Actuarial Science

In the digital age, it is becoming ever easier, and more important, to collect data to predict and inform future decisions in science and society. Applications range from analysing communities and trends on the internet, researching patients’ responses to new drugs, examining the impact of global events on the stock market, and measuring population sizes of endangered species.

Many professions require skills in extracting useful information from data and managing and presenting data accurately. You’ll learn the core methods and principles of probability theory and statistics, and gain skills in applying these methods to analyse sample data and draw inferences or generalisations. 

You’ll learn how to estimate an unknown parameter’s value, how to construct a confidence interval, and how to do hypothesis testing. The statistical computing package R is used throughout the module to support your learning and illustrate the methods.

R, Python, Excel, and collaborative platforms like GitHub are essential tools for academic study and professional advancement. This module equips you with comprehensive skills in working with these platforms through a range of hands-on problems and practical assignments. 

As you progress through the module, you'll delve into the intricacies of R, Python, and Excel, mastering their functionalities through real-world applications. From data analysis to visualisation and interpretation, you'll gain a holistic understanding of how these tools can be harnessed to extract insights from complex datasets and analyse complex problems. 

The module has a strong emphasis on collaborative work, providing opportunities for you to engage in group projects that simulate real-world scenarios. You'll learn how to effectively collaborate with peers, manage version control, and contribute to shared repositories - an invaluable skill set in today's collaborative work environments.

Linear algebra is a core subject in mathematics. It provides the algebraic foundation for advanced mathematics and has endless practical applications in industry and science, ranging from internet technologies to theoretical physics. This module in linear algebra prepares you for advanced topics in the fields of algebra, multivariable calculus, differential equations, data analysis, and financial mathematics.

Linear algebra is the study of finding solutions to systems of linear equations using matrices, and corresponding geometric objects such as vectors, lines, planes, and linear transformations of Euclidean space. It can be used to describe symmetries of space, such as rotations, reflections, and rescaling of distances.

You’ll apply powerful techniques of matrix algebra to solve systems of linear equations, learn how to find the eigenvalues and eigenvectors of a linear transformation and learn the basic concepts and core results in linear algebra. You’ll also see how these concepts can be used to provide solutions to a variety of real-world problems.

Business Economics explores the constantly evolving economic world within which actuaries work, providing context and developing economic insights that can inform real-world business decisions.

You'll be equipped with the knowledge and tools needed to understand the workings of competitive markets, and the interaction of consumers and suppliers, using a variety of models and examples to investigate decision-making in the economy. The practical roles of money, capital and labour, and the involvement of government in influencing the big-picture of the economy, will be tied to the interests of business, with a strong foundation of economic theory underpinning real-world examples and illustrations. Theories are challenged, economic conventions are interrogated, and different viewpoints are considered to ensure a practical and relevant understanding of economic issues.

The module is designed to satisfy the standards of subject CB2 of the Institute and Faculty of Actuaries examinations for exemption purposes.

You’ll learn about the mathematics behind the design and operation of popular financial investments. This enables you to gain an understanding of the key principles of working with interest rates, and of how these can be used to price and value investments such as loans, shares, bonds and property.

You will also receive a practical introduction to financial modelling and learn how models can be used to solve financial problems. This includes using the application of the above ideas on real data sets using e.g. Microsoft Excel.

This module together with second-year module Actuarial Mathematics 1 and the final year module Actuarial Mathematics 2 can lead to exemption from the CM1 exam of the Institute and Faculty of Actuaries (IFoA).

Calculus serves as the mathematical foundation for many fields, including physics, engineering, economics, computer science, and statistics. It also plays a crucial role in understanding and solving problems in biology, chemistry, and medicine.

This module delves deep into the fundamental concepts of differentiation and integration. You’ll explore the properties of core functions including polynomials, exponentials and logarithms, trigonometric functions and their inverses, as well as hyperbolic functions. You’ll become proficient in the fundamental techniques of differentiation and integration of single-variable functions.

You’ll explore the practical applications of differentiation and integration, such as optimisation problems, curve sketching and solving simple differential equations. You’ll also demonstrate how calculus can be used to solve real-world problems. Throughout the module, you’ll develop critical thinking skills, mathematical reasoning, and the ability to apply calculus techniques to solve various problems.

Explanatory and predictive modelling is essential to data-driven decision-making. Throughout this module, you’ll learn about regression, the cornerstone of versatile statistical analysis and master diagnostics, model specification, selection, and interpretation.

