The MSc in Financial Risk Management offers a comprehensive education in how organisations and investors identify, evaluate, and manage risks to maximise the likelihood of achieving their strategic objectives.
This programme equips students with the latest financial risk management tools and strategies used by leading financial institutions. The academic team combines cutting-edge research expertise with valuable industry experience to deliver a rigorous and practical learning experience.
Graduates are well-prepared for careers in corporate risk, compliance, consultancy, and academia, and benefit from exemptions from the Professional Risk Manager (PRM) exams.
Queen’s University is ranked third in the UK for Graduate Prospects in Accounting and Finance
(Times and Sunday Times Good University Guide 2025).
Financial Risk Management highlights
Professional Accreditations
This programme has an academic partnership with GARP (Global Association of Risk Professionals), supporting students in preparing for the Financial Risk Manager (FRM) examinations. Each year, several students are nominated to receive scholarships to take the FRM Exam 1 free of charge. Queen’s University Belfast is one of only 15 UK universities to hold academic partnership status with GARP through the MSc Financial Risk Management programme. https://www.garp.org/academic-partners/list
This course is part of the PRMIA (Professional Risk Managers’ International Association) Risk Accreditation Programme, granting students exemptions from the Professional Risk Manager (PRM) Exam 1. The MSc Financial Risk Management at Queen’s University Belfast is one of only five MSc programmes in the UK included in the PRMIA Risk Accreditation Programme, and one of just 17 worldwide. https://prmia.org/Public/Learning/University-Alliances/exemptions-university.aspx
Industry Links
Students are eligible for free membership of the Association of Insurance and Risk Managers in Industry and Commerce (AIRMIC), and each year, two students are nominated to receive bursaries to attend the AIRMIC conference.
Students also benefit from regular guest lectures and networking opportunities with industry professionals and academics. https://www.airmic.com/
Career Development
Students may wish to join the Queen’s Student Managed Fund (QSMF) which provides students with the opportunity to manage and operate a real-money investment portfolio. Established in 2012, the fund transitioned to a real money fund in April 2016. Students currently manage funds of around £60,000 to £70,000 through one of our Gold Sponsors, Davy Group, Ireland’s leading provider of wealth management, asset management, capital markets and financial advisory services. QSMF is also generously supported by Citco, the world’s largest hedge fund administrator. https://www.qub.ac.uk/schools/queens-business-school/student-opportunities/qsmf/
World Class Facilities
The FinTrU Trading Room, which replicates New York and London trading environments, provides students with access to 26 Bloomberg terminals, trading simulations and other financial software.
The FinTrU Trading Room is embedded into taught programmes allowing students to relate real world news and market activity to economic and financial theory. The facility is also vital for supporting extra-curricular activities.
Queen’s Business School (QBS) has recently undergone an innovative expansion that establishes a benchmark of global excellence for one of the top business schools in the UK and Ireland. A stunning new 6,000 square metre building, adjacent to the listed red-brick Riddel Hall has been designed with the latest digital infrastructure for media lecture capture, TED Talk provision and collaborative breakout sessions.
Fostering an enhanced social and educational experience the new state-of-the-art QBS venue boasts a 250-seat tiered educational space; 120-seat Harvard style lecture theatre; 150-seat computer laboratory; breakout study spaces; FinTrU Trading Room; a café, and a Business Engagement and Employability Hub. https://www.qub.ac.uk/schools/queens-business-school/student-opportunities/fintru-trading-room/
Student Experience
Students will use and have access to software such as Bloomberg, CRSP, Compustat, DataStream and S&P Global Market Intelligence.
"Studying MSc Financial Risk Management at QBS was a transformative experience. The faculty’s support and real-world insights deeply enriched my learning. Collaborative projects with peers from diverse backgrounds enhanced my understanding and built lasting friendships. The curriculum’s strong focus on quantitative skills and risk analysis prepared me exceptionally well for the fast-paced Global Financial Market. This degree was instrumental for me to secure a mid-level management position in a globally renowned Investment Bank and gave me the confidence to thrive in a competitive industry."
MSc Financial Risk Management is a year-long full-time programme delivered in-person. Students start with an intensive induction week before undertaking eight modules across the first and second semesters. In the final semester, students either study an Applied Research Project or Dissertation.
You’ll look at how organisations and investors evaluate and address risks to maximise the chances of achieving their objectives.
