(Postgraduate Diploma) Postgraduate Diploma
University of Essex
University of Essex
Mathematics, Statistics and Operational Research
A degree with an overall mid 2.2 in one of the following subjects: Mathematics, Statistics, Operational research, Finance, Economics, Business Engineering, Computing, Biology, Physics or Chemistry.
Will consider applicants with a unrelated degree but which contained at least three modules in calculus, algebra, differential equations, probability & statistics, optimisation or other mathematical modules.
Applications from students with a 2:2 or equivalent will be considered dependent on any relevant professional or voluntary experience, previous modules studied and/or personal statement.
IELTS (International English Language Testing System) code
IELTS 6.0 overall with a minimum component score of 5.5
If you do not meet our IELTS requirements then you may be able to complete a pre-sessional English pathway that enables you to start your course without retaking IELTS.
The University uses academic selection criteria to determine an applicant’s ability to successfully complete a course at the University of Essex. Where appropriate, we may ask for specific information relating to previous modules studied or work experience.
Rules of assessment
Rules of assessment are the rules, principles and frameworks which the University uses to calculate your course progression and final results.
Prof Fionn Murtagh
Professor of Data Science
External Examiners provide an independent overview of our courses, offering their expertise and help towards our continual improvement of course content, teaching, learning, and assessment.
External Examiners are normally academics from other higher education institutions, but may be from the industry, business or the profession as appropriate for the course.
They comment on how well courses align with national standards, and on how well the teaching, learning and assessment methods allow students to develop and demonstrate the relevant knowledge and skills needed to achieve their awards.
External Examiners who are responsible for awards are key members of Boards of Examiners. These boards make decisions about student progression within their course and about whether students can receive their final award.
This course is based on modules that cover the syllabus of the following Core Technical subjects of the Institute and Faculty of Actuaries, CT4, CT5, CT6, CT8 and (depending on the options chosen) one of CT2 and CT3. The syllabus is covered as required by the IFoA by 80% or more. The course includes a series of taught modules, providing up-to-date research findings in actuarial methodologies and actuarial applications. The course provides a solid training in actuarial modelling and actuarial analysis. The course aims to provide an advanced understanding of the theoretical, practical and technological developments that affect the whole of the actuarial discipline. There are a number of possible areas of specialization within the program, including Life Insurance, General Insurance and Actuarial and Financial Modelling. The M.Sc. in Actuarial Science aims to prepare students for careers as practicing actuaries in the insurance, pension, financial and consulting industries.
The course also provides the foundation for a career in many areas of actuarial science, finance and risk. It is also based on modules that cover the syllabus of the majority of the Core Technical subjects of the Institute and Faculty of Actuaries.
The course will produce specialists who will help meet the demand for actuaries to support the local, and national economy, and beyond.
The aims of the Postgraduate Diploma in Actuarial Science are:
To develop students' ability to formulate and solve advanced actuarial problems and to understand and apply complex techniques to the solution of problems in all the areas of current professional actuarial practice;
To develop skills and ability to use the advanced mathematical and statistical techniques used in actuarial science, and their application to solving actuarial problems;
To develop the skill of interpretation of statistical and actuarial outputs, integration of numerical and non-numerical information, understanding the advantages and disadvantages of arguments based on quantitative information;
To provide advanced knowledge about the insurance sector, the financial sector and risk management;
To provide students with a knowledge and skills base from which to develop further abilities to understand and critically analyse advanced life insurance and general insurance problems;
To form all rounded actuarial professionals with excellent grounding in the mathematical and statistical approach;
To provide a favourable teaching and learning environment for students to evolve, thrive and achieve their potential.
Learning outcomes and learning, teaching and assessment methods
On successful completion of the programme a graduate should demonstrate knowledge and skills as follows:
A: Knowledge and understanding
A1: Knowledge and understanding of the use of mathematics for modelling and as an investigative tool for the solution of practical problems. An appreciation of the importance of assumptions.
