BSc|Undergraduate
Actuarial Science and Risk Management
Entry year
Academic Year 2024/25
Academic Year 2024/25
Entry requirements
A*AA/AAA + A in a 4th AS-level subject
A*AA/AAA + A in a 4th AS-level subject
Duration
4 years (Full Time)
4 years (Full Time)
UCAS code
N323
N323
Placement Year
Yes
Yes
The BSc Actuarial Science and Risk Management programme has been designed by qualified actuaries to enable students to develop the theoretical and practical skills required to pursue a career as an actuary in the pensions and insurance sectors, or in the wider financial industry.
In addition, students may gain up to six exemptions from the initial technical professional exams required to qualify as an actuary via our accreditation with the Institute and Faculty of Actuaries.
Actuarial Science and Risk Management Degree highlights
The Actuarial, Accounting and Finance department at Queen’s is consistently ranked in the top 10 in the UK by the Sunday Times and the Complete University Guide.
Professional Accreditations
- Subject to academic performance, students can gain up to six exemptions from the Institute and Faculty of Actuaries (IFoA) professional exams.
Industry Links
- The Society of Northern Ireland Actuaries (SoNIA) is a regional society for local actuaries. It aims to offer a forum for Northern Ireland based actuaries and student actuaries to share opinions on actuarial topics, providing a networking opportunity.
Career Development
- During the third year of the degree, students complete a 9 to 12 month placement with an actuarial firm. These placements are usually in Belfast, Dublin, London or the Isle of Man. Example placements include Aviva, Irish Life, Spence & Partners, SCOR, The Pension Protection Fund and Pramerica. There are a dedicated Careers and Work Placement Office in the Business School who will help you to prepare for placement, and obtain positions of the highest quality.
World Class Facilities
- Students on the course will be given the opportunity to develop their financial modelling skills and will use software such as Model Risk and the Bloomberg terminals in the Trading Room.
Internationally Renowned Experts
- Students have the opportunity to engage with industry professionals who regularly deliver guest lectures.
Student Experience
- The Student Managed Fund gives students the opportunity to manage a real money portfolio where they do the research and decide on their investment strategy.
- The Finance & Actuarial society runs social and educational events for members, such as the end of year formal.
- Students can choose from a wide range of Master’s programmes as well as a comprehensive list of research topics, as shown on the Queen’s Business School website.
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Course content
Course Structure
People teaching you
Mr Neil McConvilleProgramme Director for BSc Actuarial Science
Queen's Business School
Neil McConville is a Fellow of the Institute and Faculty of Actuaries and a former consulting pensions Actuary and Scheme Actuary certificate holder. Following his graduation from Queen’s University Belfast, with a degree in Finance, Neil commenced his career as an Actuary in Dublin before moving onto a number of senior roles within benefit consulting firms based in Belfast. Neil is a Lecturer (Education) and programme director of the Actuarial Science and Risk Management degree programme and lectures across all teaching years within the degree.
Lecturer (Practice) for Actuarial Science
Queen’s Business School
Bronagh is a Fellow of the Institute and Faculty of Actuaries and a former consulting pensions actuary. Bronagh commenced her career as an Actuary in Belfast, holding a number of senior roles within benefit consulting firms prior to joining QUB in 2022. Bronagh is a Lecturer (Practice) and Advisor of Studies on the Actuarial Science and Risk Management degree programme.
Lecturer (Education) for Actuarial Science
Queen's Business School
Gillian McMahon is a Fellow of the Institute and Faculty of Actuaries and a Lecturer on the Actuarial Science and Risk Management degree programme at the Business School, Queen’s University Belfast. After completing a master’s degree in Financial and Industrial Mathematics at Dublin City University and obtaining a first class bachelor’s degree in Theoretical Physics from University College Dublin, Gillian spent nine years working in an actuarial role with a Belfast based pensions consultancy. She joined the Business School in 2016.
Contact Teaching Times
| Medium Group Teaching | 6 (hours maximum) hours of practical classes, workshops or seminars each week |
|---|---|
| Small Group Teaching/Personal Tutorial | 2 (hours maximum) hours of tutorials (or later, project supervision) each week |
| Large Group Teaching | 6 (hours maximum) hours of lectures |
| Personal Study | 24 (hours maximum) 22–24 hours studying and revising in your own time each week, including some guided study using handouts, online activities, etc. |
Learning and Teaching
Queen’s Business School is one of the largest Schools in the University with more than 1800 full-time undergraduate students and 300 plus postgraduate students. The School has been delivering high quality programmes for more than 40 years and was one of the first schools in the UK to introduce undergraduate management education. Since then, QBS has been developing and enhancing its teaching portfolio for both local and international students and boasts students from more than 20 different nationalities.
In recent years, the School has benefited from significant investment resulting in many new academic appointments and state-of-the-art facilities including computer teaching labs with specialised software and a Trading Room in Riddel Hall. In addition, the new McClay library houses an excellent selection of Management and related texts and there are extensive IT facilities throughout the campus.
At Queen’s, we aim to deliver a high quality learning environment that embeds intellectual curiosity, innovation and best practice in learning, teaching and student support to enable students to achieve their full academic potential. In line with this, one of QBS’ primary objectives is to deliver innovative learning and teaching programmes that provide students with the competences and skills to make a positive contribution to business, economic and civic life.
