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Risk is opportunity – being an actuary is a shrewd career choice. Our MSci Actuarial Science and Data Science is an Integrated Masters course that will teach you the art of turning risk into opportunity with the understanding of visualising data in actuarial applications and beyond. Such a skillset is crucial for the growing market for experts in data science with the collection and analysis of data being crucial to understanding how to improve, create and guide products and services across the globe.
Our attractive blend of actuarial science and data science will equip you with an understanding of real-world financial issues, efficient use of experimental design to provide fast and less expensive solutions, and computing skills essential for entering the actuarial and data science profession.
You’ll be taught theory and methods used by professional actuaries; on how to apply mathematical and statistical skills to minimise financial risk when the stakes are high, in areas such as commerce, government, insurance and finance. You’ll be provided with the crucial basis of core skills in data base programming and management, in developing data processing pipelines and in organising and analysing large and massive data sets. And you’ll be introduced to and use programming language Python and R for statistical analysis and data visualisation. In your third and fourth year, analysing data and methods in group projects will be essential capstone modules for the learning outcomes of the course.
Topics include:
Mathematical skills and finance
Computer science and programming
Statistics and operations research
Artificial intelligence, databases and information retrieval
Ethical issues around the use and processing of data
Specialist skills in the areas of big data, data analytics and data science
Our Integrated Masters will give you the opportunity to fast-track your degree and complete your final year in nine months compared with a regular MSc which usually takes twelve months. Combining your undergraduate and postgraduate study in one degree will give you a strong theoretical background as well as specialist expertise through independent research. This combination makes graduates from our course attractive candidates for many employers.
Why we're great.
You have access to our ultramodern facilities at our new STEM Centre that provide real-world experience.
You join a community of scholars leading the way in technological research and development.
We have active links with industry to broaden your employment potential and placement opportunities.
Our expert staff
As well as being world-class academics, our staff are award-winning teachers. 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.
Teaching on our course are expert academics and practising actuaries. The key departmental staff for our BSc Actuarial Science are Keith Bannister, Dr Haslifah Hashim, and Dr Spyridon Vrontos.
Keith Bannister is a qualified actuary, and a Fellow of the Institute and Faculty of Actuaries; he lectures part-time in actuarial science.
Dr Hashim specialises in life and general insurance, pensions, financial mathematics, enterprise risk management, forensic economics, and Islamic finance and takafu.
Dr Vrontos specialises in actuarial mathematics and modelling, asset-liability management and performance measurement for pension funds, hedge funds and mutual funds, risk management and solvency, and risk theory.
Specialist facilities
In addition to teaching, we have a Maths Support Centre, which offers help to students 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 a dedicated social and study space for Maths students in the department, which is situated in the new £18m STEM Centre
We host regular events and seminars throughout the year
Our students run a lively Mathematics Society, an active and social group where you can explore your interest in your subject with other students
Your future
Demand for skilled graduates in the areas of mathematics, big data, data science and actuarial science is growing rapidly in both the public and private sector, and there is a predicted shortage of data scientists with the skills to understand and make commercial decisions based on the analysis of big data. It is 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. An incredible 89% of our undergraduate maths students are in employment or further study (Graduate Outcomes 2020).
We also work with our University's Student Development Team to help you find out about further work experience, internships, placements, and voluntary opportunities.
Entry requirements
Clearing entry requirements
Specific entry requirements for this course in Clearing are not published here but for most of our degree courses you will need to hold a Level 3 qualification. If you are interested in applying and have already received your results, use our Clearing application form to apply for 2021 entry and find out if you are eligible. You will be asked to provide details of your qualifications and grades.
Structure
Course structure
We offer a flexible course structure with a mixture of compulsory and optional modules chosen from lists. The first three undergraduate years listed below are an example structure from the current academic year. Your course structure could differ from this if modules change from year-to-year. The final Masters year shows you all of the modules currently available (compulsory and optional) so you can see the breadth of what is on offer.
Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field. The course content is therefore reviewed on an annual basis to ensure our courses remain up-to-date so modules listed are subject to change.
Teaching and learning disclaimer
Following the impact of the pandemic, we made changes to our teaching and assessment to ensure our current students could continue with their studies uninterrupted and safely. These changes included courses being taught through blended delivery, normally including some face-to-face teaching, online provision, or a combination of both across the year.
The teaching and assessment methods listed show what is currently planned for 2021 entry; changes may be necessary if, by the beginning of this course, we need to adapt the way we’re delivering them due to the external environment, and to allow you to continue to receive the best education possible safely and seamlessly.
Components and modules explained
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.
This module will allow you to build your knowledge of differentiation and integration, how you can solve first and second order differential equations, Taylor Series and more.
Can you perform simple operations on complex numbers? How do you solve systems of linear equations using row operations? Can you calculate the determinant and inverse of a matrix? Understand the basics of linear algebra, with an emphasis on vectors and matrices.
This module introduces you to programming skills in the context of a range of mathematical modelling topics. Mathematical modelling skills will be an important focus alongside learning how to structure and implement codes in both Matlab and R. A key part of the module will be investigative open-ended computational modelling studies at both the group and individual level.
How do you apply the addition rule of probability? Or construct appropriate diagrams to illustrate data sets? Learn the basics of probability (combinatorial analysis and axioms of probability), conditional probability and independence, and probability distributions. Understand how to handle data using descriptive statistics and gain experience of R software.
This module introduces you to finance as a subject area. You gain an overview of the financial system, instruments and markets and explore important financial concepts and problems. Topics include investment companies, return and risk and behavioural finance.
How do consumers make decisions? Or firms conduct different market strategies? What impact does government policy have on inflation? Or unemployment? Develop your knowledge of economics in relation to a range of contemporary issues. Learn how to apply both micro and macroeconomic principles to the analysis of such problems.
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.
The subject of ordinary differential equations is a very important branch of Applied Mathematics. Many phenomena from Physics, Biology, Engineering, Chemistry, Finance, among others, may be described using ordinary differential equations. To understand the underlying processes, we have to find and interpret the solutions to these equations. The last part of the module is devoted to the study of nonlinear differential equations and stability. This module provides an overview of standard methods for solving single ordinary differential equations and systems of ordinary differential equations, with an introduction to the underlying theory.
What instruments are used by companies to raise finance and manage financial risk? What is the role of financial institutions operating in financial markets? What are the techniques of financial accounting? How do you use spreadsheets in financial analysis? Examine and develop the concepts and elements of corporate finance.
In this module you'll be introduced to the basics of probability and random variables. Topics you will discuss include distribution theory, estimation and Maximum Likelihood estimators, hypothesis testing, basic linear regression and multiple linear regression implemented in R.
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.
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.
What tools can you use for macroeconomic analysis? And how can these then be applied to macro-policy issues? Learn how to build alternative macroeconomic models and apply analytical reasoning. Examine real-life macroeconomic questions, on topics such as government budgets or wage-price flexibility, and critically evaluate macroeconomic policies.
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.
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.
What methods are available to model cashflows that are contingent on competing risk? What techniques for discounted emerging costs can be used in pricing, reserving and assessing profitability? Study the methods and techniques used in pricing and evaluating insurance and pension products, and insurance companies.
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.
How do consumers behave in a competitive market? And what about producers? How do various imperfections affect the outcome of decentralised markets? Study the fundamental concepts and methods in microeconomics. Understand the tools and methods of analysis for economic reasoning, and develop your critical approach to economic issues and policies.
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.
This module will allow you to step out of the classroom and gain real experience in your selected branch of Mathematics that you could not gain from a lecture. You will be able to develop your ability to work independently on research and produce a project report on your topic of interest.
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.
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.