Through hands-on activities and real data analysis, you’ll gain the skills to extract actionable insights and forecast future trends confidently. The module is designed to equip you with the required tools to navigate complex datasets across different areas of application and practice.

Optimisation techniques play an important role in practically all areas of data science, including data analysis and machine learning. An understanding of the core principles of optimisation algorithms and their properties is essential for all practitioners in this field.

You'll gain expertise in the theory and applications of optimisation techniques and algorithms, focusing on the methods most relevant to data science. You'll master how to optimise solutions, analyse and improve the performance of algorithms, and acquire decision-making techniques. The module will equip you with an understanding of the way many standard problems in data science can be formulated as optimisation problems. In addition, you’ll gain skills in applying basic optimisation algorithms and techniques, including Newton's and gradient based methods, to solve problems. Throughout the module computing tools will be used to illustrate how optimisation techniques and algorithms are used to compute solutions to relevant problems in data science.

Mathematical statistics provides the theoretical framework for statistical techniques. Understanding these mathematical underpinnings allows statisticians to develop and justify various statistical methods, ensuring their validity and reliability. Mathematical statistics enables practitioners to extract valuable insights from data, make informed decisions, and drive progress in various fields of knowledge and application.

You’ll learn advanced techniques in probability and statistics, including maximum likelihood estimation, advanced hypothesis testing, moments and moment-generating functions. You’ll also discover bivariate and multivariate discrete and continuous distributions.

By the end of the module, you’ll have a solid foundation in mathematical statistics, enabling you to confidently apply and further develop advanced skills in data analysis.

Mathematics is central to investing. In this module, you’ll learn about the mathematics behind the design and operation of popular financial investments. You’ll learn the key principles of working with interest rates, and discover how these can be used to price and value investments such as loans, shares, bonds and property.

You will also receive a practical introduction to financial modelling and learn how models can be used to solve financial problems. This includes the ideas you learn to real data sets using Microsoft Excel and other software packages. You will also further develop your skills in financial modelling and learn how models can be used to solve actuarial problems. This includes applying the concepts and techniques of actuarial mathematics on real data sets using e.g. Microsoft Excel.

This module follows on from Financial Mathematics and together with that module and the final year module Actuarial Mathematics 2 can lead to exemption from the CM1 exam of the Institute and Faculty of Actuaries (IFoA).

How can we use mathematics to design common life insurance products? How can we calculate the financial impact of uncertain future events? In this module, you’ll learn about the key principles of working with mortality rates and interest rates. This will allow you to value cash flows which are contingent on mortality and/or survival, enabling you to price and value products such as whole-life, temporary and endowment assurances and whole-life and temporary annuities.

You’ll also further develop your skills in financial modelling and learn how models can be used to solve actuarial problems. You’ll apply the concepts and techniques of actuarial mathematics to real data sets using software such as Microsoft Excel.

This module follows on from Financial Mathematics and together with that module and the final year module Actuarial Mathematics 2, it can lead to exemption from the CM1 exam of the Institute and Faculty of Actuaries (IFoA).

From start-ups to established multinationals, businesses need finance at various stages, whether it’s to fund growth, or just to survive. In this module, you’ll explore and apply the principles of corporate finance. You’ll consider a wide variety of sources of finance, from traditional to more contemporary means, and examine the process of selecting an appropriate approach depending on the circumstances.

You’ll also consider the methods businesses use to manage financial risk, and look at how firms evaluate which projects to undertake. Additionally, you’ll cover important topics such as corporate governance, alternative business forms, and the impact of taxation.

Corporate accounts and financial statements communicate the financial position of a business to various users. You’ll examine the process of constructing these reports, develop an understanding of the concepts and techniques of financial accounting, and find yourself in a better position to critically interpret and discuss the financial reports of real companies and financial institutions.

Through this module, you’ll gain insights into the needs and concerns of businesses in the commercial world, including those relevant to potential employers and clients. This module can lead to exemption from the CB1 exam of the Institute and Faculty of Actuaries (IFoA).

A strong grasp of statistical modelling and optimisation principles forms the bedrock of machine learning. This module covers essential and advanced topics of machine learning and deep learning, blending theory with practical computing tools, such as R and Python.

We’ll equip you with the necessary theoretical framework to navigate through complex algorithms and methodologies. You’ll explore key concepts including classification, prediction, and regression tree-based methods through engaging real-world datasets. 

