Actuarial Science

Actuarial Science with a Foundation Year - BSc (Hons)

UCAS code N325

This is an archived page and for reference purposes only

2019

Actuaries evaluate and manage financial risks, particularly in the financial services industry. If you are good at mathematics, enjoy problem-solving and are interested in financial matters, you should enjoy studying actuarial science. This programme with a foundation year offers you a route into actuarial science if you don't currently meet the entry requirements for the three-year degree course.

Overview

Our Foundation Year programme provides an opportunity for you to develop your mathematics skills and start learning some university-level material, fully preparing you for university study before you progress onto the Actuarial Science degree.

Our specialist programme combines the in-house expertise of our professionally qualified actuaries and internationally-renowned mathematicians and statisticians to ensure you are fully prepared for your future career.

You are encouraged to fulfil your potential while studying in our friendly and dynamic school based in the multi-award-winning Sibson Building.

This programme has been designed for those who have achieved grades or are predicted grades significantly lower than our standard AAA or AAB entry requirements, including overseas applicants from regions where A Level Mathematics or equivalent is not taught.   

Our degree programme

To help bridge the gap between school and university, you’ll cover material from the A Level Mathematics and Further Mathematics syllabuses, along with advanced topics taken from university-level studies preparing you for university. Alongside mathematics, you can choose optional modules covering topics from computing to history. 

Upon passing the Foundation Year, you can progress onto BSc Actuarial Science, with or without a Year in Industry. 

In Stage 1 you’ll continue to receive support through small group tutorials, where you can practice the new mathematics you’ll be learning, ask questions and work with other students to find solutions. You’ll study a mixture of pure and applied mathematics, statistics and economics, providing you with a solid foundation for your later studies.

In Stages 2 and 3 you study modules that align with the professional exemptions from the Institute and Faculty of Actuaries (IFoA), preparing you for your career as a qualified actuary.

During your studies, you will learn how to use PROPHET, an actuarial software widely used by the profession, along with other key computer software packages.

Accreditation - Institute and Faculty of Actuaries Curriculum 2019

This year, the Institute and Faculty of Actuaries (IFoA) is introducing a new actuarial qualification structure called Curriculum 2019.  We are delighted to say that we have successfully achieved re-accreditation for all of our Actuarial Science programmes and will be offering exemptions under the IFoA's new qualification structure from September 2019. 

Extra activities

Kent is home to the Invicta Actuarial Society. Run by students and staff, it encourages valuable contact with industry professionals. In previous years the Society has organised:

  • open lectures
  • discussions
  • socials and networking events.

You may want to join Kent Maths Society, which is run by students and holds talks, workshops and social activities.

The School of Mathematics, Statistics and Actuarial Science puts on regular events that you are welcome to attend. These may include:

  • seminars and workshops
  • employability events. 

Independent rankings

Mathematics at Kent scored 91.5 out of 100 in The Complete University Guide 2019.

In the National Student Survey 2018, over 87% of final-year Mathematics and Statistics students who completed the survey, were satisfied with the overall quality of their course.

Of Mathematics and Statistics students who graduated from Kent in 2017 and completed a national survey, over 95% were in work or further study within six months (DLHE).

Teaching Excellence Framework

All University of Kent courses are regulated by the Office for Students.

Based on the evidence available, the TEF Panel judged that the University of Kent delivers consistently outstanding teaching, learning and outcomes for its students. It is of the highest quality found in the UK.

Please see the University of Kent's Statement of Findings for more information.

TEF Gold logo

Course structure

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.

Foundation year

If your qualifications are not sufficient, for whatever reason, for direct entry onto a degree programme, you can apply for this programme.

If your first language is not English, the Foundation Year offers additional classes taught by staff who are specialists in teaching English as a foreign language.

