Actuarial Science

Actuarial Science - BSc (Hons)
with a Year in Industry

Undergraduate Open Days

Join us at the Medway campus on Saturday 24 June or the Canterbury campus on Saturday 1 July. Hear from staff and students about our courses, find out about our accommodation and see our stunning campuses for yourself.

If you’d like a high-paying career in finance or insurance… If you’re good at mathematics, enjoy problem-solving and are interested in financial matters… you should consider studying actuarial science.

Overview

Actuaries evaluate and manage financial risks, particularly in the financial services industry. Our specialist programmes are taught by professionally qualified actuaries and internationally renowned statisticians to ensure you are fully prepared for your career.

Our Year in Industry programme enables you to gain paid industry experience in addition to being taught by our professionally qualified actuaries and internationally-renowned statisticians to ensure you are fully prepared for your future career.

Why study an Actuarial Science degree at Kent

  • Our degree programmes are fully accredited by the Institute and Faculty of Actuaries, which means that you can achieve up to six exemptions from the 13 professional examinations required to become a qualified actuary.
  • You can take a year in industry and gain invaluable actuarial work experience.
  • You’ll learn to use industry standard software like PROPHET and R.
  • You’ll benefit from the extensive industrial experience of our professional actuaries.
  • You’ll study in award-winning classrooms and breakout spaces that have been specially designed for mathematical sciences.
  • You'll be able to join brilliant student societies for specialist workshops, revision sessions, socials and networking events.

What you’ll study

You’ll immerse yourself in the mathematics, statistics, finance and economics that you need to qualify as an actuary. You’ll also develop skills that are highly valued by employers, including data science, coding in R and PROPHET, financial modelling and commercial awareness.

Foundation year

If you do not have the qualifications for direct entry to this programme, you may be able to take a four-year degree with a foundation year. For more details see Actuarial Science with a Foundation Year.

Featured video

Watch to find out why you should study at Kent.

Actuarial Science student leaving the Sibson Building
If I were to go back in time knowing what I know now, I would still pick Kent.

Joey Chong - Actuarial Science with a Year in Industry

Entry requirements

The University will consider applications from students offering a wide range of qualifications. All applications are assessed on an individual basis but some of our typical requirements are listed below. Students offering qualifications not listed are welcome to contact our Admissions Team for further advice. Please also see our general entry requirements.

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    A level

    Applications are individually considered. Please contact an Admissions Officer.

  • medal-empty Access to HE Diploma

    The University will not necessarily make conditional offers to all Access candidates but will continue to assess them on an individual basis.  

    If we make you an offer, you will need to obtain/pass the overall Access to Higher Education Diploma and may also be required to obtain a proportion of the total level 3 credits and/or credits in particular subjects at merit grade or above. 

  • medal-empty BTEC Nationals

    The University will consider applicants holding BTEC National Diploma and Extended National Diploma Qualifications (QCF; NQF; OCR) on a case-by-case basis. Please contact us for further advice on your individual circumstances.

  • medal-empty International Baccalaureate

    Applications are individually considered. Please contact an Admissions Officer. 

  • medal-empty International Foundation Programme

    N/A

  • medal-empty T level

    The University will consider applicants holding T level qualifications in subjects closely aligned to the course.

International students

If you are an international student, visit our International Student website for further information about entry requirements for your country, including details of the International Foundation Programmes. Please note that international fee-paying students who require a Student visa cannot undertake a part-time programme due to visa restrictions.

Please note that meeting the typical offer/minimum requirement does not guarantee that you will receive an offer.

English Language Requirements

Please see our English language entry requirements web page.

Please note that if you do not meet our English language requirements, we offer a number of 'pre-sessional' courses in English for Academic Purposes. You attend these courses before starting your degree programme.

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Course structure

Duration: 4 years

Modules

The following modules are indicative of those offered on this programme. This listing is based on the current curriculum and may change year to year in response to new curriculum developments and innovation.  

On most programmes, you study a combination of compulsory and optional modules. You may also be able to take ‘elective’ modules from other programmes so you can customise your programme and explore other subjects that interest you.