On the BSc Actuarial Science and Risk Management programme we achieve these goals by providing a range of learning environments which enable our students to engage with subject experts both academic staff and industry guest speakers, develop skills and attributes and perspectives that will equip them for life and work in a global society and make use of innovative technologies and a world-class library that enhances their development as independent, lifelong learners. Examples of the opportunities provided for learning on this degree programme are:
- Adviser of Studies
Who acts as a first point of contact for students with academic or personal issues that they may require guidance and/or support with. - E-Learning technologies
Information associated with lectures and assignments is often communicated via a Virtual Learning Environment (VLE) called Queen’s Online. A range of e-learning experiences are also embedded in the degree programme through the use of, for example, interactive support materials, podcasts and web-based learning activities. There are also opportunities to develop skills in the use of industry software associated with actuarial practice. - Induction
A formalised induction for all undergraduate students. For Stage 1 students, this includes several half-day sessions the week before the programme begins to allow students to familiarise themselves with the campus and the degree programme. During Stage 1 there are a number of follow-up sessions throughout the year. Topics such as academic writing, referencing, plagiarism, communication skills, examination preparation and managing time effectively are all covered in these practical sessions. - Lectures
These introduce foundation information about new topics as a starting point for further self-directed private study/reading. As the module progresses this information becomes more complex. Lectures, which are normally delivered in large groups to all year-group peers, also provide opportunities to ask questions and seek clarification on key issues as well as gain feedback and advice on assessments. Additional guest lectures are also delivered by actuaries from a number of actuarial firms. In addition to the academic content of the lectures and workshops, this enables employers to impart their valuable experience to QBS Actuarial Science students and introduces important local employers to our students and allows our students to meet and engage with potential future employers. . - Peer Mentoring Scheme
Whereby students in the second year of their degree programme volunteer to mentor Stage 1 students. Developing the programme themselves, with support from academic staff in QBS, the mentors organise informal meetings, regular contact and a series of events ranging from ice-breaker type events to employer-led sessions with the Stage 1 students. - Personal Development Planning
To encourage students to engage in independent learning. - Practicals
Actuarial Science is a very theoretical yet vocational subject and as such we facilitate opportunities for students to engage in the application of theory. You will have opportunities to develop technical skills and apply theoretical principles to real-life or practical contexts through the modules you study and through industry presentations and workshops that we host. - Self-directed study
This is an essential part of life as a Queen’s student when important private reading, engagement with e-learning resources, reflection on feedback to date and assignment research and preparation work is carried out. - Seminars/tutorials
A significant amount of teaching is carried out in small groups (typically 15-20 students). These sessions are designed to explore, in more depth, the information that has been presented in the lectures. This provides students with the opportunity to engage closely with academic staff who have specialist knowledge of the topic, to ask questions of them and to assess their own progress and understanding with the support of their peers. During these classes, students will be expected to present their work to academic staff and their peers. - Student Support Systems
QBS has an active and co-ordinated student support system to assist students in making the transition from school to university. - Supervised Projects
As part of the continual assessment on a range of modules, you will be expected to undertake project work. You will receive support from the module coordinators who will guide you in terms of how to carry out your projects and will provide feedback to you during the write up stage. - Work placements
The BSc Actuarial Science and Risk Management programme has a compulsory placement year with an actuarial organisation. This begins after all Level 2 modules have been successfully completed. The dedicated Careers and Work Placement Office within the School facilitates students in sourcing and securing appropriate placements and provides appropriate support whilst the student is with the host organisation. This is a significant learning and employability enhancement opportunity and will ensure that the theory being understood in the lecture theatre is complemented by the development of practical, transferrable skills.
Assessment
Details of assessments associated with this course are outlined below:
- The way in which students are assessed will vary according to the learning objectives of each module. Details of how each module is assessed are shown in the Student Handbook which is provided to all students during their first year induction. Actuarial Science modules are typically assessed by a combination of continuous assessment and a final written unseen examination. Continuous assessment consists of tutorial submissions, short class tests, individual project work, small group projects and presentations – this involves three/four students per group working on a specific task, for example, a solution to an actuarial problem.
Once you have reviewed your feedback, you will be encouraged to identify and implement further improvements to the quality of your work.
Feedback
As students progress through their course at Queen’s they will receive general and specific feedback about their work from a variety of sources including lecturers, module co-ordinators, placement supervisors, personal tutors, advisers of study and peers. University students are expected to engage with reflective practice and to use this approach to improve the quality of their work. Feedback may be provided in a variety of forms including:
- Feedback provided via formal written comments and marks relating to work that you, as an individual or as part of a group, have submitted.
- Face to face comment. This may include occasions when you make use of the lecturers’ advertised “office hours” to help you to address a specific query.
- Placement employer comments or references.
- Online or emailed comment.
- General comments or question and answer opportunities at the end of a lecture, seminar or tutorial.
- Pre-submission advice regarding the standards you should aim for and common pitfalls to avoid. In some instances, this may be provided in the form of model answers or exemplars which you can review in your own time.
- Feedback and outcomes from practical classes.
- Comment and guidance provided by staff from specialist support services such as, Careers, Employability and Skills or the Learning Development Service.
- Once you have reviewed your feedback, you will be encouraged to identify and implement further improvements to the quality of your work.
Facilities
Students have access to Bloomberg software, a market leader in financial news, data and analytics, which is used by many financial institutions. The Trading Room allows for an interactive and exciting learning environment which, brings textbook theory to life.
https://www.qub.ac.uk/schools/queens-business-school/student-opportunities/fintru-trading-room/
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Overview
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Modules
Modules
The information below is intended as an example only, featuring module details for the current year of study (2023/24). 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.
- Year 1
Core Modules
Foundations of Economics 1 (20 credits)Foundations of Economics 1
Overview
Foundations of Economics 1 is the title of our new Level 1 semester 1 CORE (Curriculum Open-access Resource for Economics) module for non-specialists. CORE is the result of a huge global collaboration to change the way introductory economics is taught; to ensure it is student-centred and motivated by real-world problems and real-world data. Many students studying for degrees in other disciplines are drawn to economics so that they can develop their analytical skills and also engage with policy debates on issues such as environmental sustainability, inequality, the future of work, financial instability, and innovation. But, when they study economics, they find that their introductory course is arid and theoretical, and designed primarily for students who want to study the subject as their major. The result is that students from other disciplines often find themselves studying a quantitative and analytical economics module that is only minimally social in content and downplays the insights of other disciplines, or a social or business oriented module that gives them little training in modelling, or in quantitative scientific methods. In contrast, this module draws on the work of the global CORE team to offer students who are not specialist economists an in-depth introduction to economics and the global economy that is both analytical and real-world. The module focuses throughout on evidence on the economy, from around the world, and from history. It is motivated by questions — how can we explain what we see?
This module is targeted at UG students who are not taking economics as a major subject but who want to develop their analytical skills and learn how to use economics to understand and articulate reasoned views on some of the most pressing policy problems facing our societies.