Compulsory modules currently include Credits

This module introduces fundamental methods needed for the study of mathematical subjects at degree level.

a) Functions and graphs: plotting, roots, intercepts, turning points, area (graphical methods), co-ordinate geometry of straight lines, parallel and perpendicular lines, applications to plots of experimental data, quadratics, introduction to the trigonometric functions

b) Trigonometry: radians, properties of sine and cosine functions, other trigonometric functions, compound angle formulae and subsequent results, solving trigonometric equations

c) Geometry: circles and ellipses, right-angled triangles, SOHCAHTOA, trigonometric functions, inverse trigonometric functions, sine and cosine rule, opposite and alternate angle theorems, applications to geometry problems

d) Vectors: notion of a vector, representation of vectors, addition, subtraction and scaling, magnitude, scalar product, basis vectors in 2 and 3 dimensions

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Statistical techniques are a fundamental tool in being able to measure, analyse and communicate information about sets of data. Using illustrative data sets we show how statistics can be indispensable in applied sciences and other quantitative areas. This module covers the basic methods used in probability and statistics using Excel for larger data sets. A more detailed indication of the module content follows.

Sampling from populations. Data handling and analysis using Excel. Graphical representation for the interpretation of univariate and bivariate data; outliers. Sample summary statistics: mean, variance, standard deviation, median, quartiles, inter-quartile range, correlation. Probability: combinatorics, conditional probability, Bayes' Theorem. Random variables: discrete, continuous; expectation, variance, standard deviation. Discrete and continuous distributions: Binomial, discrete uniform, Normal, uniform. Sampling distributions for the mean and proportion. Hypothesis testing: one sample, mean of Normal with known variance and proportion, 1- and 2-tail. Confidence intervals: one sample, mean of Normal with known variance and population proportion.

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Functions: Functions, inverse functions and composite functions. Domain and range.

Elementary functions including the exponential function, the logarithm and natural logarithm functions and ax for positive real numbers a. Basic introduction to limits and continuity of a function, without epsilon-delta proofs.

The derivative: The derivative as the gradient of the tangent to the graph; interpretation of the derivative as a rate of change. The formal definition of the derivative and the calculation of simple examples from first principles. Elementary properties of the derivative, including the product rule, quotient rule and the chain rule; differentiation of inverse functions; calculating derivatives of familiar functions, including trigonometric, exponential and logarithmic functions. Applications of the derivative, including optimisation, gradients, tangents and normal. Parametric and implicit differentiation of simple functions. Taylor series.

Graphs: Curve sketching including maxima, minima, stationary points, points of inflection, vertical and horizontal asymptotes and simple transformations on graphs of functions. Additional material may include parametric curves and use of Maple to plot functions.

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Vectors: Vectors in two and three dimensions. Magnitude and direction. Algebraic operations involving vectors and their geometrical interpretations including the scalar product between two vectors. Use vectors to solve simple problems in pure mathematics and applications.

Kinematics: Fundamental and derived quantities and units in the S.I. system. Position, displacement, distance travelled, velocity, speed, acceleration. Constant acceleration for motion in one and two dimensions. Motion under gravity in a vertical plane. Projectiles. Use of calculus for motion in a straight line.

Forces and Newton's Laws: Newton’s laws of motion applied to simple models of single and coupled bodies.

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This module introduces the ideas of integration and numerical methods.

a) Integration: Integration as a limit of a sum and graphical principles of integration, derivatives, anti-derivatives and the Fundamental Theorem of Calculus (without proof), definite and indefinite integrals, integration of simple functions.

b) Methods of integration: integration by parts, integration by change of variables and by substitution, integration by partial fractions.

c) Solving first order differential equations: separable and linear first order differential equations. Construction of differential equations in context, applications of differential equations and interpretation of solutions of differential equations.

d) Maple: differentiation and integration, curve sketching, polygon plots, summations.

Additional material may include root finding using iterative methods, parametric integration, surfaces and volumes of revolution.

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Students will be introduced to key mathematical skills, necessary in studying for a mathematics degree: use of the University Library and other sources to support their learning, present an argument in oral or written form, learn about staff in the School and beyond, etc. In particular, students will study various techniques of proof (by deduction, by exhaustion, by contradiction, etc.). These techniques will be illustrated through examples chosen from various areas of mathematics (and in particular co-requisite modules).

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Optional modules may include Credits

Through this module, students will develop the transferable linguistic and academic skills necessary to successfully complete other modules on their programme and acquire the specific language skills that they will require when entering SMSAS and SPS Stage 1 programmes. The programme of study focuses on writing and speaking skills, enhancing academic language through classroom, homework and assessed activities. Writing skills will be used to write a technical report, interpret data and describe processes. Spoken skills will be used in presentations and seminars.