You’ll use the cutting-edge risk management tools and strategies used by leading financial firms and regulatory bodies. You have an interest in risk management and financial regulation and want a career in areas such as corporate risk, compliance, consultancy, or academia. You’ll gain exemptions from the Professional Risk Manager (PRM) exams.
Semester 1
Asset Pricing
Corporate Finance
Foundations of Risk Management
Financial Data Analytics
Semester 2
Derivatives
Financial Modelling in Python
Advanced Financial Data Analytics
Enterprise and Credit Risk Management
Semester 3
Choose 1 of these 2 options:
Applied Research Project
For those pursuing roles in the financial industry, the applied research project will be of significance. The module will review methods of company analysis, financial analysis, and various approaches to equity valuation. Students will have the opportunity to conduct independent research, undertake a valuation exercise, present their findings in a written report of industry standard and articulate their views in a presentation.
Or
Dissertation
For those intending to pursue an academic career or a research focused role the dissertation is an appropriate choice. For high performing students. The aim of the dissertation is to provide students with the skills needed for conducting theoretical and/or empirical research in finance. Meanwhile, students will be assigned an academic supervisor and will complete an independent piece of academic scholarship.
Learning opportunities available with this course are outlined below:
Teaching Methods
The MSc Financial Risk Management programme equips you with advanced quantitative and analytical skills highly sought by leading financial institutions and regulatory bodies worldwide. It prepares you for diverse careers in risk management, corporate finance, consultancy, FinTech, and regulatory compliance.
Bridging theory and practice, many modules focus on applying risk management models through simulation and real-world case studies. This hands-on approach ensures you develop practical expertise, enabling you to effectively assess and manage financial risks in complex, dynamic environments.
Throughout the programme, you will engage with academic experts and industry practitioners through lectures, workshops, and networking opportunities. You will also benefit from access to cutting-edge technologies and resources that support your growth as an independent and lifelong learner, prepared to navigate the challenges of the global financial landscape.
At Queen’s Business School, we are committed to fostering an intellectually stimulating and supportive learning environment that encourages innovation, critical thinking, and best teaching practices. Our aim is to empower students to realise their full academic potential and to equip them with the skills necessary to contribute meaningfully to the business, economic, and civic sectors.
Teaching Times
Morning / Afternoon
Full-time option: modules are taught morning/afternoon/evening.
Assessment
Assessments associated with the course are outlined below:
Assessment is by a variety of methods, including individual coursework, group work, oral presentations, simulations, case studies, class tests, examinations and dissertation or work-based research project.
The information below is intended as an example only, featuring module details for the current year of study (2025/26). Modules are reviewed on an annual basis and may be subject to future changes – revised details will be published through Programme Specifications ahead of each academic year.
The applied research project provides students with the opportunity to utilise the knowledge and skills acquired over the previous two semesters to plan, develop and produce a substantial piece of original, independent applied research.
Lectures and computer-based workshops will cover the following areas:
1. Research Methodology
2. Fundamental analysis and strategy analysis
3. Data Management, Analysis, Visualisation and Inference
4. Financial analysis [ratios/cash flows], forecasting profit & EPS.
5. Valuation 1: DDM and DCF approach
6. Valuation 2: EVA and Price- multiples
7. Critical assessment of model adequacy
8. Presenting Information and Data
Learning Outcomes
Upon successful completion of this project, students will:
1. Demonstrate an ability to design and manage a piece of individual research.
2. Apply knowledge and skills developed in previous modules to contemporary issues in financial markets.
3. Establish links between financial theory and financial practice.
4. Exhibit intellectual discipline in identifying and critique the appropriate information.
5. Identify appropriate econometric methods for critically analysing a contemporary issue in finance.
6. Critically evaluate the appropriateness of modelling assumptions.
7. Present their thinking in a professional industry-style research paper.
Skills
This applied research project provides opportunities for the student to acquire or enhance the following skills:-
· Subject-specific skills
-Use of computer-based packages to analyse and evaluate relevant data
-Ability to critically read and evaluate finance and risk-related academic literature
-Appreciation, construction and analysis of financial and economic models of practical risk situations
· Cognitive Skills
-Problem solving
-Logical reasoning
-Independent enquiry
-Critical evaluation and interpretation
-Self-assessment and reflection
-Intellectual humility
-Intellectual discipline
· Transferable Skills
-The ability to synthesis information/data from a variety of sources
-Preparation and communication of ideas in both written and presentational forms
-Ability to work both independently
-Organisation and Time Management
-Use of IT
The purpose of this course is to provide an introduction to econometric techniques used in finance. It contains a treatment of classical regression and an introduction to time series techniques. There will be an emphasis on applied work using econometric packages.
