Actuarial Science MSc

• Introduction to R Programming

  This module is designed to provide a fundamental understanding of R programming and no previous programming experience is expected. The teaching model is learning by doing and basic concepts are built up in an incremental manner. The teaching material is formulated via multiple R code examples that enable the students to work independently when dealing with small R programming tasks.

• Introduction to Python Programming

  This module is designed to provide a fundamental understanding of Python programming and no previous programming experience is expected. The teaching model is learning by doing and basic concepts are built up in an incremental manner. The teaching material is formulated via multiple Python code examples that enable the students to work independently when dealing with small Python programming tasks.

Both programming modules are designed to provide a fundamental understanding of R and Python. They are highly recommended for all the students on the programme. You are encouraged to undertake these modules so that you can get the most out of your degree.  Completing these two modules will also help you with the computer-based elements of the CM and CS subjects.

Compulsory Modules

• Financial Mathematics (CM1(1))

  You will learn how to apply compound interest theory to find the present value or the accumulation of a cash flow, and to apply financial mathematics to solve a wide range of practical problems also via computer-based applications. You will analyse and compare alternative capital projects and perform investment valuation.

  Along with Contingencies (CM1(2)), this module will cover Subject CM1 of the UK Institute and Faculty of Actuaries’ professional examinations.

Elective Modules

• Probability and Mathematical Statistics (CS1)

  This module will enable you to master the axioms of probability and conditional probability, the concept of a random variable and a probability distribution, and to define and use generating functions. You will apply and debate the principles of statistical inference, explain and evaluate the theory underlying statistical techniques.

  You will construct statistical displays of data, solve problems with more than one random variable, find moments of distributions, carry out and interpret linear regression and generalised linear regression models. You will test hypotheses and derive confidence intervals. You will explain the fundamental concepts of Bayesian statistics.

  Finally, you will become proficient in a broad range of related computer-based applications in R. The module will cover Subject CS1 of the UK Institute and Faculty of Actuaries’ professional examinations.

• Finance and Financial Reporting (CB1)

  The module is designed to provide you with the skills and knowledge to engage professionally with finance and financial reporting within a company. The finance section of the module will provide you with a basic understanding of the methods and types of instruments used by companies to raise finance. The financial reporting section will enable you to interpret the published financial statements of companies and financial institutions. The module will cover Subject CB1 of the UK Institute and Faculty of Actuaries’ professional examinations.

• Business Economics (CB2)

  This module will introduce you to fundamental concepts of economic analysis at both micro and macro levels, focusing on those areas most relevant to actuarial science. In doing so, it will cover Subject CB2 of the UK Institute and Faculty of Actuaries’ professional examinations.

• Analytics Methods for Business (non-exemption module)

  This module provides a collection of standard analytical methods and explains how data analysis is performed in the real world. It represents an introduction to specific tasks that a business analyst encounters on a daily basis, which ultimately help in analysing, communicating and validating recommendations to change the business and policies of an organisation. Furthermore, the module provides the foundation for using R to translate theory into practice.

Students with a prior exemption from CM1 may also be exempted from Bayes CM1(1) and CM1(2), subject to the provision of evidence of the prior exemption. However, they will be required to replace these with other term 1 and 2 modules.

Compulsory Modules

• Contingencies (CM1(2))

  You will gain an understanding of a broad range of life insurance products and their pricing, and a mastery of life insurance mathematics. You will be able to calculate gross premiums and reserves for fixed and variable benefit contracts. You will be introduced to annuities and assurances involving two lives, and multiple decrement models. Finally, you will be able to apply mathematics and statistics to related practical problems via computer-based applications.

  Along with Financial Mathematics (CM1(1)), this module will cover Subject CM1 of the UK Institute and Faculty of Actuaries’ professional examinations.

Elective Modules

• Financial Economics (CM2)

  You will develop a proficiency in the application of models used in financial economics and understand how they are used, also via computer-based applications. You will analyse insurance problems in terms of utility theory, define measures of investment risk, and describe how insurance companies help reduce or remove risk. You will be able to explain the assumptions and ideas underlying different financial models, and apply finance theory to assess risk, make portfolio decisions, model asset prices and interest rates, and evaluate derivatives. The module covers Subject CM2 of the UK Institute and Faculty of Actuaries’ professional examinations.