Stage 1

Compulsory modules currently include

The aim of this module is to introduce students to core economic principles and how these could be used in a business environment to understand economic behaviour and aid decision making, and to provide a coherent coverage of economic concepts and principles. Indicative topics covered by the module include the working of competitive markets, market price and output determination, decisions made by consumers on allocating their budget and by producers on price and output, and different types of market structures and the implication of each for social welfare, the working of the economic system, governments' macroeconomic objectives, unemployment, inflation, economic growth, international trade and financial systems and financial crises.

This module will cover a number of syllabus items set out in Subject CB2 – Business Economics published by the Institute and Faculty of Actuaries.

The aim of this module is to provide a grounding in the principles of modelling as applied to financial mathematics – focusing particularly on deterministic models which can be used to model and value known cashflows. Indicative topics covered by the module include data and basics of modelling, theory of interest rates, equation of value and its applications. This module will cover a number of syllabus items set out in Subject CM1 – Actuarial Mathematics published by the Institute and Faculty of Actuaries.

The aim of the module is to give students an understanding of the types of work undertaken within the actuarial profession, and a basic grounding in the core skills required by actuaries.

Indicative topics covered by the module include an overview of the actuarial profession, an introduction to Microsoft Excel, an introduction to interest rates and cash flow models. This module will cover a number of syllabus items set out in Subject CM1 – Actuarial Mathematics published by the Institute and Faculty of Actuaries.

This module serves as an introduction to algebraic methods and linear algebra methods. These are central in modern mathematics, having found applications in many other sciences and also in our everyday life.

Indicative module content:

Basic set theory, Functions and Relations, Systems of linear equations and Gaussian elimination, Matrices and Determinants, Vector spaces and Linear Transformations, Diagonalisation, Orthogonality.

To be confirmed.

Introduction to Probability. Concepts of events and sample space. Set theoretic description of probability, axioms of probability, interpretations of probability (objective and subjective probability).

Theory for unstructured sample spaces. Addition law for mutually exclusive events. Conditional probability. Independence. Law of total probability. Bayes' theorem. Permutations and combinations. Inclusion-Exclusion formula.

Discrete random variables. Concept of random variable (r.v.) and their distribution. Discrete r.v.: Probability function (p.f.). (Cumulative) distribution function (c.d.f.). Mean and variance of a discrete r.v. Examples: Binomial, Poisson, Geometric.

Continuous random variables. Probability density function; mean and variance; exponential, uniform and normal distributions; normal approximations: standardisation of the normal and use of tables. Transformation of a single r.v.

Joint distributions. Discrete r.v.'s; independent random variables; expectation and its application.

Generating functions. Idea of generating functions. Probability generating functions (pgfs) and moment generating functions (mgfs). Finding moments from pgfs and mgfs. Sums of independent random variables.

Laws of Large Numbers. Weak law of large numbers. Central Limit Theorem.

Introduction to R and investigating data sets. Basic use of R (Input and manipulation of data). Graphical representations of data. Numerical summaries of data.

Sampling and sampling distributions. ?² distribution. t-distribution. F-distribution. Definition of sampling distribution. Standard error. Sampling distribution of sample mean (for arbitrary distributions) and sample variance (for normal distribution) .

Point estimation. Principles. Unbiased estimators. Bias, Likelihood estimation for samples of discrete r.v.s

Interval estimation. Concept. One-sided/two-sided confidence intervals. Examples for population mean, population variance (with normal data) and proportion.

Hypothesis testing. Concept. Type I and II errors, size, p-values and power function. One-sample test, two sample test and paired sample test. Examples for population mean and population variance for normal data. Testing hypotheses for a proportion with large n. Link between hypothesis test and confidence interval. Goodness-of-fit testing.

Association between variables. Product moment and rank correlation coefficients. Two-way contingency tables. ?² test of independence.

Stage 2

Compulsory modules currently include

The aim of this module is to provide a grounding in the principles of modelling as applied to actuarial work – focusing particularly on deterministic models which can be used to model and value cashflows which are dependent on death, survival, or other uncertain risks. Indicative topics covered by the module include equations of value and its applications, single decrement models, multiple decrement and multiple life models. This module will cover a number of syllabus items set out in Subject CM1 – Actuarial Mathematics published by the Institute and Faculty of Actuaries.