The course is designed to give students both theoretical and practical experience of statistical and econometric techniques. A wide range of topics is typically covered including the basic regression model, which includes a discussion of the classical violations of this model and methods for their correction. Students will learn a computer statistical software package (R).
Learning Outcomes
Upon successful completion of this course students will have an understanding of:-
• the main issues relating to the appropriate econometric modelling of financial and economic time series;
• and have gained experience in the use of econometric software and be able to demonstrate their software skills in completing assignments;
• and be able to discuss, applied econometric research topics in finance;
• and have improved their data management, programming and research skills.
Skills
Subject-specific Skills
• The ability to construct arguments and exercise problem solving skills in finance
• The ability to use computer-based mathematical/statistical/econometric packages to analyse and evaluate relevant data
• The ability to read and evaluate finance and risk-related academic literature
Cognitive Skills
• Problem solving
• Logical reasoning
• Independent enquiry
• Critical evaluation and interpretation
• Self-assessment and reflection
Transferable Skills
• The ability to synthesise information/data from a variety of sources
• The preparation and communication of ideas in finance, information economics and risk management
• Organisation and time management
• Problem solving and critical analysis
• Work-based skills; use of IT, including word-processing, email, internet and statistical/econometric/risk management packages
• The ability to communicate quantitative and qualitative information together with analysis, argument and commentary
The aim of this course is to develop in students a theoretical and practical knowledge of derivative instruments.
This module provides participants with an exhaustive coverage of widely used derivative products stressing pricing and uses for financial engineering and risk management. The module provides an overview of derivative instruments, markets, participants and uses. It focuses on the pricing and uses of futures, forwards and options. The cost of carry relationship, the binomial approach, the Black-Scholes model and its variants are detailed to equip participants with the basic tools for pricing derivatives. The module examines practical uses of derivative securities as risk management tools for corporations and financial institutions.
Areas to be covered include:
THE MOVEMENT OF FUTURES PRICES: some basic facts. CTAs, managed futures, hedge funds. Financialization of Commodity Markets. Time series momentum.
MEAN VARIANCE APPROACHES TO HEDGE RATIO DETERMINATION, STOCK INDEX FUTURES AND HEDGING EFFECTIVENESS: The mean-variance approach to hedge ratio construction. Hedging with stock index futures. Hedging effectiveness and hedge ratio estimation - OLS, ECM and GARCH procedures. Duration and Expiration effects.
THE STOCHASTIC PROCESS OF ASSET PRICES AND THE DERIVATION OF THE BLACK-SCHOLES MODEL:The Wiener process and rare events in financial markets; Ito processes; Ito's lemma; generalised Ito's lemma; Black-Scholes differential equation; Black-Scholes pricing formula; options on stocks paying known dividends; pseudo-American model; option on stock indices, currency options and options on futures;
VOLATILITY: Estimating volatility: historical; implied - application of Newton-Raphson. Empirical characteristics of volatility: smiles; term structure skew; mean reversion; Forecasting volatility: application of GARCH; empirical evidence of volatility forecasts - implied versus historical; Bisection.
EXOTIC OPTIONS: Types of exotic options - barrier options; lookback options; strike options; binary or digital options; compound options; and chooser options.
INTEREST RATE DERIVATIVES: The standard market models; models of short rate; HJM and LMM models.
RISK AND REGULATION WITH EMPHASIS ON VALUE AT RISK: Regulation of Financial Institutions; value at risk and forecast accuracy; capital adequacy and value at risk; value at risk and the variance covariance approach; value at risk and non-parametric methods such as historical simulation and bootstrapping; value at risk and linear and non-linear positions.
REAL OPTIONS: The option to expand, contract, default, abandon and switch. The valuation of real options in the face of compoundness, interaction between options and ownership. Real options and the valuation of internet companies.