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Through this module, students will develop the transferable linguistic and academic skills necessary to successfully complete other modules on their main programme of study. The programme of study focuses primarily on grammar, vocabulary, academic writing and speaking skills but will include all language skills. Academic lectures and seminar participation will enhance students' listening skills.

The module begins with an intensive revision of language structures and goes on to embed these structures into academic writing and speaking. Students will learn key steps in the academic writing process, enhance their writing skills and learn to adapt these skills for a variety of tasks and processes needed for study (e.g. learn to write e-mails appropriate for an academic context). Throughout the module, students will also develop their academic vocabulary through reading and writing tasks specially designed for this.

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Over the past 500 years, inventions such as telescopes, robots and fridges have revolutionised our relationships with one another and with the natural world. This module engages with some well-known inventions since the so-called 'scientific revolution' (c. 1600), alongside some unexpected and surprising ones. It examines their making and their use, and explores how they have contributed to the distinctively modern European perspective that has come to be known as ‘science’. This module approaches its topics from the perspectives of cultural and social history.

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Since Plato's Dialogues, it has been part of philosophical enquiry to consider philosophical questions using logic and common sense alone. This module aims to train students to continue in that tradition. In the first part students will be introduced to basic themes in introductory formal logic and critical thinking. In the second part students will be presented with a problem each week in the form of a short argument, question, or philosophical puzzle and will be asked to think about it without consulting the literature. The problem, and students’ responses to it, will then form the basis of a structured discussion. By the end of the module, students (a) will have acquired a basic logical vocabulary and techniques for the evaluation of arguments; (b) will have practised applying these techniques to short passages of philosophical argument; and (c) will have acquired the ability to look at new claims or problems and to apply their newly acquired argumentative and critical skills in order to generate philosophical discussions of them.

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Stage 1

Compulsory modules currently include Credits

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.

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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.

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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.

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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. The coverage is sufficient to enable students to gain exemption from the Actuarial profession's Business Economics examination (CT7 up to 2018, CB2 from 2019), whilst giving a coherent coverage of economic concepts and principles. The syllabus includes: the working of competitive markets, consumer demand and behaviour, product selection, marketing and advertising strategies, costs of production, production function, revenue and profit, profit maximisation under perfect competition and monopoly, imperfect competition, business strategy, the objectives of strategic management, firms' growth strategy, pricing strategies, government intervention, international trade, balance of payment and exchange rates, the role of money and interest rates in the economy, the level of business activity, unemployment, inflation and macroeconomic policy.

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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.

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This module introduces widely-used mathematical methods for functions of a single variable. The emphasis is on the practical use of these methods; key theorems are stated but not proved at this stage. Tutorials and Maple worksheets will be used to support taught material.

Complex numbers: Complex arithmetic, the complex conjugate, the Argand diagram, de Moivre's Theorem, modulus-argument form; elementary functions

Polynomials: Fundamental Theorem of Algebra (statement only), roots, factorization, rational functions, partial fractions

Single variable calculus: Differentiation, including product and chain rules; Fundamental Theorem of Calculus (statement only), elementary integrals, change of variables, integration by parts, differentiation of integrals with variable limits

Scalar ordinary differential equations (ODEs): definition; methods for first-order ODEs; principle of superposition for linear ODEs; particular integrals; second-order linear ODEs with constant coefficients; initial-value problems

Curve sketching: graphs of elementary functions, maxima, minima and points of inflection, asymptotes

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This module introduces widely-used mathematical methods for vectors and functions of two or more variables. The emphasis is on the practical use of these methods; key theorems are stated but not proved at this stage. Tutorials and Maple worksheets will be used to support taught material.

Vectors: Cartesian coordinates; vector algebra; scalar, vector and triple products (and geometric interpretation); straight lines and planes expressed as vector equations; parametrized curves; differentiation of vector-valued functions of a scalar variable; tangent vectors; vector fields (with everyday examples)

Partial differentiation: Functions of two variables; partial differentiation (including the chain rule and change of variables); maxima, minima and saddle points; Lagrange multipliers

Integration in two dimensions: Double integrals in Cartesian coordinates; plane polar coordinates; change of variables for double integrals; line integrals; Green's theorem (statement – justification on rectangular domains only)

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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.