You’ll uncover the power of resampling techniques and support vector machines, and dive into the exciting realm of deep learning. With applications spanning biomedical statistics, finance, and insurance, this module offers a hands-on learning experience tailored to aspiring data scientists.

What are the commonly used models in actuarial science? How can we apply these models to tackle the complex problems faced by financial professionals in practical situations? Modelling is crucial for actuaries as it allows us to assess and manage risks in various circumstances. This module gives you the valuable practical and theoretical skills needed to navigate these critically relevant issues.

You’ll gain a strong foundation in financial economics modelling techniques and be able to apply them in quantitative risk management situations, including portfolio selection and the pricing and valuation of financial derivatives.

You’ll develop valuable skills to model economic decision making by forecasting potential future scenarios, and apply a range of financial risk measurement tools to evaluate suitable investment opportunities. In addition, you’ll explore a range of liability valuation modelling tools which can be used to estimate insurance claims. The modelling techniques that you learn in this module will provide you with the indispensable knowledge and skills needed for a successful career in insurance, finance and related fields.

You will also have the opportunity to gain valuable exemptions from subject CM2 of the Institute and Faculty of Actuaries (IFoA, UK).

How is mathematics used to design common life insurance products, including those with profits and unit-linked products? In this module, you’ll learn how to price and value complex cash flows on various insurance products. You’ll look at cases where the benefits can vary and where the cash flows are contingent on the mortality, morbidity and/or survival of more than one life. You’ll also learn how to calculate and analyse the profitability of these products.

You’ll have the opportunity to gain valuable, practical experience working with one of the industry’s leading actuarial modelling software applications, PROPHET. This is used by insurance and financial services companies to meet reporting responsibilities, improve risk management and develop profitable products. You will also further develop your skills in financial modelling and learn how models can be used to solve actuarial problems. You’ll do this by applying the concepts and techniques of actuarial mathematics to real data sets using PROPHET and/or Microsoft Excel.

This module follows on from Financial Mathematics and Actuarial Mathematics 1 and together with these modules can lead to exemption from the CM1 exam of the Institute and Faculty of Actuaries (IFoA).

Mathematical and statistical modelling techniques are vital tools for those working in the insurance industry. This module introduces you to these techniques and illustrates their importance to survival analysis and insurance. You’ll also learn how they are used by actuaries employed by pension schemes and insurance companies.

There are many applications of these techniques including fitting statistical distributions to mortality data and insurance claims data so that the solvency of insurance companies can be assessed and managed. They can also be used to determine the effect of factors such as age, lifestyle and geographical location on longevity and claims levels. Modelling techniques can also be used to advise governments on healthcare, state pension provision and regulation of entire industries.

Throughout the module, you’ll study both theory and its application using programming languages such as R and software such as Microsoft Excel to solve real-life problems that actuaries in the pension and insurance sectors may encounter.

This module will cover a number of syllabus items set out in subjects CS1 and CS2 published by the Institute and Faculty of Actuaries.

You’re now at the final stages of your undergraduate journey into actuarial practice. This module brings together your theoretical knowledge, skills and insights where you will apply it to the context of the professional and commercial world. You’ll survey the wider landscape of financial services and investigate some of the common roles, issues and complexities you’re likely to encounter working as an actuary.

You’ll refine the core skills required to work in this sector and explore the various risks the industry faces, together with effective strategies for managing these risks. Through insightful discussions on topical industry-shaping issues and collaborative projects, you’ll develop your ability to analyse and address emerging challenges, enhance your teamwork and communications skills.

A core focus of this module is enhancing your employability and preparing you for a career in the commercial and professional world. You’ll have the opportunity to reflect on your learning, assess how your strengths and competencies align with various industry requirements, and build a foundation for your future in the industry.

Stochastic models and time series techniques are vital tools for actuaries. This module demonstrates how these concepts are applied by actuaries working for insurance companies and investment firms. You’ll learn how to use time-series skills to analyse security prices and other economic factors such as interest rates, inflation and foreign exchange rates. You’ll also learn how stochastic theory is fundamental in designing actuarial models in fields such as population projection.

You’ll use industry-standard software such as R to solve real-life problems encountered in various actuarial sectors. You’ll also engage with topical actuarial issues by reading and discussing industry-specific articles. This will give you a competitive edge when it’s time to launch your career.

This module also covers several syllabus items in Subjects CS1 and CS2 published by the Institute and Faculty of Actuaries.