Learning Outcomes
Upon successful completion of this module, students will have an understanding of:-
1. understand the mechanisms of futures and forward market
2. price futures and forward instruments
3. understand the mechanisms of options markets
4. understand concepts of stochastic processes and its application in financial modelling
5. understand and derive binomial tree model
6. understand and derive Black-Scholes-Merton model
7. estimate historical and implied volatility
8. construct hedges using futures and options
Skills
This module provides opportunities for the student to acquire or enhance the following skills:
Subject-specific Skills
• The ability to construct arguments and exercise problem solving skills in the context of theories of finance and risk management
• The ability to use computer-based mathematical / statistical / econometric packages to analyse and evaluate relevant data
• The ability to read and evaluate finance and risk-related academic literature
• The ability to appreciate, construct and analyse mathematical, statistical, financial and economic models of practical risk situations
• The ability to connect business problems with risk management
• The ability to marry regulatory structure with the principles of risk sharing and risk mitigation
Cognitive Skills
• Problem solving
• Logical reasoning
• Independent enquiry
• Critical evaluation and interpretation
• Self assessment and reflection
Transferable Skills
• The ability to synthesise information/data from a variety of sources including from databases, books, journal articles and the internet
• The preparation and communication of ideas in finance, information economics and risk management in both written and presentational forms
• The ability to work both independently and in groups
• Organisation and time management
• Problem solving and critical analysis
• Work-based skills; use of IT, including word-processing, email, internet and statistical/econometric/risk management packages
• The ability to communicate quantitative and qualitative information together with analysis, argument and commentary in a form appropriate to different intended audiences
Course Description:
The purpose of this course is to analyse how corporations make major financial decisions. The theory of corporate behaviour is discussed and the relevance of each theoretical model is examined by an empirical analysis of actual corporate decision making.
Course Aim:
The aims of this module are to:
(i) familiarize students with the issues confronting corporations when making investment and financing decisions;
(ii) develop the ability of students to obtain corporate information from the Bloomberg database.
Course Coverage:
• Corporate Governance
• Investment Appraisal
• Dividend Policy
• Capital Structure
• Initial Public Offerings
• Mergers and Acquisitions
Learning Outcomes
Upon successful completion of this module, students will be able to:
• describe and synthesize academic theories which explain the approaches of corporations to investment and financing decisions;
• analyse how corporations can increase shareholder value;
• evaluate empirical evidence regarding whether corporate decision making is consistent with academic theories;
• apply theoretical principles to hypothetical situations;
• use the Bloomberg database in a trading-room environment.
Skills
This course provides opportunities for the student to acquire or enhance the following skills:
Subject-specific Skills
• The ability to construct arguments and exercise problem solving skills in the context of theories of finance and risk management
• The ability to use computer-based mathematical / statistical / econometric packages to analyse and evaluate relevant data
• The ability to read and evaluate finance and risk-related academic literature
• The ability to appreciate, construct and analyse mathematical, statistical, financial and economic models of practical risk situations
Cognitive Skills
• Problem solving
• Logical reasoning
• Independent enquiry
• Critical evaluation and interpretation
• Self assessment and reflection
Transferable Skills
• The ability to synthesise information/data from a variety of sources including from databases, books, journal articles and the internet
• The preparation and communication of ideas in finance, information economics and risk management in both written and presentational forms
• The ability to work both independently and in groups
• Organisation and time management
• Problem solving and critical analysis
• Work-based skills; use of IT, including word-processing, email, internet and statistical/econometric/risk management packages
• The ability to communicate quantitative and qualitative information together with analysis, argument and commentary in a form appropriate to different intended audiences.
The aims of this module are to:
Deepen participants' understanding of financial predictions and decision-making by exploring the revolutionary
impact of combining econometrics and machine learning in financial analytics.
Integrate machine learning and classical financial time series econometrics to tackle complex financial problems
characterised by uncertainty and conflicting objectives.
Explore the role of machine learning in processing large datasets and accurately modelling the complexities of
financial markets.
Advocate for adopting a growth mindset for learning advanced financial data analytics, emphasising embracing
challenges, persisting through setbacks, leveraging criticism, and finding lessons in others' success.
Equip participants with the necessary insights and tools to navigate the sophisticated realm of financial analytics,
encouraging a lifelong commitment to learning and development in the field.
Learning Outcomes
Upon successful completion of this module students will be able to:
1. Extract meaning from noisy financial data
2. Critique stylised facts of financial data for economic inference
3. Evaluate the output of statistical tests
Skills
This module provides opportunities for the student to acquire or enhance the following skills:-
1. Problem solving – innovative ability to implement statistical tests
2. Logical reasoning – analysing data
3. Digital Proficiency – ability to write code
4. Abstraction – developing generic re-usable solutions
5. Critical Thinking – applying and interpreting statistics
The aims of this module are to:
(i) provide students with the necessary theoretical and analytical tools which underpin the pricing of assets;
(ii) familiarize students with the environment of a trading room
Areas to be covered include:
Financial markets
Overview of main markets; how firms and governments raise finance; financial instruments; trading securities.