The course content will be drawn primarily from the following units from the textbook Economy, Society, and Public Policy:
1 Capitalism: affluence, inequality, and the environment
2 Social interactions and economic outcomes
3 Public policy for fairness and efficiency
4 Work, wellbeing and scarcity
5 Institutions, power, and inequality
6 The firm: employees, managers, and owners
7 Firms, customers, and markets
8 The labour market: unemployment, wages, and profits
9 The credit market: borrowers, lenders, and the rate of interest
10 Market successes and failures
11 Government, citizens, and public policy
12 Banks, money, and central bank policyLearning Outcomes
Successful completion of the module will enable students to:
Understand the reach of economics and its place in the wider social sciences; understand how to interpret relevant evidence and apply relevant economic theory to help answer a variety of economic and social questions; understand how to critically evaluate the application of models in economics to real-world questions and policy issues; understand key aspects of the historical development of the global economy and its contemporary nature.Skills
Subject-specific skills
Successful completion of the module will enable students to:
Develop/enhance subject-specific skills including the ability to construct arguments and exercise problem solving skills in the context of real-world economic and social questions; the ability to construct, interpret and critically evaluate economic models of behaviour; the ability to apply economic models and concepts to real world questions; the ability to understand, evaluate and commentate on the economy and on economic and social policy.
Cognitive and transferable skills
Successful completion of the module will enable students to:
Develop/enhance generic cognitive and transferable skills, including: problem solving, logical reasoning, independent enquiry, critical evaluation and interpretation, self-assessment and reflection, synthesising information from a variety of sources, written and verbal communication, organisation and time management.Coursework
0%
Examination
70%
Practical
30%
Stage/Level
1
Credits
20
Module Code
ECO1015
Teaching Period
Autumn
Duration
12 weeks
Actuarial Mathematics 1 (20 credits)Actuarial Mathematics 1
Overview
(1) Intro to cashflow modules and using them to describe financial instruments.
(2) Time value of money, interest rates and force of interest: discounting single cashflows using simple and compound interest rates (compounded annually and more frequently).
(3) Discounting and accumulating a series of cashflows using actuarial annuity functions such as annuity certain (payable in advance, in arrears, continuously), plus increasing and deferred annuities.
(4) Equations of value and calculating loan schedules.
(5) Project appraisal using Net Present Value, Internal/Money-weighted/Linked-Internal rate of return etc.
(6) Introduction to asset classes and simple derivative functions.Learning Outcomes
At the conclusion of this module students will be equipped to:
1.Understand simple actuarial functions used and mathematical techniques employed, by an actuary.
2.Be able to convert annual interest rates into continuous rates and rates of other compound frequencies.
3.Determine the present value of cashflows and/or the yield for various financial instruments.Skills
Numerical and problem solving skills.
Coursework
0%
Examination
75%
Practical
25%
Stage/Level
1
Credits
20
Module Code
FIN1013
Teaching Period
Spring
Duration
12 weeks
Foundations of Economics 2 (20 credits)Foundations of Economics 2
Overview
Foundations of Economics 2 is the title of our new Level 1 semester 2 CORE (Curriculum Open-access Resource for Economics) module for non-specialists. It builds explicitly on material covered in Foundations of Economics 1 in semester 1. CORE is the result of a huge global collaboration to change the way introductory economics is taught; to ensure it is student-centred and motivated by real-world problems and real-world data. Many students studying for degrees in other disciplines are drawn to economics so that they can develop their analytical skills and also engage with policy debates on issues such as environmental sustainability, inequality, the future of work, financial instability, and innovation. But, when they study economics, they find that their introductory course is arid and theoretical, and designed primarily for students who want to study the subject as their major. The result is that students from other disciplines often find themselves studying a quantitative and analytical economics module that is only minimally social in content and downplays the insights of other disciplines, or a social or business oriented module that gives them little training in modelling, or in quantitative scientific methods. In contrast, this module draws on the work of the global CORE team to offer students who are not specialist economists an in-depth introduction to economics and the global economy that is both analytical and real-world. The module focuses throughout on evidence on the economy, from around the world, and from history. It is motivated by questions — how can we explain what we see?
This module is targeted at UG students who are not taking economics as a major subject but who want to develop their analytical skills and learn how to use economics to understand and articulate reasoned views on some of the most pressing policy problems facing our societies.
The course content will be drawn primarily from the following units from the textbook The Economy:
9. The Labour Market: Wages, Profit and Unemployment
13 Economic fluctuations and unemployment
14 Unemployment and fiscal policy
15 Inflation, unemployment, and monetary policy
16 Technological progress, employment, and living standards in the long run
A selection of (two or more) capstone units drawn from The Economy will also be covered:
17 The Great Depression, golden age, and global financial crisis
18: Globalization—trade, migration and investment
19: Inequality
20: Environmental sustainability and collapse
21: Innovation, intellectual property, and the networked economy
22: Politics, economics, and public policyLearning Outcomes
Successful completion of the module will enable students to:
Understand the reach of economics and its place in the wider social sciences; understand how to interpret relevant evidence and apply relevant economic theory to help answer a variety of economic and social questions; understand how to critically evaluate the application of models in economics to real-world questions and policy issues; understand key aspects of the historical development of the global economy and its contemporary nature.Skills
Subject-specific skills
Successful completion of the module will enable students to:
Develop/enhance subject-specific skills including the ability to construct arguments and exercise problem solving skills in the context of real-world economic and social questions; the ability to construct, interpret and critically evaluate economic models of behaviour; the ability to apply economic models and concepts to real world questions; the ability to understand, evaluate and commentate on the economy and on economic and social policy.
Cognitive and transferable skills
Successful completion of the module will enable students to:
Develop/enhance generic cognitive and transferable skills, including: problem solving, logical reasoning, independent enquiry, critical evaluation and interpretation, self-assessment and reflection, synthesising information from a variety of sources, written and verbal communication, organisation and time management.Coursework
30%
Examination
70%
Practical
0%
Stage/Level
1
Credits
20
Module Code
ECO1016
Teaching Period
Spring
Duration
12 weeks
Introduction to Probability & Statistics (30 credits)Introduction to Probability & Statistics
Overview
This is a fundamental module which provides an introduction to probability theory and the key concepts found in statistics. The topics covered include the laws of probability, discrete and continuous random variables, standard discrete and continuous distributions, bivariate distributions, statistical models, sampling, estimation, hypothesis testing and statistical quality control.
Learning Outcomes
- Demonstrate an understanding of the concepts of probability, conditional probability, multiplicative law, independence, Bayes theorem and their interpretations.
- Be able to apply set theory to the proof and use of the axioms of probability.
- Understand and use combinatorial methods: counting rules; sampling with and without replacement; ordered and non-ordered samples.
- Be able to define discrete and continuous random variables and the corresponding probability distributions, probability functions, cumulative distribution functions and probability density functions.
- Understand and use transformations in the discrete and continuous variable context.
- Be able to define expectation and calculate expected values for the mean and variance of specific discrete and continuous distributions.