• Insurance Risk Modelling (CS2)

  This module aims to explain the fundamental risk modelling for insurance applications. Specifically, statistical and stochastic modelling for life and non-life insurance risks are discussed in order to cover Subject CS2 of the UK Institute and Faculty of Actuaries’ professional examinations. Various topics will be accompanied by computer-based applications.

• Machine Learning (non-exemption module)

  This module provides an overview of machine learning concepts, techniques and algorithms used in practice to describe and analyse complex data and design predictive analytics methods. You should expect to engage with the main idea and intuition behind modern machine learning tools from a practical perspective. Standard computing skills in R, Python and Matlab will be used to put in practice the theory discussed in the lectures.

Students with a prior exemption from CM1 may also be exempted from Bayes CM1(1) and CM1(2), subject to the provision of evidence of the prior exemption. However, they will be required to replace these with other term 1 and 2 modules.

To complete the MSc in Actuarial Science, you have several options in your third term:

• Five electives plus Career Management Skills and Research Methods module
• Three electives plus a General Research project
• Modelling Practice (CP2), Professional Communication (CP3), two short electives plus the Career Management Skills and Research Methods module
• Modelling Practice (CP2), Professional Communication (CP3) and a General Research Project.

Subject to availability, you can also choose projects designed by our industry partners, including, for example, the Bank of England, Government Actuary’s Department and Guy Carpenter. Most of these projects are directly supervised by the industry partner representatives together with our academic staff.

Over the years, several students taking research projects with us have been recipients of the prestigious SCOR award.

• General Research Project

  This module will help you integrate your learning across a range of skills and in particular to enable you to demonstrate the results of your learning through the development of a final project. You may choose to complete more traditional academic desk research, complete a business plan or carry out a consultancy project and any reasonable proposal is acceptable providing that it is agreed with the project supervisor and the course director

• Career Management Skills and Research Methods

  Supporting your wider learning and career success through the development of key transferrable skills and attributes that you will use both in your programme and across your career. In particular: research and analysis, career planning and employability skills development, and sustainable working.

  Develop a grounding in research methods, targeted to your particular degree requirements. You will be able to use these skills to support your learning, substantiate your arguments and make assessments about the nature of the evidence you are using.

  Career and employability skills development, delivered in a highly targeted and applied format throughout the year, will help you develop your aspirations, take a planned and efficient approach to your job search and / or entrepreneurial plans, and help you create a strong base from which to manage your career in the longer term. The content of this module will also help you understand how to apply your learning in the wider context of your career.

• Modelling Practice (CP2)

  This module will provide you with an understanding of how to model data and processes using spreadsheets, how to document your work, analyse the methods used and outputs generated, and communicate the approach, results and conclusions to your junior and senior colleagues.

  It covers Subject CP2 of the UK Institute and Faculty of Actuaries’ professional examinations.

• Professional Communication (CP3)

  You will be introduced to the skill of communicating with non-actuaries on topics related to actuarial practice. You will revise its main areas and study how technical actuarial concepts and other specialist information can be explained to clients in plain, jargon-free English. You will learn how to draft letters to those seeking professional advice in a manner suited to the level of knowledge of the recipient.

  The module covers Subject CP3 of the UK Institute and Faculty of Actuaries’ professional examinations.

Short electives offered in 2023

The short electives will give you a breadth of subject matter in actuarial science, insurance, business analytics, areas of finance and investment.

• Applied Machine Learning
• Applied Natural Language Processing
• Data Management Systems
• Advanced Predictive Analytics
• Emerging Global Risks
• Financial Risk: The Future of  Finance  (jointly with USS)
• Topics in Quantitative Risk Management
• Ethics, Society and the Finance Sector
• Financial Crime
• Valuation of Financial Institutions.

International electives

• FinTech (taught in Italy)
• International Real Estate Markets (Dubai).

More about elective modules at Bayes

Please note that electives are subject to change and availability.