Find out more about MACT5160

The aim of this module is to provide a basic understanding of corporate finance including a knowledge of the instruments used by companies to raise finance and manage financial risk. Indicative topics covered by the module include corporate governance and organisation, taxation, dividend policy, how corporates are financed, and evaluating projects. This module will cover a number of syllabus items set out in Subject CB1 – Business Finance published by the Institute and Faculty of Actuaries.

Find out more about MACT5270

The aim of this module is to provide the ability to construct and interpret the accounts and financial statements of companies and financial institutions, to construct management information and to evaluate working capital.

This module will cover a number of syllabus items set out in Subject CB1 – Business Finance published by the Institute and Faculty of Actuaries.

Find out more about MACT5280

Constructing suitable models for data is a key part of statistics. For example, we might want to model the yield of a chemical process in terms of the temperature and pressure of the process. Even if the temperature and pressure are fixed, there will be variation in the yield which motivates the use of a statistical model which includes a random component. In this module, students study linear regression models (including estimation from data and drawing of conclusions), the use of likelihood to estimate models and its application in simple stochastic models. Both theoretical and practical aspects are covered, including the use of R.

Find out more about MAST5001

Probability: Joint distributions of two or more discrete or continuous random variables. Marginal and conditional distributions. Independence. Properties of expectation, variance, covariance and correlation. Poisson process and its application. Sums of random variables with a random number of terms.

Transformations of random variables: Various methods for obtaining the distribution of a function of a random variable —method of distribution functions, method of transformations, method of generating functions. Method of transformations for several variables. Convolutions. Approximate method for transformations.

Sampling distributions: Sampling distributions related to the Normal distribution — distribution of sample mean and sample variance; independence of sample mean and variance; the t distribution in one- and two-sample problems.

Statistical inference: Basic ideas of inference — point and interval estimation, hypothesis testing.

Point estimation: Methods of comparing estimators — bias, variance, mean square error, consistency, efficiency. Method of moments estimation. The likelihood and log-likelihood functions. Maximum likelihood estimation.

Hypothesis testing: Basic ideas of hypothesis testing — null and alternative hypotheses; simple and composite hypotheses; one and two-sided alternatives; critical regions; types of error; size and power. Neyman-Pearson lemma. Simple null hypothesis versus composite alternative. Power functions. Locally and uniformly most powerful tests.

Composite null hypotheses. The maximum likelihood ratio test.

Interval estimation: Confidence limits and intervals. Intervals related to sampling from the Normal distribution. The method of pivotal functions. Confidence intervals based on the large sample distribution of the maximum likelihood estimator – Fisher information, Cramer-Rao lower bound. Relationship with hypothesis tests. Likelihood-based intervals.

Find out more about MAST5007

This module covers aspects of Statistics which are particularly relevant to insurance. Some topics (such as risk theory and credibility theory) have been developed specifically for actuarial use. Other areas (such as Bayesian Statistics) have been developed in other contexts but now find applications in actuarial fields. Indicative topics covered by the module include Bayesian Statistics; Loss Distributions; Reinsurance and Ruin; Credibility Theory; Risk Models; Ruin Theory; Generalised Linear Models; Extreme Value Theory. This module will cover a number of syllabus items set out in Subjects CS1 and CS2 – Actuarial Statistics published by the Institute and Faculty of Actuaries.

Find out more about MAST5010

Optional modules may include

In this module we will study linear partial differential equations, we will explore their properties and discuss the physical interpretation of certain equations and their solutions. We will learn how to solve first order equations using the method of characteristics and second order equations using the method of separation of variables.

Introduction to linear PDEs: Review of partial differentiation; first-order linear PDEs, the heat equation, Laplace's equation and the wave equation, with simple models that lead to these equations; the superposition principle; initial and boundary conditions

Separation of variables and series solutions: The method of separation of variables; simple separable solutions of the heat equation and Laplace’s equation; Fourier series; orthogonality of the Fourier basis; examples and interpretation of solutions

Solution by characteristics: the method of characteristics for first-order linear PDEs; examples and interpretation of solutions; characteristics of the wave equation; d’Alembert’s solution, with examples; domains of influence and dependence; causality.