- Be able to define, interpret and apply the properties of the expectation and variance operators for discrete and continuous cases.
- Demonstrate an understanding of key discrete and continuous distributions including the specific circumstances when distributions may be applied.
- Demonstrate an ability to use statistical tables and deal with linear combinations of independent normal random variables.
- Be familiar with the Central limit theorem for the approximate distribution of sample mean and be able to utilise this theorem in the approximation of binomial and Poisson distributions.
- Understand and be able to define bivariate distributions, their joint probability (density) functions, cumulative distribution functions, marginal distributions, conditional distributions of discrete and continuous random variables.
- Demonstrate an understanding of independence for bivariate data.
- Be able to define expectation and to calculate expected values: means, variances and covariances, correlation coefficients for bivariate distributions and for linear combinations of random variables.
- Be able to define statistical models, experimental, systematic and random errors; precision and accuracy.
- Be able to describe and utilise the following methods of sampling: accessibility, judgement, quota, sequential, random, systematic, stratified and cluster sampling methods.
- Understand the concept of estimation, the definition of a statistic, sampling distribution, sample estimator, sample estimate and the desirable properties for an estimator.
- Be able to define and calculate an estimate of the population mean and variance from a single sample and from several samples.
- Demonstrate an understanding of and be able to implement the method of moments, maximum likelihood estimation and the method of least squares, in particular, the likelihood function, asymptotic variance, normal equations, and linear regression.
- Understand and be able to define the null and alternative hypotheses; one and two-sided tests; test statistic; critical region, P-value, significance level; type I and type II errors; power function and confidence intervals.
- Know when to apply the correct method for significance testing based on given circumstances.
- Be able to interpret results of a significance test and confidence intervals.
- Demonstrate an understanding and be able to describe non-parametric methods and their advantages and disadvantages.
- Understand, be able to carry out and interpret significance tests, in particular key parametric tests based on the Normal distribution, t-distribution, F-distribution and Chi squared distribution, and key non-parametric tests.
- Know when to apply and how to calculate nonparametric statistics and how to choose the appropriate technique to use for a practical example.Skills
- Understanding when and how to apply probability theory and reasoning with uncertainty.
- Knowing how to apply estimation approaches and the appropriate technique to use.
- Being able to apply probability theory to a practical example.
- Understanding the principles of hypothesis testing.
- Knowing when to apply the correct method for significance testing.
- Calculating test statistics and being able to use these to draw a conclusion about a null hypothesis.
- Knowing when to apply and how to calculate nonparametric statistics and choosing the appropriate technique to use for a practical example.Coursework
0%
Examination
90%
Practical
10%
Stage/Level
1
Credits
30
Module Code
SOR1020
Teaching Period
Full Year
Duration
24 weeks
Introduction to Statistical and Operational Research Methods
Overview
Introduction to statistical software for applying the following topics in Operational Research and Statistical Methods:
Linear Programming: Characteristics of linear programming models, general form. Graphical solution. Simplex method: standard form of linear programming problem, conversion procedures, basic feasible solutions. Simplex algorithm: use of artificial variables.
Decision Theory: Characteristics of a decision problem. Decision making under uncertainty: maximax, maximin, generalised maximin (Hurwicz), minimax regret criteria. Decision making under risk: Bayes criterion, value of perfect information. Decision tree; Bayesian decision analysis.
Random Sampling and Simulation: Random sample from a finite population, from a probability distribution. Use of random number tables. General method for drawing a random sample from a discrete distribution. Drawing a random sample from a continuous distribution: inverse transformation method, exponential distribution. Dynamic simulation techniques: application to queueing problems. Computer aspects: random number generators, sampling from normal distributions.
Initial Data Analysis: Scales of measurement. Discrete and continuous variables. Sample mean, variance, standard deviation, percentile for ungrouped data; boxplot. Frequency table for grouped discrete data: relative frequency, cumulative frequency, bar diagram; sample mean, variance, percentile. Frequency table for grouped continuous data: stem-and-leaf plot, histogram, cumulative percentage frequency plot; sample mean, variance, percentile. Linear transformation. Bivariate data; scatter diagram, sample correlation coefficient.Learning Outcomes
Perform linear programming using computer software.
Utilise decision analysis methods, such as decision trees.
Simulate date and produce random samples.
Calculate descriptive statistics for a given data set identifying the key characteristics and any unusual features.
Summarise data using appropriate graphical and tabular techniques.Skills
Apply a range of statistical and OR techniques to data using an appropriate method. Computational skills in statistical software to manage and analyse data. Ability to interpret results and add meaning to the analysis. Understanding sampling processes and the appropriate process to undertake.
Coursework
0%
Examination
0%
Practical
100%
Stage/Level
1
Credits
10
Module Code
SOR1021
Teaching Period
Spring
Duration
12 weeks
Actuarial Placement Preparation (0 credits)Actuarial Placement Preparation
Overview
This module is the first year component of the Employability classes for Actuarial Science students. It will focus on:
a: Understanding placement learning.
b: How to identify and prepare for placement opportunities.
c: Recording and self assessment of preparation process.Learning Outcomes
1. Preparation for Placement: Students will be able to understand and respond to the diversity, availability, accessibility and expectations of placement opportunities.
2. Placement Performance: Students will be able to record, review and realise the personal, career, and skill development opportunities of placement.
3 Placement Review and Application: Students will be able to identify the tangible value of placement learning and apply it to a graduate interview and presentation.Skills
1. Selective placement search (identifying and evaluating placement opportunities).
2. Interview and application skills
3. Presentation skills
4. Self-evaluation skillsCoursework
0%
Examination
90%
Practical
10%
Stage/Level
1
Credits
0
Module Code
FIN1015
Teaching Period
Spring
Duration
12 weeks
Financial Reporting and Analysis (20 credits)Financial Reporting and Analysis
Overview
Key financial statements and their users; income statement, statement of financial position and cash flow statement; use and limitations of financial ratio analysis; the relationship between accounting information and share price; introduction to creative accounting; introduction to two financial management issues, namely financing and working capital management; and investment appraisal.
Learning Outcomes
Understand the key elements in the preparation of a company's financial accounts; be able to interpret and analyse financial information of a company and the limitation of the techniques utilised; have worked in small groups and made tutorial presentations
Skills
Have a general understanding of financial reporting and analysis; develop a critical approach and evaluation to the interpretation of financial information relevant to a company.
