| Program start date | Application deadline |
| 2024-09-01 | - |
| 2024-09-09 | - |
Program Overview
The MSc in Actuarial Science at Bayes Business School provides a comprehensive understanding of actuarial science, preparing students for careers in insurance, finance, and business analytics. The program offers flexible study options, exemptions from professional exams, and a strong industry focus, ensuring graduates are equipped with the knowledge and skills to succeed in the actuarial profession.
Program Outline
Degree Overview:
This program is designed for individuals with strong technical ability, an interest in solving business problems, and an appreciation for the risks that changes in the world bring about. It is ideal for those who want to take the first step toward a rewarding career as an actuary.
Objectives
The MSc in Actuarial Science aims to:
- Provide a firm grounding in the fundamentals of actuarial science.
- Equip students with the knowledge and skills to study in detail the mathematical and statistical techniques for measuring the probability and risk of future events.
- Help students understand the financial impact of these events on a business and/or its clients.
- Enable students to gain exemptions from the Institute and Faculty of Actuaries’ Core Mathematics, Core Statistics, and Core Business professional examinations (Subjects CM1, CM2, CS1, CS2, CB1, and CB2).
- Teach students advanced financial and business principles, and analytical methods.
Description
The MSc in Actuarial Science offers a comprehensive and rigorous understanding of actuarial science in a variety of fields, including insurance, finance, investment, and business analytics. Students will gain a deep understanding of the mathematical and statistical techniques used to measure and manage risk, as well as the financial and business implications of those risks. The program is designed to be flexible, offering students several study options to choose from. It also boasts a strong record of preparing students for the actuarial profession, with many graduates achieving top results in professional exams and securing prestigious careers in the field.
Outline:
Course Structure
The course is divided into three terms, each with a specific focus and set of modules.
Term 1:
- Compulsory Core Modules:
- Financial Mathematics (CM1(1))
- Contingencies (CM1(2))
- Research Methods for Actuarial Professionals (non-exemption module)
- Elective Modules:
- Probability and Mathematical Statistics (CS1)
- Finance and Financial Reporting (CB1)
- Business Economics (CB2)
- Analytics Methods for Business (non-exemption module)
Term 2:
- Compulsory Core Modules:
- Probability and Mathematical Statistics (CS1)
- Finance and Financial Reporting (CB1)
- Business Economics (CB2)
- Elective Modules:
- Financial Economics (CM2)
- Insurance Risk Modelling (CS2)
- Machine Learning (non-exemption module)
Term 3:
Students can choose one of the following options:
- Option 1:
- Modelling Practice (CP2)
- Professional Communication (CP3)
- Two short electives
- Option 2:
- Modelling Practice (CP2)
- Professional Communication (CP3)
- Applied Research Project
- Option 3:
- Applied Research Project
- Three short electives
- Option 4:
- Five short electives
Short Electives offered in 2023:
- Applied Machine Learning
- Applied Natural Language Processing
- Data Management Systems
- Modelling and Data Analysis
- Emerging Global Risks
- Stochastic Claims Reserving in General Insurance
- Topics in Quantitative Risk Management
- Ethics, Society and the Finance Sector
- Financial Crime
- Valuation of Financial Institutions
Individual Modules
Financial Mathematics (CM1(1)):
This module covers the theory and applications of compound interest, financial mathematics, and investment valuation. Students will learn how to calculate the present value and future value of cash flows, analyze and compare capital projects, and perform investment valuation.
Contingencies (CM1(2)):
This module provides a comprehensive introduction to life insurance mathematics, covering various life insurance products, their pricing, and相关的 calculations. Students will gain a deep understanding of life insurance principles and their applications.
Probability and Mathematical Statistics (CS1):
This module covers the fundamental concepts of probability theory, mathematical statistics, and statistical inference. Students will learn about random variables, probability distributions, hypothesis testing, confidence intervals, and linear regression.
Finance and Financial Reporting (CB1):
This module provides an overview of finance and financial reporting principles, covering corporate finance, investment analysis, and financial statement analysis. Students will learn how companies raise capital, analyze financial instruments, and interpret financial statements.
Business Economics (CB2):
This module introduces students to microeconomics and macroeconomics, focusing on areas relevant to actuarial science. It covers topics such as supply and demand, market equilibrium, economic growth, and monetary policy.
Financial Economics (CM2):
This module delves into financial economics, covering various models and theories used to analyze financial markets, risk, and investment decisions. Students will learn about portfolio theory, asset pricing models, and risk management techniques.