Advanced Capstone Project: Actuarial Science, Data Science or Mathematics
(30 CREDITS)
Our Advanced Capstone Projects are opportunities for students to study independently a topic in mathematics, statistics and related areas (such as mathematical physics, data science, modelling and so on) and develop skills such as writing reports and giving presentations. You will be monitored by a supervisor, who will periodically set tasks and discuss the progress of the work.
The key purpose of Advanced Capstone Projects is that you should be given the opportunity to show your strengths and be allowed a certain amount of freedom and leeway in how you complete the project. It will also provide opportunities for you to develop transferable communication, time- and task-management skills, through researching the topic and organising and producing the written and oral reports.
Looking to build your research capabilities? This module will equip you with the principal research tools for your postgraduate course in Mathematical Sciences, including practice in the mathematical word-processing language LaTeX.
Humans can often perform a task extremely well (e.g., telling cats from dogs) but are unable to understand and describe the decision process followed. Without this explicit knowledge, we cannot write computer programs that can be used by machines to perform the same task. “Machine learning” is the study and application of methods to learn such algorithms automatically from sets of examples, just like babies can learn to tell cats from dogs simply by being shown examples of dogs and cats by their parents. Machine learning has proven particularly suited to cases such as optical character recognition, dictation software, language translators, fraud detection in financial transactions, and many others.
Can you calculate confidence intervals for parameters and prediction intervals for future observations? Represent a linear model in matrix form? Or adapt a model to fit growth curves? Learn to apply linear models to analyse data. Discuss underlying assumptions and standard approaches. Understand methods to design and analyse experiments.
Our events are a great way to find out more about studying at Essex. We run a number of Open Days throughout the year which enable you to discover what our campus has to offer.
You have the chance to:
tour our campus and accommodation
find out answers to your questions about our courses, student finance, graduate employability, student support and more
meet our students and staff
Check out our Visit Us pages to find out more information about booking onto one of our events. And if the dates aren’t suitable for you, feel free to book a campus tour here.
Once you’ve checked that we have the right course for you, applying couldn’t be simpler. Fill in our quick and easy Clearing application form with as much detail as you can. We’ll then take a look and get back to you with a decision. There’s no need to call us to apply; just do it all online.
We don’t interview all applicants during Clearing, however, we will only make offers for the following course after a successful interview:
BA Multimedia Journalism
BSc Nursing (Adult)
BSc Nursing (Mental Health)
BA Social Work
The interview allows our academics to find out more about you, and in turn you’ll be able to ask us any questions you might have.
Further details will be emailed to you if you are shortlisted for interview.
Home to 15,000 students from more than 130 countries, our Colchester Campus is the largest of our three sites, making us one of the most internationally diverse campuses on the planet - we like to think of ourselves as the world in one place.
The Campus is set within 200 acres of beautiful parkland, located two miles from the historic town centre of Colchester – England's oldest recorded town. Our Colchester Campus is also easily reached from London and Stansted Airport in under one hour.
If you live too far away to come to Essex (or have a busy lifestyle), no problem. Our 360 degree virtual tours allows you to explore our University from the comfort of your home. Check out our Colchester virtual tour and Southend virtual tour to see accommodation options, facilities and social spaces.
Exhibitions
Our staff travel the world to speak to people about the courses on offer at Essex. Take a look at our list of exhibition dates to see if we’ll be near you in the future.
At Essex we pride ourselves on being a welcoming and inclusive student community. We offer a wide range of support to individuals and groups of student members who may have specific requirements, interests or responsibilities.
The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include, but are not limited to: strikes, other industrial action, staff illness, severe weather, fire, civil commotion, riot, invasion, terrorist attack or threat of terrorist attack (whether declared or not), natural disaster, restrictions imposed by government or public authorities, epidemic or pandemic disease, failure of public utilities or transport systems or the withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications.
The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and
Ordinances and in the University Regulations, Policy and Procedures.
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