Coursework
20%
Examination
70%
Practical
10%
Stage/Level
1
Credits
20
Module Code
FIN1003
Teaching Period
Autumn
Duration
12 weeks
- Year 2
Core Modules
Financial Risk Modelling (20 credits)Financial Risk Modelling
Overview
This module provides an introduction into practical areas of financial risk modelling, via model analysis (using Microsoft Excel and Monte Carlo simulation) and reporting
Learning Outcomes
Students will develop their understanding in the following areas:
Model Analysis and reporting
• Data analysis
• Financial and actuarial model development using Monte Carlo simulation
• Ability to analyse, apply and interpret model results
• Communication of the approach, results and conclusions
• Run-Off TrianglesSkills
The aim of this module is to give students an introduction to financial risk modelling including an introduction to the Institute and Faculty CA2 exam that is required to become a fully qualified actuary in the UK and Ireland.
Coursework
30%
Examination
0%
Practical
70%
Stage/Level
2
Credits
20
Module Code
FIN2021
Teaching Period
Spring
Duration
12 weeks
Actuarial methods in General Insurance (20 credits)Actuarial methods in General Insurance
Overview
The course provides a grounding in mathematical and statistical techniques with particular reference to their application in the field of General Insurance. Key topics include:
(i) Actuarial modelling;
(ii) Fundamentals of general insurance;
(iii) Loss distributions; and
(iv) Time series.Learning Outcomes
The aims of this module are to build on the mathematical and statistical techniques learned in the first year probability and statistics courses, and apply these to basic General Insurance problems faced by actuaries. Specifically, on completion of this module a student will be able to:
(i) Calculate probabilities and moments of loss distributions both with and without limits and risk-sharing arrangements,
(ii) Construct risk models involving frequency and severity distributions,
(iii) Recognise extreme value distributions,,
(iv) Understand the concepts underlying time series models and apply them,
(v) Use R Studio to assist with calculations in relation to the above topics.Skills
The course provides a grounding in mathematical and statistical techniques with particular reference to their application in the field of General Insurance. The course teaches students to place General Insurance in the context of a wider economic environment.
Coursework
0%
Examination
85%
Practical
15%
Stage/Level
2
Credits
20
Module Code
FIN2017
Teaching Period
Autumn
Duration
12 weeks
Excel Analysis (20 credits)Excel Analysis
Overview
This module looks at how to manage advanced spreadsheets in Excel, and use the Visual
Basic for Applications (VBA) programming language.Learning Outcomes
Upon successful completion of this module, students will be able to:
• Create and maintain complex spreadsheets
• Import data from a range of sources
• Prepare professional quality graphs and tables
• Use advanced functions
• Write and debug macros in VBA
• Develop financial models using Excel and VBASkills
This course provides opportunities for the students to acquire or enhance the following skills:
Excel and VBA
Data management
Data analysisCoursework
70%
Examination
0%
Practical
30%
Stage/Level
2
Credits
20
Module Code
FIN2030
Teaching Period
Autumn
Duration
12 weeks
Principles of Actuarial Modelling (20 credits)Principles of Actuarial Modelling
Overview
The course provides grounding in stochastic processes and their application. It also introduces survival models and provides some basic applications. The aims of this module are to: (i) describe the principles of actuarial modeling (ii) describe the general principles of stochastic processes (iii) define and apply a Markov chain and a Markov process (iv) introduce the concept of survival models
Learning Outcomes
At the end of this module students will be equipped to:
1. Describe the principles of actuarial modelling.
2.Differentiate between different stochastic processes.
3.Define and apply a Markov chain
4.Define and apply a Markov process.
5.Explain the concept of survival models
6.Carry out calculations on the above topics in MS Excel.Skills
Numerical, problem solving, mathematical modeling and group work skills.
Coursework
0%
Examination
85%
Practical
15%
Stage/Level
2
Credits
20
Module Code
FIN2012
Teaching Period
Spring
Duration
10 weeks
Actuarial Placement Learning (0 credits)Actuarial Placement Learning
Overview
This module is the second year component of the Placement classes for Actuarial Science students. It will focus on:
a: Understanding placement learning.
b: How to identify and prepare for placement opportunities.
c: Recording and self assessment of preparation process.Learning Outcomes
1. Preparation for Placement: Students will be able to understand and respond to the diversity, availability, accessibility and expectations of placement opportunities.
2. Placement Performance: Students will be able to record, review and realise the personal, career, and skill development opportunities of placement.
3 Placement Review and Application: Students will be able to identify the tangible value of placement learning and apply it to a graduate interview and presentation.Skills
1. Selective placement search (identifying and evaluating placement opportunities).
2. Interview and application skills
3. Presentation skills
4. Self-evaluation skillsCoursework
70%
Examination
0%
Practical
30%
Stage/Level
2
Credits
0
Module Code
FIN2023
Teaching Period
Full Year
Duration
24 weeks
Actuarial Mathematics 2 (20 credits)Actuarial Mathematics 2
Overview
(1) Intro to simple assurance and annuity contracts and derive relationships between them.
(2) Derive life table functions (lx & dx).
(3) Calculate net premiums and reserves for assurance and annuity contracts.
(4) Calculate gross premiums and reserves.
(5) Extending calculations to reflect joint life contracts.
(6) Modelling multiple decrements and looking at selection and mortality rates.Learning Outcomes
At the conclusion of this module students will be able to:
(1) Understand further actuarial functions allowing for decrements used and the mathematical techniques employed by an actuary
(2) Demonstrate the relationship between simple annuity and assurance functions
(3) Solve equations of value to determine premium levels or reserves.Skills
Numeracy and problem solving.
Coursework
15%
Examination
75%
Practical
10%
Stage/Level
2
Credits
20
Module Code
FIN2018
Teaching Period
Autumn
Duration
12 weeks
Investment Analysis (20 credits)Investment Analysis
Overview
Introduction and Investment Environment
Investment Project Evaluation
Security Analysis: Bond and Equity
Risk Aversion and Capital Allocation
Optimal Risky Portfolios
Capital Asset Pricing Model
Empirical Analysis on Security Returns
Portfolio Performance Evaluation
Market Efficiency and Behavioural Finance
Professional ethics in FinanceLearning Outcomes
Upon successful completion of this module students will:
- Understand the techniques for the evaluation of investment projects;
- Have the knowledge of the risk return relationship, portfolio theory, and professional ethics;
- Understand empirical analysis on security returns;
- Apply the tools they have acquired to set investment criteria, create and manage portfolios consisting of different assets, the most efficient manner for given aims and environment restrictions.Skills
Quantitative analysis, problem solving, logical reasoning, ability to evaluate/interpret financial data.
