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Students
Tuition Fee
USD 20,700
Per course
Start Date
Medium of studying
On campus
Duration
9 months
Program Facts
Program Details
Degree
Diploma
Major
Actuarial Science | Probability Theory | Statistics
Area of study
Mathematics and Statistics
Education type
On campus
Timing
Full time
Course Language
English
Tuition Fee
Average International Tuition Fee
USD 20,700
Intakes
Program start dateApplication deadline
2023-10-06-
2024-01-15-
About Program

Program Overview


Actuaries provide assessments of financial security systems, with a focus on their complexity, their mathematics, and their mechanisms. Actuaries quantify the probability and manage the risk of future events in areas such as insurance, healthcare, pensions, investment, and banking and also in non-financial areas. This course is taught by the Department of Mathematical Sciences and is intended for students with a first degree in mathematics, statistics, economics or finance who would like to acquire knowledge in actuarial science. Our Postgraduate Diploma Actuarial Science course is based on the syllabus of the majority of the core subjects of the Institute and Faculty of Actuaries, so you’ll cover subjects as part of your course CB1 (Business Finance) depending on the optional module selected, CM2 (Financial Engineering and Loss Reserving) and CS2 (Risk Modelling and Survival Analysis). This focus on up-to-date research findings in actuarial methodologies and actuarial applications means that you gain a solid training in actuarial modelling and actuarial analysis. It is also possible to specialise on a topic of choice, with options including:
  • Actuarial and financial modelling
  • General insurance
  • Life insurance
You will also have the chance to study a problem in depth through a Masters thesis project on a subject chosen by you or your supervisor. As part of our Department of Mathematical Sciences you’re a member of an inclusive and approachable research community with an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology. We are genuinely innovative and student-focused. Our research groups are working on a broad range of collaborative areas tackling real-world issues. Here are a few examples:
  • Our data scientists carefully consider how not to lie, and how not to get lied to with data. Interpreting data correctly is especially important because much of our data science research is applied directly or indirectly to social policies, including health, care and education.
  • We do practical research with financial data (for example, assessing the risk of collapse of the UK’s banking system) as well as theoretical research in financial instruments such as insurance policies or asset portfolios.
  • We also research how physical processes develop in time and space. Applications of this range from modelling epilepsy to modelling electronic cables.
  • Our optimisation experts work out how to do the same job with less resource, or how to do more with the same resource.
  • Our pure maths group are currently working on two new funded projects entitled ‘Machine learning for recognising tangled 3D objects’ and ‘Searching for gems in the landscape of cyclically presented groups’.
  • We also do research into mathematical education and use exciting technologies such as electroencephalography or eye tracking to measure exactly what a learner is feeling. Our research aims to encourage the implementation of ‘the four Cs’ of modern education, which are critical thinking, communication, collaboration, and creativity.
Why we're great.
  • Study the majority of the Core Technical subjects of the Institute and Faculty of Actuaries.
  • Work alongside expert academics and practising actuaries.
  • Through our pioneering teaching approach we develop the actuarial scientists of the future.

Our expert staff

Many of our academics have won national or regional awards for lecturing, and many of them are qualified and accredited teachers – something which is very rare at a university. Our course teachers are expert academics conducting internationally excellent multidisciplinary research, with significant multi-year experience in consulting and practicing actuarial science. Our key actuarial science staff are Professor Spyridon Vrontos (specialising in actuarial and financial data science, predictive modelling and predictability), Dr Tolulope Fadina (mathematical finance), Dr Junlei Hu (reinsurance and optimal risk transfer), Dr Peng Liu (applied probability and queueing systems), Dr Jackie Wong (Bayesian methods and survival analysis), and Dr John O’Hara (financial mathematics and machine learning in finance).

Specialist facilities

  • You have access to our renowned maths and stats skills support , which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
  • We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
  • We host events and seminars throughout the year

Your future

We expect our graduates of MSc Actuarial Science to become actuaries in a range of industries. It has been predicted by the US Department of Labor that the employment of actuaries is expected to grow faster than any other occupation, making it a great prospect for a graduate job. Aside from a rewarding career as an actuary, clear thinkers are required in every profession, so the successful mathematician has an extensive choice of potential careers. The Council for Mathematical Sciences offers further information on careers in mathematics. We also work with the University’s Careers Services to help you find out about further work experience, internships, placements, and voluntary opportunities. We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability; applied statistics, bioinformatics and mathematical biology, and our department is strongly committed to research and to the promotion of graduate activities.

