Actuarial Science with Business Analytics MSc
Key information
Duration: 12 months
Attendance mode: Full-time
Fees: From £15,000 (more information)
Location: Bunhill Row
Start of programme: September 2024
Application deadline: Rolling applications
Entry year: Showing course information for 2024
Develop sought-after business analytical skills of modern actuaries
Overview
Actuarial Science with Business Analytics MSc Who is it for?
This pathway is for you if you like to think about innovative tools – there is a rising need for these people in actuarial practice, and demand is far higher than supply. Our dedicated MSc in Actuarial Science with Business Analytics, established in 2020, aims to fill this gap.
Choose this MSc if you are interested in understanding the fundamentals of traditional areas of actuarial practice, and in taking advantage of unique opportunities to grow in the new areas of business analytics methods, machine learning, data management systems and natural language processing. You will already hold the equivalent of a UK upper second class degree in a highly quantitative programme, such as mathematics or statistics.
You will be taught and receive advice on study and exam techniques by qualified actuaries, academics and other subject-specialists with commercial experience and research expertise.
Why choose this course?
An enduring and constantly evolving degree embracing traditional and cutting-edge actuarial fields
Ranked 1st in Europe for actuarial research. Top 50 UNL Global Research Rankings of Actuarial Science and Risk Management & Insurance.
Course objectives
This postgraduate programme, with a choice of study options, will ensure that you learn the right tools and cultivate the new skillset for actuaries and become competent and ready to harness these in an ever-changing global business environment.
Like our MSc in Actuarial Science, this pathway will offer you the choice of the Core Principles of the Institute and Faculty of Actuaries’ curriculum, enabling you to gain exemptions from Subjects CM1, CM2, CS1, CS2, CB1, CB2. Also recognising the importance of modelling and communication practices in a business environment, you will be given the opportunity to gain exemptions from Subjects CP2 and CP3.
Add further value to your course by studying four compulsory Business Analytics modules. You will learn how data analysis is performed in the real world and study machine learning techniques and their use in analysing complex data and designing predictive analytics methods.
If you succeed on the MSc in Actuarial Science with Business Analytics or MSc Actuarial Science you can also proceed to the MSc in Actuarial Management.
Teaching staff
The teaching staff on the MSc in Actuarial Science with Business Analytics have many years of practical experience working in the insurance, pensions and financial services sectors and are also active researchers in their fields. This knowledge and experience inform the highly interactive lectures that make up the MSc in Actuarial Science with Business Analytics.
Module leaders include:
- Professor Vali Asimit
- Dr Zoltan Butt
- Dr Michail Chronopoulos
- Dr Russell Gerrard
- Mr David Hargreaves
- Dr Zaki Khorasanee
- Dr Pietro Millossovich
- Professor Jens Perch Nielsen
- Dr Iqbal Owadally
- Professor Keith Pilbeam
- Professor Rosalba Radice
- Professor Ben Rickayzen
- Dr Simone Santoni
- Mr Nick Silver
- Dr Douglas Wright
- Dr Rui Zhu.
Accreditation details
Bayes Business School is recognised as a Center of Actuarial Excellence (CAE) from the Society of Actuaries (SOA), one of the main actuarial professional bodies in the US. Together with our accreditation by the Institute and Faculty of Actuaries in the UK, this reinforces our establishment as a global hub for actuarial studies and intellectual capital development. Our courses are also recognised as preparing students for certain SOA actuarial exams.
Course content
On the MSc Actuarial Science with Business Analytics you will:
- Summarise and critically assess fundamental concepts in actuarial science, insurance, economics, finance, investment, financial reporting and business
- Make use of analytical skills to evaluate and solve complex problems within the organisation’s strategic perspective
- Demonstrate critical awareness of current analytical methods in order to transform information into knowledge
- Increase your understanding and knowledge of how current analytical methods could be applied in practice
- Analyse the breadth of machine learning techniques and their applications
- Frame analytics problems from a machine learning perspective and suggest practical solutions to them
- Carry out modelling and effectively communicate the results to a defined audience.