Coursework
0%
Examination
100%
Practical
0%
Stage/Level
2
Credits
20
Module Code
FIN2010
Teaching Period
Spring
Duration
12 weeks
- Year 3
Core Modules
Queen's Management School Placement Year (120 credits)Queen's Management School Placement Year
Overview
None
Coursework
70%
Examination
0%
Practical
30%
Stage/Level
3
Credits
120
Module Code
FIN3333
Teaching Period
Full Year
Duration
40 weeks
- Year 4
Core Modules
Stochastic Processes for Finance (20 credits)Stochastic Processes for Finance
Overview
1. STOCHASTIC PROCESSES:
The Poisson process, the Wiener process; Simulation of stochastic processes; Properties of stochastic processes; Ornstein-Uhlenbeck process
2. STOCHASTIC CALCULUS:
Stochastic integrals; Stochastic differential equations; The Ito rule
3. INVESTMENT STRATEGIES:
Self-financing portfolios; Average returns; Black-Scholes world; Optimal investment in the BS model; Diversification across assets
4. HEDGING STRATIGIES AND OPTION PRICING:
The BS equation; The BS formula; The pricing kernel; Risk-neutral pricing; The theorem of Girsanov; Risk management
5. TERM STRUCTURE MODELS OF INTEREST RATES:
Characteristics of a model for the term-structure of interest rates; The risk-neutral approach to the pricing of zerocoupon bonds and interest-rate derivatives for a general one-factor diffusion model for the risk-free rate of interest; State-price deflators to the pricing of zero-coupon bonds and interest-rate derivatives for a general one-factor diffusion model for the risk-free rate of interest; the Vasicek, Cox-Ingersoll-Ross and Hull-White models; Limitations of these one-factor modelsLearning Outcomes
Upon successful completion of this module students will:
1. Understand Wiener processes, Markov processes and Martingales and be able to apply these to solve practical problems
2. Understand basic concepts of Stochastic Calculus: Stochastic Integrals and Stochastic Differential Equations and the Ito Rule, and be able to apply these to solve finance and risk management problems
3 Demonstrate a knowledge and understanding of models of the term structure of interest rates
4. Appreciate the applications of advanced stochastic calculus in financial and other commercial environmentsSkills
On successful completion of this module students will be able to gain a range of problem solving, mathematical and financial modelling skills.
Coursework
15%
Examination
75%
Practical
10%
Stage/Level
4
Credits
20
Module Code
FIN3021
Teaching Period
Spring
Duration
12 weeks
Actuarial Econometrics and Data Science (20 credits)Actuarial Econometrics and Data Science
Overview
The aim of this course is to teach students to apply financial econometrics techniques sensibly in the context of real-world empirical problems, with particular focus on actuarial fields. Through software application (using R) students will be taught statistical techniques which underpin quantitative analysis in the financial world.
Learning Outcomes
At the conclusion of the course participants will be equipped to:
1. Understand the iterative process of real world data analysis.
2. Understand how to use statistical techniques to calibrate answers to many problems posed in actuarial science.
3. Understand how to source, prepare and encode financial data.
4. Obtain analytical skills to identify patterns in data.
5. Understand how to robustly infer real world effects from statistical analysis.
6. Understand how to encode analytical questions using statistical software (R).Skills
1. To interpret the results of robust statistical analysis of financial data sensibly.
2. Advanced software skills in visualisation and statistical analysis of financial data.Coursework
0%
Examination
55%
Practical
45%
Stage/Level
4
Credits
20
Module Code
FIN3026
Teaching Period
Autumn
Duration
12 weeks
Financial Engineering (20 credits)Financial Engineering
Overview
Mechanics of futures and forward markets. Hedging strategies using futures. Interest rate futures. Swaps. Option properties. Trading strategies with options. Hedging with options. Value at risk. Binomial option models. Credit risk and regulatory capital.
Learning Outcomes
To provide a theoretical and practical analysis of derivatives and derivative markets.
Skills
Have an understanding of the role of derivative markets and derivative instruments in today's financial market place; to be able to price derivatives, both theoretically and practically; to be comfortable with the use of software which prices and hedges derivatives; to be able to assess the risk sensitivities of options; to be able to construct hedging strategies using options.
Coursework
0%
Examination
75%
Practical
25%
Stage/Level
4
Credits
20
Module Code
FIN3017
Teaching Period
Autumn
Duration
12 weeks
Actuarial Modelling (20 credits)Actuarial Modelling
Overview
The course extends the principles taught in actuarial modelling to include the use of the Binomial and Poisson models for mortality modelling. The concept of graduation, including methods and statistical testing, is also covered.
The aims of the module are:
i. To understand the use of Binomial and Poisson models of mortality and their application in actuarial modelling.
ii. To understand how to estimate transition intensities depending on age, both exactly or via the census approximation
iii. Describe how to test crude estimates for consistency with a standard table or a set of graduated rates.
iv. Describe the process of graduation
v. Develop an appreciation of the application of predictive modelling and analytics beyond traditional actuarial work.Learning Outcomes
On successful completion of this module a student will be able to:
1. Describe the Binomial model of mortality as well as being able to derive
maximum likelihood estimator for the probability of death.
2. Describe the Poisson approximation to the estimator in the case of a single decrement mortality model.
3. Understand and explain the importance of dividing the data into homogenous classes.
4. Calculate a central exposed to risk given appropriate data.
5. Explain the concept of a rate interval
6. Describe various statistical tests (e.g. chi-square test, standardised deviations test, sign test etc) to compare crude mortality estimates to a standard table.
7. Understand and describe the reasons for graduating crude mortality intensities and probabilities.
8. Describe a test for smoothness of a set of graduated mortality rates. Describe the process of graduation via different methods (e.g. parametric formula, standard table, graphical).
9. Allow for the presence of duplicate policies when performing statistical tests.Skills
Numerical, problem solving, mathematical and actuarial modeling, statistical testing.
Coursework
25%
Examination
75%
Practical
0%
Stage/Level
4
Credits
20
Module Code
FIN3019
Teaching Period
Spring
Duration
12 weeks
Equity Research (20 credits)Equity Research
Overview
Firm valuation, valuation techniques, accounting & valuation, M&A, capital structure, corporate growth, value drivers, practice and pitfalls.
Learning Outcomes
• Assess the value of a company.
