduates of this Master's have expertise in how financial markets work, and the mathematical and computational skills required for quantitative roles in the financial industry. This includes handling data, extracting information from data, and developing data-driven models – including the know-how to validate and deploy them in international markets.

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, and self-directed learning 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, totalling approximately 19-22 hours. 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 MSc Financial Risk Management is a one-year programme. 

In Term 1, you will study topics that introduce you to the applied mathematical and computational aspects of quantitative finance, probability theory, stochastic processes and their applications, and key concepts and models of asset pricing, portfolio theory, and risk measurement. You will choose from a range of optional topics, which may include numerical methods for finance, market microstructure, operational risk, financial institutions and markets, and blockchain technologies. 

In Term 2, you study topics that introduce you to the instruments used to analyse, characterise, validate, parametrise, and model complex financial datasets. You will choose from a range of optional topics, which may include algorithmic trading, applied computational finance, machine learning with applications in finance, networks and systemic risk, and financial market modelling and analysis. You will also begin preparation for your final research project/dissertation. 

In Term 3, you will primarily focus on your final research project/dissertation and any examinations that take place in the main examination period. 

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 Financial Risk Management.

Accessibility

The department will endeavour to make reasonable adjustments for students with disabilities, including those with long-term health conditions, neurodivergence, learning differences and mental health conditions. This list is not exhaustive. If you're unsure of your eligibility for reasonable adjustments at UCL, please contact Student Support and Wellbeing Services.

Reasonable adjustments are implemented on a case-by-case basis. With the student's consent, reasonable adjustments are considered by UCL Student Support and Wellbeing Services, and where required, in collaboration with the respective department.

Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information about support available can be obtained from UCL Student Support and Wellbeing Services.

For more information about the department and accessibility arrangements for your course, please contact the department.

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.

Online - Open day

Graduate Open Events: UCL Computer Science Master's Courses (Afternoon)

Join us for an exciting online session led by staff and students from UCL Computer Science. We'll explore our 17 MSc programmes in areas such as AI, Machine Learning, Fintech, Robotics, Cybersecurity, Systems Engineering, and Disability Innovation. We'll cover key information about admissions, scholarships, careers, and student life, followed by a live Q&A with staff and students. We want you to leave this session with a feel for what life is like as a UCL Computer Science student.

Online - Open day

Graduate Open Events: UCL Computer Science Master's Courses (Evening)

Join us for an exciting online session led by staff and students from UCL Computer Science. We'll explore our 17 MSc programmes in areas such as AI, Machine Learning, Fintech, Robotics, Cybersecurity, Systems Engineering, and Disability Innovation. We'll cover key information about admissions, scholarships, careers, and student life, followed by a live Q&A with staff and students. We want you to leave this session with a feel for what life is like as a UCL Computer Science student.

Fees and funding

Fees for this course

UK students International students
Fee description Full-time
Tuition fees (2026/27) £34,700
Tuition fees (2026/27) £50,600

Postgraduate Taught students benefit from a cohort guarantee, meaning that their tuition fees will not increase during the course of the programme, but UCL reserves the right to increase tuition fees to reflect any sums (including levies, taxes, or similar financial charges) that UCL is required to pay any governmental authority in connection with tuition fees.

The tuition fees shown are for the year indicated above. Where the course 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 with a fee status classification of UK, a fee deposit will be charged at 2.5% of the first year fee.

For full-time and part-time offer holders with a fee status classification of Overseas, 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. While it is not a requirement, we recommend at least 16GB RAM and 1 TB SSD storage. Approximate costs may range from £800-£1500. If you are considering undertaking a machine learning project, there will be computational capability available to you from within the Computer Science department. Nevertheless, you may find it helpful to have a capable GPU in addition to the above.

For in-person teaching, 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 £119.90. This price was published by TfL in 2025. 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.

UCL East London Scholarship

CLOSED FOR 25/26 ENTRY
Value: Tuition fees plus £16,000 stipend ()
Criteria Based on financial need
Eligibility: UK

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 course 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 Financial Risk Management at graduate level.
  • why you want to study Financial Risk Management at UCL
  • what particularly attracts you to this programme.
  • how your academic and professional background meets the demands of this programme.
  • what programming experience you have.
  • where you would 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 courses (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: 2026-2027

Got questions? Get in touch

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