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Full time | Colchester Campus | 1 year | 06-OCT-22

Study mode

Full time

Duration

1 year

Start date

06-OCT-22

Key information
DATA SOURCE : IDP Connect

Qualification type

MSc - Master of Science

Subject areas

Actuarial Science Statistical Analysis

Course type

Taught

Course Summary

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 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 MSc Actuarial Science course is based on the syllabus of most 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.

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.

Modules

This is a dissertation module for MSc students. Student will be provided with a list of dissertation titles or your own, provided a member of staff agrees it is of suitable standard and is able to supervise it.

Tuition fees

UK fees
Course fees for UK students

For this course (per year)

9,200

International fees
Course fees for EU and international students

For this course (per year)

19,740

Entry requirements

We will consider applicants with a 2:2 degree in one of the following subjects: Mathematics, Statistics, Operational research, Computer Science, Applied Mathematics, Pure Mathematics, Biostatistics, Economic Statistics, Statistics, Economics OR a 2.2 degree in any subject which includes one module in: Calculus, Maths, Engineering Maths, Advanced Maths and one module in Statistics or Probability, Maths, Engineering Maths, Advanced Maths and one additional relevant module, from Algebra, Analysis, Programming language (R, Matlab or Python), a second module in Probability or Statistics, Numerical Methods, Complex Numbers, Differential Equations, Optimisation (Linear Programming), Regression, Stochastic Process, Maths, Engineering Maths, Advanced Maths. Applicants with a degree below 2:2 or equivalent will be considered dependent on any relevant professional or voluntary experience and previous modules studied.

University information

The University of Essex is a hub of innovation and stereotype-breaking success. It offers students a fantastic academic experience, and a fresh way of thinking about some of the key challenges faced by society today. The university delivers an impressive selection of postgraduate courses at a number of levels, including master’s programmes, doctoral degrees, research positions and short courses for continued professional development. The...more

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