A2: Understanding of contemporary theories relating to portfolio analysis, asset allocation and the market efficiency debate
A3: Knowledge and understanding of the principles of finance relevant to Actuarial Science.
A4: Knowledge and understanding of the principles of specific actuarial mathematics techniques
A5: Knowledge and understanding of the subjects of probability and inference and specialist statistics applications in insurance
A6: Knowlede and understanding of information technology skills as relevant to an actuary
A7: A range of ideas concerning Mathematics and Finance, including methods appropriate in specialized applications and some knowledge of relevant probabilistic/statistical/computing ideas.
A8: Knowledge and understanding of the application of reasoning in financial analysis to applied topics.
A9: Analyse in-depth financial techniques that are used in actuarial science.
A10: Critically analyse life insurance and survival analysis data and apply complex techniques for life insurance pricing.
Lectures are the principal method of delivery for the concepts and principles involved in A1 – A10. Students are also directed to reading from textbooks and material available on-line. In some modules, understanding is enhanced through the production of a written report, and also by means of laboratories and assignments.
Achievement of knowledge outcomes is assessed primarily through unseen closed-book examinations, and also, in some modules through marked coursework, laboratory reports, statistical assignments, project reports and oral examinations.
Regular problem sheets provide formative assessment in most modules.
B: Intellectual and cognitive skills
B1: Analyse a specified problem and choose the most suitable methods and tools for its solution.
B2: Assess the relative merits of a range of theories, techniques and tools needed for a problem's solution or to articulate arguments and policies.
B3: Synthesise and interpret information from a range of sources (lectures, classes, journals, books, etc.) developing a critical evaluation of the importance and relevance of the sources to an area of study.
B4: Construct reasoned, informed and concise descriptions and assessments of accounting or finance ideas.
B5: Critically evaluate contemporary theories and empirical evidence, marshal evidence, develop an argument (in writing) and present ideas in a coherent and effective manner;
B6: Manipulate and analyse numerical (including financial) data and appreciate the nature and limitations of basic statistical concepts;
The basis for intellectual skills is provided in lectures, and the skills are developed by means of recommended reading, guided and independent study, assignments and project work.
Achievement of intellectual skills is assessed primarily through unseen closed-book examinations, and also through marked assignments and project work.
C: Practical skills
C1: Use computer packages and/or programming languages for data analysis and computation and use computer packages for presentation of material to others.
C2: The ability to apply a rigorous, analytic, highly numerate approach to a problem.
C3: Identify, select and gather information, using the relevant sources.
C4: Organise ideas in a systematic way.
C5: Present financial ideas and arguments coherently in writing.
C6: Use and apply the terminology and concepts of finance.
The students learn to use the R programming language and Microsoft Excel in a variety of actuarial, financial and statistical tasks.
The practical skills of actuarial science including mathematics, statistics and finance are developed in exercise classes, laboratory classes, assignments and project work.
Achievement of practical skills is assessed through marked coursework and project reports.
D: Key skills
D1: Communicate effectively, both mathematical arguments and textual accounts of ideas.
D2: Use appropriate IT facilities as a tool in the analysis of mathematical problems.
D3: Use mathematical techniques correctly.
D4: Analyse complex problems and find effective solutions.
D5: Organise activity and manage time in the course of study.
D6: Capacity to: (a) organise and implement a plan of independent study, (b) reflect on his or her own learning experience and adapt in response to feedback; (c) recognise when he or she needs to learn more and appreciate the role of additional research.
D1 is practised throughout the scheme in the writing of solutions to mathematical problems, both for assessment and as exercises, and (in some modules) writing reports or projects.
D1 and D2 are developed in group and individual project work.
D2 is developed through the use of computer packages in a number of modules.
D3 - D6 are developed in exercises and assignments throughout the course.
D1 is assessed through examinations, coursework and oral examinations.
D2 is assessed primarily through coursework.
Assessment of the key skills D3 - D6 is intrinsic to subject based assessment.