Find out more about MAST5005

Formulation/Mathematical modelling of optimisation problems

Linear Optimisation: Graphical method, Simplex method, Phase I method, Dual problems,

Transportation problem.

Non-linear Optimisation: Unconstrained one dimensional problems, Unconstrained high dimensional problems, Constrained optimisation.

Find out more about MAST5011

This module is designed to provide students with an introduction to the use of data analytics tools on large data sets including the analysis of text data. The module will begin by discussing the principles of text-mining and big data. The module will then discuss the techniques that can be used to explore large data sets (including pre-processing and cleaning) and the use of multivariate statistical techniques for supervised and unsupervised learning. The module will conclude by considering several data mining techniques.

Syllabus: What is "big data"? What is text mining? Exploratory data analysis for large datasets, and pre-processing and cleaning; Multivariate statistical analysis (both unsupervised, e.g. factor analysis or principle component analysis, and supervised, e.g. linear discriminant analysis); Data security; Data mining including techniques such as classification trees, neural networks, clustering, text analysis or network analysis.

Find out more about MAST5956

Year in industry

You spend a year working in industry between Stages 2 and 3. We can offer help and advice in finding a placement. This greatly enhances your CV and gives you the opportunity to apply your academic skills in a practical context. It also gives you an idea of your career
options. Recent placements have included RSA Group, Lloyds and the Bank of England. 

Compulsory modules currently include

Students spend a year (minimum 44 weeks) working in an industrial, commercial, public sector or similar setting, applying and enhancing the skills and techniques they have developed and studied in the earlier stages of their degree course.

The work they do is entirely under the direction of their industrial supervisor, but support is provided by the CEMS Employability and Placements Team . This support includes ensuring that the work they are being expected to do is such that they can meet the learning outcomes of the module.

Participation in this module, is dependent on students obtaining an appropriate placement, for which support and guidance is provided through the CEMS Employability and Placements Team. It is also dependent on students progressing satisfactorily from Stage 2 of their studies.

Students who do not obtain a placement will be required to transfer to the appropriate course without a Year in Industry.

Find out more about MAST5801

Students spend a year (minimum 44 weeks) doing paid work in an organisation outside the University, in an industrial, commercial, public sector, or similar setting, applying and enhancing the skills and techniques they have developed and studied in the earlier stages of their degree course.

The Assessments required for this module should provide evidence of the subject specific and generic learning outcomes, and of reflection by the student on them as an independent learner.

The placement work they do is entirely under the direction of their industrial supervisor, but support is provided by the CEMS Employability and Placements Team. This support includes ensuring that the work they are being expected to do is such that they can meet the learning outcomes of this module.

Participation in the placement year, and hence in this module, is dependent on students obtaining an appropriate placement, for which support and guidance is provided by the CEMS Employability and Placements Team. It is also dependent on students progressing satisfactorily from Stage 2 of their studies.

Students who do not obtain a placement will be required to transfer to the appropriate course without a Year in Industry.

Find out more about MAST5802

Stage 3

Compulsory modules currently include

The aim of this module is to provide a grounding in mathematical and statistical modelling techniques that are of particular relevance to survival analysis and their application to actuarial work.

Calculations in life assurance, pensions and health insurance require reliable estimates of transition intensities/survival rates. This module covers the estimation of these intensities and the graduation of these estimates so they can be used reliably by insurance companies and pension schemes. The syllabus also includes the study of various other survival models, and an introduction to machine learning. This module will cover a number of syllabus items set out in Subject CS2 – Actuarial Mathematics published by the Institute and Faculty of Actuaries.

Find out more about MACT5250

The aim of this module is to provide a grounding in the principles of modelling as applied to actuarial work – focusing particularly on deterministic models which can be used to model and value cashflows which are dependent on death, survival, or other uncertain risks. Indicative topics covered by the module include equations of value and its applications, single decrement models, multiple decrement and multiple life models, pricing and reserving. This module will cover a number of syllabus items set out in Subject CM1 – Actuarial Mathematics published by the Institute and Faculty of Actuaries.