Note: the key difference from the MSc in Actuarial Science is that the modules Analytics Methods for Business (term 1), Machine Learning (term 2) and at least two from Applied Machine Learning, Applied Natural Language Processing, and Data Management Systems in term 3 become compulsory in this programme.
You are also expected to pass the (non-credit-bearing) modules Introduction to R Programming and Introduction to Python Programming before transferring to MSc Actuarial Science with Business Analytics.
Course structure
Programme content is subject to change. We regularly review our module offering and amend to keep up to date and relevant.
Induction weeks
All our MSc courses start with two compulsory induction weeks which include relevant refresher courses, pre-study programming modules, an introduction to the careers services and the annual careers fair.
Pre-Study Modules
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 and are compulsory for those students opting for this degree pathway. Completing these two modules will also help you with the computer-based elements of the CM and CS subjects.
Term 1
Compulsory Core Modules
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 that 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.
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.
Research Methods for Actuarial Professionals (non-exemption module)
Strong research is a key element of development strategy for companies and institutions, large and small. This module aims to provide a ground in statistical learning research, particularly supervised and unsupervised learning, which you will be able to apply to real data. The content is tailored to support you and to develop your research and statistical learning skills. The module will utilise specific training in statistical learning techniques in order to provide a strong foundation for in-depth and specialist teaching and learning in terms 2 and 3. You will also develop an intuition behind the methods which you will be able to use to support your learning, substantiate your arguments and make assessments about the nature of the evidence you are using.
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.
Term 2
Compulsory Core Modules
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.
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.
Term 3
To complete the MSc in Actuarial Science with Business Analytics, you have several options in your third term:
- Modelling Practice (CP2), Professional Communication (CP3) and two short electives from Applied Machine Learning, Applied Natural Language Processing, and Data Management Systems
- Applied Research Project and three short electives with at least two from Applied Machine Learning, Applied Natural Language Processing, and Data Management Systems
- Five short electives with at least two from Applied Machine Learning, Applied Natural Language Processing, and Data Management Systems.
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.
Applied Research Project (ARP)
The ARP will be of approximately 3,000-5,000 words. In this case, the topic is supplied by Bayes faculty and initial guidance is offered, but no formal supervision, is offered to help you identify the research question.
Subject to availability, you can also choose projects designed by our industry partners that aim to develop students’ consulting skills, including various analytics consulting companies, companies from the finance and insurance sectors, well-known retailers, etc., and some examples are: Bank of England, Ekimetrics, Fiat Chrysler Automobiles, Government Actuary’s Department, Velador Associates and Vodafone UK. Most of these projects are directly supervised by the industry partner representatives together with our academic staff.
Short electives offered in 2023
The short electives aim to offer a breadth of subject matter in actuarial science, insurance, business analytics, finance and investment.
- Applied Machine Learning
- Applied Natural Language Processing
- Data Management Systems
- Emerging Global Risks
- Topics in Quantitative Risk Management
- Stochastic Claims Reserving in General Insurance
- Modelling and Data Analysis
- 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.
Download course specification:
Actuarial Science with Business Analytics MSc [PDF]Assessment methods
Term dates
Term dates 2024/25
- Induction: 9th September 2024 - 20th September 2024
- Term one: 23rd September 2024 - 6th December 2024
- Term one exams: 6th January 2025 - 17th January 2025
- Term two: 20th January 2025 - 4th April 2025
- Term two exams: 21st April 2025 - 2nd May 2025
- Term three - international electives: 5th May 2025 - 16th May 2025
- Term three: 19th May 2025 - 4th July 2025
- Term three exams: 7th July 2025 - 18th July 2025
- Resits: 11th August 2025 - 22nd August 2025
- Additional resit week - tests only: 25th August 2025 - 29th August 2025.
Timetables
Course timetables are normally available from July and can be accessed from our timetabling pages. These pages also provide timetables for the current academic year, though this information should be viewed as indicative and details may vary from year to year.