• Differentiate between different valuations techniques.
• Make independent buy/hold/sell recommendations.
• Critically assess practices carried out by equity analysts.
• Analyse relevant debates covered by the financial press and scholarly articles.Skills
The overall aim of the module is to prepare students for a career as an equity analyst. Students will be equipped with an understanding of different valuation techniques. Through the understanding of how equity investments are made students will be prepared to have a broader view of investment decisions and capital markets. Students will have the skill to make independent buy/sell/hold recommendation and interpret their analysis in light of investment criteria set by different investors. The module will be a good preparation for students that are looking to complete their CFA exams.
Coursework
30%
Examination
70%
Practical
0%
Stage/Level
4
Credits
20
Module Code
FIN3013
Teaching Period
Spring
Duration
12 weeks
Actuarial Applications (20 credits)Actuarial Applications
Overview
This module will assess your ability to communicate effectively in both writing and presentation
format to a non-actuarial/non-technical audience and in doing so will cover actuarial-related topics
such as pension schemes, pension fund investment, investment strategy, solvency 2 and capital
requirements.Learning Outcomes
Understand the role of communication in Actuarial Science
Develop clear and concise writing and presentation skills
Develop an understanding of the framework within which Actuarial decisions are made, implemented and managed
Develop an understanding of the importance of ethics, professionalism and the role of the professional body.Skills
Upon completing this course, students will have honed a comprehensive set of skills crucial for their professional development as actuaries. They will gain proficiency in articulating complex actuarial concepts clearly and concisely, ensuring that their writing and presentation skills are both accessible to non-specialists and informative to experts. The course will equip them with advanced writing and presentation abilities. The course also demonstrates how artificial intelligence (AI) can be used to appropriately enhance writing in actuarial science.
Furthermore, students will be able to provide an analysis of the environment within which actuarial decisions are made, implemented and managed. Students will also understand the role of an actuary in society and the idea of “always an actuary” in their professional and non-professional life.Coursework
100%
Examination
0%
Practical
0%
Stage/Level
4
Credits
20
Module Code
FIN3022
Teaching Period
Autumn
Duration
12 weeks
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Entry Requirements
Entrance requirements
| A level requirements A*AA including Mathematics OR AAA + A (AS) including A-level Mathematics A maximum of one BTEC/OCR Single Award or AQA Extended Certificate will be accepted as part of an applicant's portfolio of qualifications with a Distinction* being equated to a grade A at A-level. |
| Irish leaving certificate requirements H1H1H1H1H2H2 including Higher Level grade H1 in Mathematics |
| International Baccalaureate Diploma 36 points overall including 6,6,6 at Higher Level to include Higher Level Mathematics. If not offered at Higher Level/GCSE then Standard Level grade 4 in English would be accepted. |
| Access Course Not considered. |
| Graduate A minimum of a 2:1 Honours Degree provided subject requirements are also satisfied |
| Note All applicants must have GCSE English Language grade C/4 or an equivalent qualification acceptable to the University. |
Selection Criteria
In addition, to the entrance requirements above, it is essential that you read our guidance below on 'How we choose our students' prior to submitting your application.
Applications are dealt with centrally by the Admissions and Access Service rather than by Queen's Business School. Once your application has been processed by UCAS and forwarded to Queen's, an acknowledgement is normally sent within two weeks of its receipt by the University.
Selection is on the basis of the information provided on your UCAS form, which is considered by a member of administrative staff from the Admissions and Access Service and, if appropriate, the Selector from the School. Decisions are made on an ongoing basis and will be notified to you via UCAS.
Applicants for the BSc Honours in Actuarial Studies must be able to satisfy the University's General Entrance Requirement and, in addition, must meet the Mathematics subject requirement. Offers are made in terms of grades rather than UCAS Tariff points.
Actuarial Science and Risk Management is one of the most highly competitive degree courses at Queen's, where the number of applicants far outnumbers the places available. A key criterion used for making offers to applicants with A-level qualifications is an assessment of the applicant's GCSE grades. When considering applications, GCSE performance in the best nine subjects will be scored, with 4 points awarded for an A*/9 grade, 3 points for an A/8-7 grade, 2 points for a B/6 grade, and 1 point for a C*-C/5-4 grade. Please note that only GCSEs completed in Year 11 and Year 12 (Year 10 and Year 11 in England and Wales) will be counted for scoring purposes. We initially make offers to those applicants who score a minimum of 34 points. During the admissions cycle we constantly review the admissions statistics, comparing them to previous years, to assess if the points threshold can be lowered and more offers made. The number of points required to be considered for an offer varies every year depending on competition for places available, and cannot be predicted in advance. For guidance, for 2023 entry, the final threshold was 34 points.
For applicants offering the Irish Leaving Certificate, performance at Irish Junior Certificate (IJC) is taken into account. The best nine IJC subjects are considered, with 4 points being awarded for an A/Distinction grade, 3 points for a B/Higher Merit grade, and 1 point for a C/Merit grade. We initially make offers to those applicants who score a minimum of 34 points. This offer threshold may be lowered as the cycle progresses, as for A-level applicants. The number of points required to be considered for an offer varies every year depending on competition for places available, and cannot be predicted in advance. For guidance, for 2023 entry, the final threshold was 34 points.
Applicants offering a range of other qualifications e.g. BTEC Extended Diplomas, Higher National Diplomas and Foundation Access courses are not normally considered unless the applicant can meet, or has met, the Mathematics subject requirement.
In addition to the academic requirements above, the information provided in the personal statement section and the academic reference together with predicted grades are noted, but these are not the final deciding factors as to whether or not a conditional offer can be made. However, they may be reconsidered in a tie break situation in August.
A-level General Studies and A-level Critical Thinking will not normally be considered as part of a three A-level offer and, although they may be excluded where an applicant is taking 4 A-level subjects, the grade achieved could be taken into account if necessary in August/September.
If you are made an offer then you may be invited to an Open Day organised by Queen's Business School, which is usually held in the second semester. This will allow you the opportunity to visit the University, to find out more about the degree programme of your choice, the facilities on offer together with a flavour of the academic and social life at Queen's.
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
An IELTS score of 6.5 with a minimum of 5.5 in each test component or an equivalent acceptable qualification, details of which are available at: http://go.qub.ac.uk/EnglishLanguageReqs
If you need to improve your English language skills before you enter this degree programme, INTO Queen's University Belfast 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.