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Stage 2

Compulsory modules currently include Credits

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. Stochastic processes of events such as accidents, together with the financial flow of their payouts underpin much of the work. Since the earliest games of chance, the probability of ruin has been a topic of interest. Outline Syllabus includes: Decision Theory; Bayesian Statistics; Loss Distributions; Reinsurance; Credibility Theory; Empirical Bayes Credibility theory; Risk Models; Ruin Theory; Generalised Linear Models; Run-off Triangles.

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A time series is a collection of observations made sequentially in time. Examples occur in a variety of fields, ranging from economics to engineering, and methods of analysing time series constitute an important area of statistics. This module focuses initially on various time series models, including some recent developments, and provides modern statistical tools for their analysis. The second part of the module covers extensively simulation methods. These methods are becoming increasingly important tools as simulation models can be easily designed and run on modern PCs. Various practical examples are considered to help students tackle the analysis of real data.The syllabus includes: Difference equations, Stationary Time Series: ARMA process. Nonstationary Processes: ARIMA Model Building and Testing: Estimation, Box Jenkins, Criteria for choosing between models, Diagnostic tests.Forecasting: 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: Spectral Analysis. Generation of pseudo – random numbers, simulation methods: inverse transform and acceptance-rejection, design issues and sensitivity analysis.

Marks on this module can count towards exemption from the professional examination CT6 of the Institute and Faculty of Actuaries. Please see http://www.kent.ac.uk/casri/Accreditation/index.html for further details.

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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, we study how suitable models can be constructed, how to fit them to data and how suitable conclusions can be drawn. Both theoretical and practical aspects are covered, including the use of R.

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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.

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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.

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15

This module introduces and explores a range of topics relating to corporate finance which are fundamental to understanding why and how companies raise money to start a business or expand an existing one. The module covers the different ways that the money can be raised, for example from a bank or through a stocks and shares market, and the interest rate or investment return that an investor will expect to receive from a company in order to provide the money required. This is a very practical module to the extent that it will help students develop business awareness in the field of company finance. Reference will often be made to actual happenings in the financial markets in support of the material covered.

The intention is that this curriculum together with that for MACT5280 Financial Reports and their Analysis would provide an acceptable platform for exemption from the UK actuarial profession's examination in subject CT2, subject to satisfactory performance.

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This module considers the construction and analysis of corporate accounts including the following: Regulatory backdrop to accounting, Accounting Principles, Basic construction of the main accounts, ie statements of comprehensive income, statements of financial position, cashflow statements and changes in equity statements, Directors' and auditors’ reports, Interpretation of accounts and horizontal and vertical analysis using ratios, Limitations of accounts and ratio analysis, Group accounting structures, Peculiarities of insurance company accounts.

The intention is that this curriculum together with that for MACT5270 Corporate Finance for Actuaries would provide an acceptable platform for exemption from the UK actuarial profession’s examination in subject CT2, subject to satisfactory performance.

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Optional modules may include Credits

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.

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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.

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Year in industry

Students on this course can 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 put your academic skills into practice. It also gives you an idea of your career options. Recent placements have included IBM, management consultancies, government departments, actuarial firms and banks.

Stage 3

Compulsory modules currently include Credits

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.

Marks on this module can count towards exemption from the professional examination CT4 of the Institute and Faculty of Actuaries. Please see http://www.kent.ac.uk/casri/Accreditation/index.html for further details.

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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.

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15

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 published by the Institute and Faculty of Actuaries.

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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.

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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.

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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.

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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.

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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:

  • skills and knowledge appropriate to graduates in mathematical subjects
  • the ability to use rigorous reasoning and precise expression
  • the capabilities to formulate and solve problems
  • an appreciation of recent actuarial developments, and of the links between the theory and its practical application in industry
  • the ability to formulate a logical, mathematical approach to solving problems
  • an enhanced capacity for independent thought and work
  • competence in the use of IT and the relevant software
  • opportunities to study advanced topics, engage in research and develop communication and personal skills
  • eligibility for up to eight exemptions from examinations of the Institute and Faculty of Actuaries.

In addition, the Year in Industry enables students to gain awareness of the application of technical concepts in the workplace.

Learning outcomes

Knowledge and understanding

You gain knowledge and understanding of:

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

Intellectual skills

You gain the following intellectual abilities:

  • a reasonable understanding of the programme's main body of knowledge
  • skills in calculation and manipulation of the material in the programme
  • the ability to apply a range of concepts and principles in various contexts
  • how to present a logical argument
  • solving problems using various appropriate methods
  • IT skills
  • research, presentation and report-writing skills
  • an aptitude to work independently with relatively little guidance.