Valuation
Valuing stocks.
Asset returns and portfolio theory
Measuring asset returns; theory of choice under uncertainty; mean-variance portfolio theory.
Asset-pricing models
Assessing the theoretical and empirical validity of various asset pricing models.
Upon successful completion of this module, students will:
1. Be familiar with the various theories on individuals’ investment decision making
2. apply techniques for formally assessing risk.
3. understand the methodologies employed in investigating asset pricing behaviour in the capital market
4. be able to critically evaluate the various asset pricing models in terms of both theory and empirical evidence
5. be able to critically appraise the EMH, anomalies and behavioural finance.
6. be familiar with the trading-room environment and the Bloomberg database.
Skills
This module provides opportunities for the student to acquire or enhance the following skills:-
• Subject-specific skills
o Use of computer-based packages to analyse and evaluate relevant data
o Ability to criticially read and evaluate finance and risk-related academic literature
o Appreciation, construction and analysis of financial and economic models of practical risk situations
• Cognitive Skills
o Problem solving
o Logical reasoning
o Independent enquiry
o Criticial evaluation and interpretation
o Self-assessment and reflection
• Transferable Skills
o The ability to synthesis information/data from a variety of sources
o Preparation and communication of ideas in both written and presentational forms
o Ability to work both independently and in groups
o Organisation and Time Management
o Use of IT.
i. develop the students' computational skills
ii. introduce a range of numerical techniques of importance in finance
iii. familiarise students with financial models and how to implement them
Areas to be covered include:
A primer on financial instrument pricing
o Bonds, forwards, options
o Discounting
o Probability distributions
o Expectation theory
Python
o Arrays and data structures
o Programming constructs
o Functions and classes
Numerical Methods
o Root finding
o Linear Algebra
Financial Modelling
o Stochastic processes
o Interest rate models
Option Pricing
o Black Scholes Merton
o The Greeks
o Lattice Models
o Model extensions
Monte Carlo
o Monte Carlo simulation
o Variance reduction
o Markov Chains
Credit Risk
o Merton Model
Learning Outcomes
Upon successful completion of this module, students will:
1. Describe and discuss the modelling frameworks used to value financial instruments.
2. Understand the salient features of prominent derivatives contracts.
3. Translate financial problems into mathematical models with appropriate numerical solutions
4. Have experience using Python to implement financial models
5. Critically evaluate the efficacy of different approaches to derivative pricing
Skills
This module provides opportunities for the student to acquire or enhance the following skills:
• Subject-specific skills
o The ability to appreciate, construct and analyse mathematical, statistical, and financial models
o Use of coding languages to implement financial models.
• Cognitive Skills
o Problem solving
o Abstraction
o Logical reasoning
o Critical evaluation and interpretation
o Self-assessment and reflection
• Transferable Skills
o Organisation and time management
o Use computational technology
The aims of this course are to:
i. analyse the management of risk at the enterprise level, examining how companies are addressing all their key risks on a consistent integrated basis.
ii. Profile the development of credit culture and its key role in the global economy. Identify the key credit players, their roles and the interaction between key players.
iii. Introduce students to the techniques used to quantify credit risk. The incremental nature of model development is highlighted and the strengths and weaknesses of various techniques are discussed.
iv. Provide students with an understanding of basic credit derivatives and securitised credit products set against a backdrop of how the complexity of these instruments contributed to the recent financial crisis.
Learning Outcomes
Upon successful completion of this module, students will:
be able to:
i. Describe and synthesize the theory and rationale behind a corporation’s motivation to implement an Enterprise Risk Management programme.