Find out more about MACT5330

The aim of this module is to provide a grounding in the principles of modelling as applied to actuarial work – focusing particularly on stochastic asset liability models. These skills are also required to communicate with other financial professionals and to critically evaluate modern financial theories.

Indicative topics covered by the module include theories of financial market behaviour, measures of investment risk, stochastic investment return models, asset valuations, and liability valuations.

This module will cover a number of syllabus items set out in Subject CM2 – Actuarial Mathematics 2 published by the Institute and Faculty of Actuaries.

Find out more about MACT5350

The aim of this module is to provide a grounding in the principles of modelling as applied to actuarial work – focusing particularly on the valuation of financial derivatives. These skills are also required to communicate with other financial professionals and to critically evaluate modern financial theories.

Indicative topics covered by the module include theories of stochastic investment return models and option theory.

This module will cover a number of syllabus items set out in Subject CM2 – Actuarial Mathematics published by the Institute and Faculty of Actuaries.

Find out more about MACT5370

This module is split into two parts:

1. An introduction to the practical experience of working with the financial software package, PROPHET, which is used by commercial companies worldwide for profit testing, valuation and model office work. The syllabus includes: overview of the uses and applications of PROPHET, introduction on how to use the software, setting up and performing a profit test for a product , analysing and checking the cash flow results obtained for reasonableness, using the edit facility on input files, performing sensitivity tests , creating a new product using an empty workspace by selecting the appropriate indicators and variables for that product and setting up the various input files, debugging errors in the setting up of the new product, performing a profit test for the new product and analysing the results.

2. An introduction to financial modelling techniques on spreadsheets which will focus on documenting the process of model design and communicating the model's results. The module enables students to prepare, analyse and summarise data, develop simple financial and actuarial spreadsheet models to solve financial and actuarial problems, and apply, interpret and communicate the results of such models.

Find out more about MACT5390

The module will give students an understanding of the practical application of the techniques they learn in the BSc in Actuarial Science. It brings together skills from other modules, and ensures that students have the necessary entry-level skills and knowledge to join the actuarial profession or to embark on related careers, and also provides a platform for ongoing professional development. The syllabus is dynamic, changing regularly to reflect current practice and trends.

Find out more about MACT6013

Introduction: Principles and examples of stochastic modelling, types of stochastic process, Markov property and Markov processes, short-term and long-run properties. Applications in various research areas.

Random walks: The simple random walk. Walk with two absorbing barriers. First–step decomposition technique. Probabilities of absorption. Duration of walk. Application of results to other simple random walks. General random walks. Applications.

Discrete time Markov chains: n–step transition probabilities. Chapman-Kolmogorov equations. Classification of states. Equilibrium and stationary distribution. Mean recurrence times. Simple estimation of transition probabilities. Time inhomogeneous chains. Elementary renewal theory. Simulations. Applications.

Continuous time Markov chains: Transition probability functions. Generator matrix. Kolmogorov forward and backward equations. Poisson process. Birth and death processes. Time inhomogeneous chains. Renewal processes. Applications.

Queues and branching processes: Properties of queues - arrivals, service time, length of the queue, waiting times, busy periods. The single-server queue and its stationary behaviour. Queues with several servers. Branching processes. Applications.

In addition, level 7 students will study more complex queuing systems and continuous-time branching processes.

This module will cover a number of syllabus items set out in Subject CS2 published by the Institute and Faculty of Actuaries. This is a dynamic syllabus, changing regularly to reflect current practice.

Find out more about MAST6360

Stationary Time Series: Stationarity, autocovariance and autocorrelation functions, partial autocorrelation functions, ARMA processes.

ARIMA Model Building and Testing: estimation, Box-Jenkins, criteria for choosing between models, diagnostic tests for residuals of a time series after estimation.

Forecasting: Holt-Winters, Box-Jenkins, prediction bounds.

Testing for Trends and Unit Roots: Dickey-Fuller, ADF, structural change, trend-stationarity vs difference stationarity.