International Students - Foundation and International Year One Programmes
INTO Queen's offers a range of academic and English language programmes to help prepare international students for undergraduate study at Queen's University. You will learn from experienced teachers in a dedicated international study centre on campus, and will have full access to the University's world-class facilities.
These programmes are designed for international students who do not meet the required academic and English language requirements for direct entry.
- Foundation
The INTO progression course suited to this programme is
http://www.intostudy.com/en-gb/universities/queens-university-belfast/courses/international-foundation-in-business-humanities-and-social-sciences.
INTO - English Language Course(QSIS ELEMENT IS EMPTY)
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Careers
Career Prospects
Introduction
Students pursuing a career in Actuarial Science should enjoy working with numbers, be effective communicators and work well with people as they will have to analyse and interpret financial and other information to meet the needs of different users, including managers and investors.
http://www.prospects.ac.uk
Employment after the Course
The traditional areas in which actuaries are employed include:
Pensions Industry - Actuaries are involved in the management and valuation of pension scheme liabilities (for regulatory purposes). They are also involved in new design and restructuring of pension schemes, deficit management and any requirements of regulatory change on pension schemes.
Investment Industry - Actuaries are involved in a wide variety of work such as pricing financial derivatives, working in fund management or working in quantitative investment research.
Life and Non-Life Insurance Industries - Actuaries design new insurance policies and calculate premium rates for the protection of life (whole life or term assurance) or personal items (car insurance or buildings and contents). Actuaries also perform reserving calculations to demonstrate solvency of the company.
Employment Links
Graduate employers include: KPMG, Spence & Partners, Irish Life, Invesco, Boal & Co, Willis Towers Watson, Allianz Insurance, Mercer, AXA Insurance, Deloitte, Milliman, Liberty Mutual Insurance, PwC, Pramerica, Metlife, XPS.
Alumni Success
"Queen’s gave me the tools to succeed, such as the ability to solve problems and analyse complex situations. It helped me develop strong communication and presentation skills as well as a commercial awareness of the financial industry. I now work as a Commercial Actuary at Allianz which involves estimating the value of claims and premiums to ensure solvency and profitability. I am also involved in pricing work for our main property and small business accounts and through building actuarial models I advise the underwriters on how they should determine technical premiums for customers. I hope to further develop my leadership skills to accompany my technical knowledge and move into more senior roles, gaining experience across a wide range of areas such as reserving, pricing and capital modelling.”
Kevin O’Reilly, Commercial Actuary at Allianz Insurance
Professional Opportunities
Recent placement providers have included Aviva, Irish Life, Kerr Henderson, Spence & Partners, SCOR, The Pension Protection Fund and Pramerica.
What employers say
Additional Awards Gained
Year in Industry
Prizes and Awards
A number of local employers and professional bodies sponsor prizes on an annual basis for best students in their level, module or category.
These include Invesco, The Company of Actuaries Charitable Trust Fund, Kerr Henderson, SCOR Global Life, Mercer, Pramerica, Spence and Partners, Acumen Resources, XPS, and Allianz Re Dublin.
Degree 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 Degree Plus/Future Ready Award. It's what makes studying at Queen's University Belfast special.
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Fees and Funding
Tuition Fees
| Northern Ireland (NI) 1 | £4,750 |
| Republic of Ireland (ROI) 2 | £4,750 |
| England, Scotland or Wales (GB) 1 | £9,250 |
| EU Other 3 | £20,800 |
| International | £20,800 |
1 EU 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 and will be subject to an annual inflationary increase, unless explicitly stated otherwise.
Tuition fee rates are calculated based on a student’s tuition fee status and generally increase annually by inflation. How tuition fees are determined is set out in the Student Finance Framework.
Additional course costs
All Students
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. A programme may have up to 6 modules per year, each with a recommended text.
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 final year 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.
Actuarial Science and Risk Management costs
Students undertake a placement in year 3 and are responsible for funding travel, accommodation and subsistence costs. These costs vary depending on the location and duration of the placement.
A limited amount of funding may be available to contribute towards these additional costs, if the placement takes place through a government student mobility scheme.
Student who undertake optional study tours are expected to make a contribution, of approximately £150.
How do I fund my study?
There are different tuition fee and student financial support arrangements for students from Northern Ireland, those from England, Scotland and Wales (Great Britain), and those from the rest of the European Union.
Information on funding options and financial assistance for undergraduate students is available at www.qub.ac.uk/Study/Undergraduate/Fees-and-scholarships/.
Scholarships
Each year, we offer a range of scholarships and prizes for new students. Information on scholarships available.
International Scholarships
Information on scholarships for international students, is available at www.qub.ac.uk/Study/international-students/international-scholarships/.
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Apply
How and when to Apply
How to Apply
Application for admission to full-time undergraduate and sandwich courses at the University should normally be made through the Universities and Colleges Admissions Service (UCAS). Full information can be obtained from the UCAS website at: www.ucas.com/students.
When to Apply
UCAS will start processing applications for entry in autumn 2024 from 1 September 2023.
Advisory closing date: 31 January 2024 (18:00). This is the 'equal consideration' deadline for this course.
Applications from UK and EU (Republic of Ireland) students after this date are, in practice, considered by Queen’s for entry to this course throughout the remainder of the application cycle (30 June 2024) subject to the availability of places.
Applications from International and EU (Other) students are normally considered by Queen’s for entry to this course until 30 June 2024. If you apply for 2024 entry after this deadline, you will automatically be entered into Clearing.
Applicants are encouraged to apply as early as is consistent with having made a careful and considered choice of institutions and courses.
The Institution code name for Queen's is QBELF and the institution code is Q75.
Further information on applying to study at Queen's is available at: www.qub.ac.uk/Study/Undergraduate/How-to-apply/
Terms and Conditions
The terms and conditions that apply when you accept an offer of a place at the University on a taught programme of study. Queen's University Belfast Terms and Conditions.
Additional Information for International (non-EU) Students
- Applying through UCAS
Most students make their applications through UCAS (Universities and Colleges Admissions Service) for full-time undergraduate degree programmes at Queen's. The UCAS application deadline for international students is 30 June 2024. - Applying direct
The Direct Entry Application form is to be used by international applicants who wish to apply directly, and only, to Queen's or who have been asked to provide information in advance of submitting a formal UCAS application. Find out more. - Applying through agents and partners
The University’s in-country representatives can assist you to submit a UCAS application or a direct application. Please consult the Agent List to find an agent in your country who will help you with your application to Queen’s University.
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Fees and Funding