Subject-specific skills

You gain actuarial science skills in the following:

  • specific mathematical and statistical techniques and their application to solving actuarial problems
  • use of industry-specific IT skills and software
  • an understanding of the practical applications of the subject material in insurance
  • the ability to develop simple actuarial computer models to solve actuarial problems and to interpret and communicate the results.

Transferable skills

You gain transferable skills in the following:

  • problem-solving in relation to qualitative and quantitative information
  • written and oral communication skills
  • numeracy and computation
  • information retrieval, in relation to primary and secondary information sources, including online computer searches
  • word-processing and other IT skills, including spreadsheets and internet communication
  • interpersonal skills such as the ability to interact with other people and to engage in team-working
  • time-management and organisation, and the ability to plan and implement efficient and effective modes of working
  • study skills required for continuing professional development.

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.

Christopher Ju Leong Low

The lecturers at Kent are mostly qualified actuaries, so they include their own practical experiences in their teaching.

Christopher Ju Leong Low Actuarial Science BSc

Entry requirements

When considering your application, we look at both your qualifications and your potential, as shown, for example, by your personal statement and the comments of your referees.

To take a foundation degree, you need to have an English language standard of 5.5 in IELTS; however please note that these requirements are subject to change.  For the latest details, see www.kent.ac.uk/ems/eng-lang-reqs

Home/EU students

The University will consider applications from students offering a wide range of qualifications. Typical requirements are listed below. Students offering alternative qualifications should contact us for further advice. 

It is not possible to offer places to all students who meet this typical offer/minimum requirement.

New GCSE grades

If you’ve taken exams under the new GCSE grading system, please see our conversion table to convert your GCSE grades.

Qualification Typical offer/minimum requirement
A level

BCC at A Level including a B in Mathematics. Non-UK qualifications at a level below A Levels should have strong results in Mathematics. All applications are considered on an individual basis.

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.

BTEC Level 3 Extended Diploma (formerly BTEC National Diploma)

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.

International Baccalaureate

34 points overall or 16 points at HL including Mathematics 6 at HL

International students

The University welcomes applications from international students. Our international recruitment team can guide you on entry requirements. See our International Student website for further information about entry requirements for your country. 

However, please note that international fee-paying students cannot undertake a part-time programme due to visa restrictions.

If you need to increase your level of qualification ready for undergraduate study, we offer a number of International Foundation Programmes.

Meet our staff in your country

For more advice about applying to Kent, you can meet our staff at a range of international events.

English Language Requirements

Please see our English language entry requirements web page.

Please note that if you are required to meet an English language condition, we offer a number of 'pre-sessional' courses in English for Academic Purposes. You attend these courses before starting your degree programme. 

General entry requirements

Please also see our general entry requirements.

Fees

The 2019/20 annual tuition fees for this programme are:

UK/EU Overseas
Full-time £9250 £15700

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

For 2019/20 entrants, the standard year in industry fee for home, EU and international students is £1,385

Fees for Year Abroad

UK, EU and international students on an approved year abroad for the full 2019/20 academic year pay £1,385 for that year. 

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

General additional costs

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

Funding

University funding

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

Government funding

You may be eligible for government finance to help pay for the costs of studying. See the Government's student finance website.

Scholarships

General scholarships

Scholarships are available for excellence in academic performance, sport and music and are awarded on merit. For further information on the range of awards available and to make an application see our scholarships website.

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 AAA over three A levels, or the equivalent qualifications (including BTEC and IB) as specified on our scholarships pages

The scholarship is also extended to those who achieve AAB at A level (or specified equivalents) where one of the subjects is either mathematics or a modern foreign language. Please review the eligibility criteria.

The Key Information Set (KIS) data is compiled by UNISTATS and draws from a variety of sources which includes the National Student Survey and the Higher Education Statistical Agency. The data for assessment and contact hours is compiled from the most populous modules (to the total of 120 credits for an academic session) for this particular degree programme. 

Depending on module selection, there may be some variation between the KIS data and an individual's experience. For further information on how the KIS data is compiled please see the UNISTATS website.

If you have any queries about a particular programme, please contact information@kent.ac.uk.