Seasonality and Volatility: ARCH, GARCH, ML estimation.

Multiequation Time Series Models: transfer function models, vector autoregressive moving average (VARM(p,q)) models, impulse responses.

Spectral Analysis: spectral distribution and density functions, linear filters, estimation in the frequency domain, periodogram.

Simulation: generation of pseudo-random numbers, random variate generation by the inverse transform, acceptance rejection. Normal random variate generation: design issues and sensitivity analysis.

This module will cover a number of syllabus items set out in Subject CS2 published by the Institute and Faculty of Actuaries. This is a dynamic syllabus, changing regularly to reflect current practice.

Find out more about MAST6390

Fees

The 2023/24 annual tuition fees for this course are:

  • Home full-time £9,250
  • EU full-time £13,500
  • International full-time £18,000

For details of when and how to pay fees and charges, please see our Student Finance Guide.

For students continuing on this programme, fees will increase year on year by no more than RPI + 3% in each academic year of study except where regulated.* 

Your fee status

The University will assess your fee status as part of the application process. If you are uncertain about your fee status you may wish to seek advice from UKCISA before applying.

Fees for year in industry

Fees for undergraduate students are £1,385.

Fees for year abroad

Fees for undergraduate students are £1,385.

Students studying abroad for less than one academic year will pay full fees according to their fee status.

Additional costs

Find out more about accommodation and living costs, plus general additional costs that you may pay when studying at Kent.

Funding

We have a range of subject-specific awards and scholarships for academic, sporting and musical achievement.

Search scholarships

Kent offers generous financial support schemes to assist eligible undergraduate students during their studies. See our funding page for more details. 

The Kent Scholarship for Academic Excellence

At Kent we recognise, encourage and reward excellence. We have created the Kent Scholarship for Academic Excellence. 

The scholarship will be awarded to any applicant who achieves a minimum of A*AA over three A levels, or the equivalent qualifications (including BTEC and IB) as specified on our scholarships pages.

Teaching and assessment

Most of the teaching is by lectures and examples classes. At Stage 1, you can go to regular supervised classes where you can get help and advice on the way you approach problems. Modules that include programming or working with computer software packages usually involve practical sessions.

Each year, there are a number of special lectures by visiting actuaries from external organisations, to which all students are invited. These lectures help to bridge the gap between actuarial theory and its practical applications.

The course provides practical experience of working with PROPHET, a market-leading actuarial software package used by commercial companies worldwide for profit testing, valuation and model office work. 

Modules are assessed by end-of-year examinations, or by a combination of coursework and examinations.

Contact hours

For a student studying full time, each academic year of the programme will comprise 1200 learning hours which include both direct contact hours and private study hours.  The precise breakdown of hours will be subject dependent and will vary according to modules.  Please refer to the individual module details under Course Structure.

Methods of assessment will vary according to subject specialism and individual modules.  Please refer to the individual module details under Course Structure.

Programme aims

We aim to help students develop:

  • Equip students with the technical appreciation, skills and knowledge appropriate to graduates in mathematical subjects. 

  • Develop students’ facilities of rigorous reasoning and precise expression. 

  • Develop students’ capabilities to formulate and solve problems. 

  • Develop in students appreciation of recent actuarial developments, and of the links between the theory of the subjects and their practical application in industry. 

  • Develop in students a logical, mathematical approach to solving problems. 

  • Develop in students an enhanced capacity for independent thought and work. 

  • Ensure students are competent in the use of information technology, and are familiar with computers, together with the relevant software. 

  • Provide students with opportunities to study advanced topics, engage in research at some level, and develop communication and personal skills. 

  • Provide successful students with eligibility for up to 6 exemptions from examinations of the Institute and Faculty of Actuaries.  

  • For the programme involving a year in industry, to enable students to gain awareness of the application of technical concepts in the workplace. 