ii. Understand how risks may be categorised and thus develop an appropriate business risk framework.iii. understand how corporate credit culture and the lending decisions have evolved over the past 50 years
iv. be able to identify and critically access the roles played by key institutional and market players in credit markets
v. be able to demonstrate knowledge of the structure and application of accounting and market based credit risk models
vi. be familiar with portfolio based techniques for credit risk modelling
vii. understand the features of credit derivatives and securitized credit products with an appreciation of how these instruments contributed to the recent financial crisis
Skills
This course provides opportunities for the student to acquire or enhance the following skills:
Subject-specific skills:
o The ability to critically read and evaluate finance and risk specific academic literature
o The ability to apply financial data to a series of models in order to make a appropriate estimate of credit risk exposure
o The understanding of the relative strengths and weaknesses of credit risk models
o The ability to analyse various credit derivatives from a risk mitigation perspective
o The ability to identify and debate issues pertaining to credit risk set within a broader context of the current financial climate
Cognitive skills:
o Problem solving
o Logical reasoning
o Independent enquiry
o Critical evaluation and interpretation
o Self assessment and reflection
Transferable Skills:
o The ability to synthesise financial information/data from a variety of sources
o Preparation and communication of ideas in both written and presentational forms
o Ability to work both independently and in groups
o Organisation and Time Management
o Use of IT
This module considers both risk and regulation in financial services. With regard to risk the module introduces students to the risks that institutions must take if they are to survive and prosper including market risk, credit risk, liquidity risk and operational risk. Emphasis is on the quantification of these risks, decisions about what level of such risks are acceptable and the action required to mitigate unacceptable levels of risk.
MODULE AIMS
(i) to offer a rigorous and intellectually demanding course of study of the techniques, principles and underpinning theories behind effective financial regulation
(ii) to offer a rigorous and intellectually demanding course of study of risk assessment and risk mitigation techniques applicable to financial institutions
(iii) to provide students with an understanding of current thoughts on financial market reform.
With regard to regulation the emphasis is on identifying the objectives of the regulatory system. The course stresses that being clear about the objectives of regulation is essential from the point of view of ensuring that the system is operated efficiently, that priorities are correctly assigned and weighted, and that the spirit as well as the letter of regulatory requirements is observed.
Learning Outcomes
Upon successful completion of this module students will have an understanding of:
1. the economics of information and its importance in financial regulation
2. the calculation of market risk, credit risk, liquidity risk and operational risk for financial institutions
3. the relationship between the capital requirements faced by financial institutions and their levels of credit risk, market risk and operational risk.
4. obstacles to efficient supervision and resolution
5. working in small groups and making tutorial presentations
6. how to use journal articles to build knowledge of the subject material
Skills
This module provides opportunities for the student to acquire or enhance the following skills:-
• Subject-specific skills
o Ability to critically read and evaluate finance and risk-related academic literature;
o Appreciation, construction and analysis of maths/statistical, financial and economic models of practical risk situations;
o Ability to connect business problems with risk management;
o Ability to marry regulatory structure with the principles of risk sharing and risk mitigation
• Cognitive Skills
o Problem solving
o Logical reasoning
o Independent enquiry
o Criticial evaluation and interpretation
o Self assessment and reflection
• Transferable Skills
o The ability to synthesis information/data from a variety of sources
o Preparation and communication of ideas in both written and presentational forms
o Ability to work both independently and in groups
o Organisation and Time Management
o Use of IT.
The aim of the dissertation is to provide students with the skills needed for the advanced analysis of relevant datasets, to allow them to demonstrate an understanding of the relevant literature and to derive and test hypotheses and to draw appropriate conclusions.
Learning Outcomes
On completion of the dissertation students will have an understanding of:-
• how to conduct a review of the current and relevant literature of the subject area chosen for the research study;
• how to derive hypotheses or formulate research questions;
• how to use data extracted from datasets or interviews to test hypotheses or answer research questions;
• how to draw conclusions and identify the limitations of the study and scope for further research.
Skills
This course provides opportunities for the student to acquire or enhance the following skills:-
• Communication
• Effective and independent learning
• Specific research skills relevant to the chosen research topic
• Data analysis skills relevant to the chosen research topic
• Econometric skills
Normally a strong 2.2 Honours degree or equivalent qualification acceptable to the University in Mathematics, Accountancy, Finance, Economics or other relevant quantitative subject. Science and Engineering disciplines will be considered where there is a significant mathematical component. Performance in relevant modules must be at UK 2:2 Honours standard (or acceptable equivalent).
We welcome applications from a diverse range of applicants so will also consider previous work experience alongside academic qualifications. Prior experiential learning in quantitative analysis, Mathematics or Finance based subjects in lieu of academic qualifications will be considered on an individual basis.