Please note that all academic timetables are subject to change.
Fees & funding
UK/Home fee
September 2024 entry
£15,000
MSc Full-time
Tuition fees are subject to annual change.
International fee
September 2024 entry
£24,700
MSc Full-time
Tuition fees are subject to annual change.
Deposit: £2,000 (usually paid within 1 month of receiving offer and non-refundable unless conditions of offer are not met).
First installment: Half fees less deposit (payable during on-line registration which should be completed at least 5 days before the start of the induction period).
Second installment: Half fees (paid in January following start of course).
Tuition fee increases
Where applicable, tuition fees for Bayes' programmes will be subject to inflationary increases in each year of study. Our policy for these increases is set out in our terms and conditions of study.
Scholarships & bursaries
Scholarships, sponsorships, loans and other funding could support your education at Bayes Business School.
Learn about the cost of living as a Bayes student in London.
Scholarships
We have a range of scholarships for Master's degrees at Bayes Business Scool. Most scholarship applications for 2024/25 year of entry will open in January 2024.
View our scholarships and fundingOther funding opportunities
Scholarships are very competitive, you may wish to look other options for funding, including the government PG Loan.
View other funding optionsSponsorship
Students on the course who are sponsored in full or in part by their employer will need to complete a sponsorship form as part of the application process.
View our sponsorship guidanceCareers
Your Master’s in Actuarial Science with Business Analytics prepares you to tackle roles in actuarial and risk analysis, consultancy and underwriting in leading banking, insurance and financial services firms. As more technology and analytics are introduced across the actuarial industry, your skills become invaluable to the increasing number of companies seeking actuarial students who have knowledge of business analytics.
Our expert Careers Team will give you advice on your finding your ideal career path and how to achieve your professional goals.
Continuing study
The MSc in Actuarial Management serves as a continuation of the MSc in Actuarial Science with Business Analytics, allowing successful candidates to focus on the application of concepts learned, study the key areas of actuarial practice, choose from the various actuarial specialist subjects and attain further technical knowledge.
Students taking that MSc get an opportunity to obtain further exemptions from the later professional subjects of the Institute and Faculty of Actuaries, enabling them to reach the highest possible level of the professional qualification.
Class of 2022 Profile
Job titles include:
- Actuarial Analyst
- Trainee Actuary
- Model Management and Development Analyst
- Junior Specialist
- Auditor.
Download our latest MSc Employment Report
Recent employers
Alumni stories
Entry requirements
- A UK upper second class degree or above, or the equivalent from an overseas institution, in a highly quantitative programme such as mathematics or statistics is required to enter this course
- Work experience is not a requirement of this course.
English language requirements
If you have been studying in the UK for the last three years it is unlikely that you will have to take an English language test.
If you have studied in the UK at degree level for less than three years (e.g. 3+1, 2+1, 2+2, etc.) you will be required to provide the results of an approved English language test and possibly resit the test to meet our academic entry requirements.
Full list of approved English language tests/qualifications and minimum requirements.
Apply
Please see our Application Guide for details of the documents you will need to supply as part of your application, and other useful information.
We cannot comment on individual eligibility before you apply. We can only make a decision on your application once it is fully complete, with all requested information received.
Frequently asked questionsApply for September 2024 entry
Individuals wishing to apply for either the MSc Actuarial Science or the MSc Actuarial Science with Business Analytics should apply for the MSc Actuarial Science in the first instance.
Applicants who are interested in the MSc Actuarial Science with Business Analytics will be able to opt for it during Term 1. You will need to provide a supporting personal statement and successfully pass the pre-entry modules Introduction to R Programming and Introduction to Python Programming.
Terms and conditions
Students applying to study at Bayes Business School are subject to City, University of London's terms and conditions.
Student life
We are located right in the heart of London. Being a student at City allows you to take advantage of all that London has to offer.
London is continually ranked as one of the 'Best Student Cities' in the world to study within (QS, 2019).
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