Learning outcomes

Knowledge and understanding

You gain knowledge and understanding of:

  • Core mathematical understanding in the principles of calculus, algebra, mathematical methods, discrete mathematics, analysis and linear algebra. 
  • Statistical understanding in the subjects of probability and inference and time series modelling, plus specialist statistics applications in insurance. 
  • Information technology skills as relevant to actuaries. 
  • Methods and techniques appropriate to the mathematics of finance, of finance and financial reporting, and of financial economics. 
  • The principles of economics as relevant to actuaries. 
  • Methods and techniques appropriate to survival models.
  • The principles of specific actuarial mathematics techniques.
  • Understanding of the core areas of actuarial practice.  

Outcome specific to the Year in Industry programme: 

Aspects of the core subject areas from the perspective of a commercial or industrial organisation. 

Intellectual skills

You gain the following intellectual abilities:

  • Ability to demonstrate a reasonable understanding of the main body of knowledge for the course. 
  • Ability to demonstrate a reasonable level of skill in calculation and manipulation of the material written within the course and some capability to solve problems formulated within it. 
  • Ability to apply a range of core concepts and principles in well-defined contexts relevant to actuarial science. 
  • Ability to use logical argument. 
  • Ability to demonstrate skill in solving problems by various appropriate methods. 
  • Ability in relevant computer skills and usage. 
  • Ability to demonstrate research, presentation and report-writing skills. 
  • Ability to work with relatively little guidance. 

Outcome specific to the Year in Industry programme:

Use of the intellectual skills specified for the programme in the context of a commercial or industrial organisation. 

Subject-specific skills

You gain actuarial-science skills in the following:

  • Skills in the specific mathematical and statistical techniques used in actuarial science, and in their application to solving actuarial problems. 
  • Skills in the specific information technology and software used in actuarial science.
  • Understanding of the practical applications of the course material in insurance.  
  • Ability to develop simple actuarial computer models to solve actuarial problems and to interpret and communicate the results.     

Outcome specific to the Year in Industry programme:  

Application of some of the subject-specific skills specified for the programme from the perspective of a commercial or industrial organisation. 

Transferable skills

You gain transferable skills in the following:

  • Problem-solving skills, relating to qualitative and quantitative information. 
  • Communication skills, covering both written and oral communication. 
  • Numeracy and computational skills. 
  • Information-retrieval skills, in relation to primary and secondary information sources, including information retrieval through on-line computer searches. 
  • Information technology skills such as word-processing and spreadsheet use, internet communication, etc. 
  • Interpersonal skills, relating to the ability to interact with other people and to engage in team-working. 
  • Time-management and organisational skills, as evidenced by the ability to plan and implement efficient and effective modes of working.  
  • Study skills needed for continuing professional development. 

Independent rankings

Mathematics at Kent was ranked 19th for student satisfaction in The Complete University Guide 2023.

Careers

Graduate destinations

The Actuarial Science programme allows you to gain exemptions from the professional examinations set by the UK actuarial profession, so our graduates have a head start when looking to qualify as actuaries. It also provides an excellent foundation for careers in many other areas of finance and risk.

Recent graduates have gone on to work in:

  • insurance companies and consultancy practices
  • the Government Actuary’s Department
  • the London Stock Exchange
  • other areas of financial management.

Help finding a job

The University has a friendly Careers and Employability Service, which can give you advice on how to:

  • apply for jobs
  • write a good CV
  • perform well in interviews.

Career-enhancing skills

You graduate with an excellent grounding in the fundamental concepts and principles of actuarial science, together with practical experience in the use of industry-standard actuarial software.

To help you appeal to employers, you also learn key transferable skills that are essential for all graduates. These include the ability to:

  • think critically
  • communicate your ideas and opinions
  • manage your time effectively
  • work independently or as part of a team.

You can also gain extra skills by signing up for one of our Kent Extra activities, such as learning a language or volunteering.

Apply for Actuarial Science with a Year in Industry - BSc (Hons)

If you are from the UK or Ireland, you must apply for this course through UCAS. If you are not from the UK or Ireland, you can apply through UCAS or directly on our website if you have never used UCAS and you do not intend to use UCAS in the future.

Find out more about how to apply

All applicants

International applicants

Contact us

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International student enquiries

Enquire online

T: +44 (0)1227 823254
E: internationalstudent@kent.ac.uk

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