Applicants are advised to apply as early as possible and ideally no later than 14th August 2026 for courses which commence in late September. In the event that any programme receives a high number of applications, the University reserves the right to close the application portal prior to the deadline stated on course finder. Notifications to this effect will appear on the application portal against the programme application page.
Please note: international applicants will be required to pay a deposit to secure a place on this course.
The University's Recognition of Prior Learning Policy provides guidance on the assessment of experiential learning (RPEL). Please visit the link below for more information. http://go.qub.ac.uk/RPLpolicyQUB
International Students
Our country/region pages include information on entry requirements, tuition fees, scholarships, student profiles, upcoming events and contacts for your country/region. Use the dropdown list below for specific information for your country/region.
English Language Requirements
Evidence of an IELTS* score of 6.5, with not less than 5.5 in any component, or an equivalent qualification acceptable to the University is required.
*Taken within the last 2 years.
International students wishing to apply to Queen's University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.
If you need to improve your English language skills before you enter this degree programme, Queen's University Belfast International Study Centre offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for admission to this degree.
Academic English: an intensive English language and study skills course for successful university study at degree level
Pre-sessional English: a short intensive academic English course for students starting a degree programme at Queen's University Belfast and who need to improve their English.
As many financial firms continue to expand their risk management functions, this programme opens a wide range of exciting career opportunities. These include applying cutting-edge quantitative modelling techniques, collaborating with traders to develop bespoke financial products, and managing and monitoring portfolio and product risks.
Graduate prospects from the MSc Financial Risk Management are excellent; culminating in Queen’s being ranked third in the UK for Graduate Prospects in Accounting and Finance (Times and Sunday Times Good University Guide 2025). Graduates from this programme have secured roles with employers such as Royal Bank of Scotland, BNY Mellon, Citi, PwC, EY, Intel, and many others. Typical roles include financial and data analysts, risk managers, management consultants, and project managers. https://www.qub.ac.uk/directorates/sgc/careers/
Graduate Plus/Future Ready Award for extra-curricular skills
In addition to your degree programme, at Queen's you can have the opportunity to gain wider life, academic and employability skills. For example, placements, voluntary work, clubs, societies, sports and lots more. So not only do you graduate with a degree recognised from a world leading university, you'll have practical national and international experience plus a wider exposure to life overall. We call this Graduate Plus/Future Ready Award. It's what makes studying at Queen's University Belfast special.
1EU citizens in the EU Settlement Scheme, with settled status, will be charged the NI or GB tuition fee based on where they are ordinarily resident. Students who are ROI nationals resident in GB will be charged the GB fee.
2 EU students who are ROI nationals resident in ROI are eligible for NI tuition fees.
3 EU Other students (excludes Republic of Ireland nationals living in GB, NI or ROI) are charged tuition fees in line with international fees.
All tuition fees quoted relate to a single year of study unless stated otherwise. Tuition fees will be subject to an annual inflationary increase, unless explicitly stated otherwise.
Terms and Conditions for Postgraduate applications:
1.1 Due to high demand, there is a deadline for applications.
1.2 International applicants will be required to pay a deposit to secure their place on the course. The current mandatory tuition fee deposit payment is £1000 International (Non- EU & EU except ROI).
1.3 This condition of offer is in addition to any academic or English language requirements.
Depending on the programme of study, there may be extra costs which are not covered by tuition fees, which students will need to consider when planning their studies.
Students can borrow books and access online learning resources from any Queen's library. If students wish to purchase recommended texts, rather than borrow them from the University Library, prices per text can range from £30 to £100. Students should also budget between £30 to £75 per year for photocopying, memory sticks and printing charges.
Students undertaking a period of work placement or study abroad, as either a compulsory or optional part of their programme, should be aware that they will have to fund additional travel and living costs.
If a programme includes a major project or dissertation, there may be costs associated with transport, accommodation and/or materials. The amount will depend on the project chosen. There may also be additional costs for printing and binding.
Students may wish to consider purchasing an electronic device; costs will vary depending on the specification of the model chosen.
There are also additional charges for graduation ceremonies, examination resits and library fines.
How do I fund my study?
The Department for the Economy will provide a tuition fee loan of up to £6,500 per NI / EU student for postgraduate study. Tuition fee loan information.
A postgraduate loans system in the UK offers government-backed student loans of up to £11,836 for taught and research Masters courses in all subject areas (excluding Initial Teacher Education/PGCE, where undergraduate student finance is available). Criteria, eligibility, repayment and application information are available on the UK government website.