Program Outline

Course structure

Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field. The following modules are based on the current course structure and may change in response to new curriculum developments and innovation. We understand that deciding where and what to study is a very important decision for you. We’ll make all reasonable efforts to provide you with the courses, services and facilities as described on our website. However, if we need to make material changes, for example due to significant disruption, or in response to COVID-19, we’ll let our applicants and students know as soon as possible.


Components

Components are the blocks of study that make up your course. A component may have a set module which you must study, or a number of modules from which you can choose. Each component has a status and carries a certain number of credits towards your qualification.
Status What this means
Core You must take the set module for this component and you must pass. No failure can be permitted.
Core with Options You can choose which module to study from the available options for this component but you must pass. No failure can be permitted.
Compulsory You must take the set module for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Compulsory with Options You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Optional You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
The modules that are available for you to choose for each component will depend on several factors, including which modules you have chosen for other components, which modules you have completed in previous years of your course, and which term the module is taught in.


Modules

Modules are the individual units of study for your course. Each module has its own set of learning outcomes and assessment criteria and also carries a certain number of credits. In most cases you will study one module per component, but in some cases you may need to study more than one module. For example, a 30-credit component may comprise of either one 30-credit module, or two 15-credit modules, depending on the options available. Modules may be taught at different times of the year and by a different department or school to the one your course is primarily based in. You can find this information from the module code . For example, the module code HR100-4-FY means:
HR 100 4 FY
The department or school the module will be taught by. In this example, the module would be taught by the Department of History. The module number. The UK academic level of the module. A standard undergraduate course will comprise of level 4, 5 and 6 modules - increasing as you progress through the course. A standard postgraduate taught course will comprise of level 7 modules. A postgraduate research degree is a level 8 qualification. The term the module will be taught in.
  • AU : Autumn term
  • SP : Spring term
  • SU : Summer term
  • FY : Full year
  • AP : Autumn and Spring terms
  • PS: Spring and Summer terms
  • AS: Autumn and Summer terms
Year 1 What do you understand about Bayes’ theorem and Bayesian statistical modelling? Or about Markov chain Monte Carlo simulation? Focus on Bayesian and computational statistics. Understand the statistical modelling and methods available. Learn to develop a Monte Carlo simulation algorithm for simple probability distributions. View Bayesian Computational Statistics on our Module Directory How do you define simple assurance contracts? What practical methods are required to evaluate expected values from a contract? How can you calculate gross premiums and reserves of assurance and reserves? Understand the mathematical techniques that can calculate, model and value cashflows dependent on death, survival or other uncertain risks. View Contingencies I on our Module Directory This module will enable you to expand your knowledge on multiple statistical methods. You will learn the concepts of decision theory and how to apply them, have the chance to explore “Monte Carlo” simulation, and develop an understanding of Bayesian inference, and the basic concepts of a generalised linear model. View Statistical Methods on our Module Directory Ever considered becoming an Actuary? This module covers the required material for the Institute and Faculty of Actuaries CT4 and CT6 syllabus. It explores the stochastic process and principles of actuarial modelling alongside time series models and analysis. View Stochastic Processes on our Module Directory Why are arbitrage arguments important in modern finance? How can a binomial model evaluate derivatives? What are the main models for interest rates? Understand the mathematical techniques underlying the modelling of derivative pricing. Acquire skills in the development of pricing and risk management. Explore stochastic methods and credit risk. View Financial Derivatives on our Module Directory What are the principles of actuarial modelling? And what are survival models? Examine how calculations in clinical trials, pensions, and life and health insurance require reliable estimates of transition intensities/survival rates. Learn how to estimate these intensities. Build your understanding of estimation procedures for lifetime distributions. View Survival Analysis on our Module Directory How do you formulate financial decision problems mathematically? And how do you identify an appropriate method of solution? Understand the basic models and mathematical methods underlying modern portfolio management. Assess the limitations of these models and learn to correctly interpret your results from calculations. View Mathematics of Portfolios on our Module Directory COMPONENT 08: COMPULSORY WITH OPTIONS MA211-7-SP or MA312-7-SP (15 CREDITS) What skills do you need to succeed during your studies? And what about after university? How will you realise your career goals? Develop your transferable skills and experiences to create your personal profile. Reflect on and plan your ongoing personal development, with guidance from your personal advisor within the department. View Research Skills and Employability on our Module Directory


Teaching

  • Core components can be combined with optional modules, to enable you to gain either in-depth specialisation or a breadth of understanding
  • Learn to use LATEX to produce a document as close as possible to what professional mathematicians produce in terms of organisation, layout and type-setting
  • Our postgraduates are encouraged to attend conferences and seminars on a Thursday afternoon


Assessment

  • Courses are assessed on the results of your written examinations, together with continual assessments of your practical work and coursework
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