Insurance Risk Modelling (CS2):
This module focuses on modeling insurance risks, covering statistical and stochastic modeling techniques applied to life and non-life insurance. Students will learn how to model various insurance risks and apply these models to practical scenarios.
Machine Learning (non-exemption module):
This module introduces students to machine learning concepts, techniques, and algorithms used in data analysis and predictive modeling. Students will learn how to apply machine learning techniques to analyze data, identify patterns, and make predictions.
Modelling Practice (CP2):
This module teaches students how to model data and processes using spreadsheets, analyze the methods used, and communicate the results to others. Students will gain hands-on experience in building and analyzing models for real-world problems.
Professional Communication (CP3):
This module focuses on communicating actuarial concepts and technical information effectively to non-actuarial audiences. Students will learn how to explain complex topics in plain language and tailor their communication style to different audiences.
Applied Research Project:
This project allows students to delve deeper into a specific topic in actuarial science or finance related to their career interests. They will conduct independent research, analyze data, and present their findings in a written report.
Short Electives:
Students can choose from a variety of short electives covering various topics in actuarial science, finance, business analytics, and related fields. These electives provide students with the opportunity to explore areas of interest and gain additional specialized knowledge.
International Electives:
Students also have the option to take international electives in FinTech and International Real Estate Markets, taught in Italy and Dubai, respectively. These electives offer students a global perspective on finance and real estate, expanding their knowledge and cultural understanding.
Term Dates:
- Induction: September 9th - 20th, 2024
- Term 1: September 23rd - December 6th, 2024
- Term 2: January 20th - April 4th, 2025
- Term 3: May 19th - July 4th, 2025
- International Electives: May 5th - 16th, 2025
Timetables:
Timetables for the MSc Actuarial Science program are typically available from July and can be accessed on the City, University of London website.
Note:
This information is for the 2024 entry year. Course content and structure may be subject to change in future years.
Assessment:
Assessment methods in the MSc in Actuarial Science include:
- Coursework (e.g., assignments, projects, presentations)
- Examinations (written and/or computer-based)
- Group projects
- Individual presentations
- Computer-based components (e.g., modeling exercises) The specific assessment methods used for each module will be outlined in the module handbook.
Teaching:
The MSc in Actuarial Science is taught by a team of highly qualified and experienced academics and professionals from the insurance, finance, and actuarial industries. The teaching approach is interactive and engaging, incorporating lectures, seminars, workshops, group discussions, and practical exercises.
Teaching Staff:
The teaching staff includes qualified actuaries, academics, and subject-specialists with extensive industry experience and research expertise. The program director is Professor Ioannis Kyriakou, Professor of Actuarial Finance. Other notable faculty members 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
Unique Approaches:
The MSc in Actuarial Science offers several unique approaches to teaching and learning:
- Strong Industry Focus: The program maintains close ties with the industry, ensuring that the curriculum and teaching methods are aligned with current industry practices and needs.
- Emphasis on Practical Skills: Students are provided with ample opportunities to apply their knowledge and skills to real-world problems through case studies, simulations, and projects.
- International Faculty: The teaching staff is comprised of academics and industry professionals from various countries, bringing a global perspective to the program.
- Flexible Learning Options: The program offers various study options, including full-time, part-time, and online modes, allowing students to choose the learning path that best suits their needs and circumstances.
Careers:
The MSc in Actuarial Science prepares graduates for a wide range of careers in the actuarial profession and related fields. Potential career paths include:
- Actuary
- Actuarial Analyst
- Trainee Actuary
- Model Management and Development Analyst
- Junior Specialist
- Auditor
- Financial Analyst
- Risk Analyst
- Consultant
- Underwriter Graduates can find employment in various industries, including:
- Insurance
- Banking
- Finance
- Investment
- Professional Services
- Government
Recent Employers:
Graduates of the MSc in Actuarial Science have been employed by leading companies, including:
- Aon
- Aviva
- EY
- KPMG
- Lloyds Banking Group
- PwC
- Swiss Re
Graduate Outcomes Survey 2020-21:
According to the Graduate Outcomes Survey 2020-21, 70.6% of graduates were either employed or in further study six months after completing the course. The median salary for employed graduates was £32,178.
Other:
Accreditation:
The MSc in Actuarial Science is accredited by the Institute and Faculty of Actuaries and recognized as a Center of Actuarial Excellence (CAE) by the Society of Actuaries. This accreditation demonstrates the high quality of the program and ensures that graduates meet the professional standards required for actuarial careers.
Scholarships & Funding:
Bayes Business School offers a range of scholarships and funding opportunities to support students' education. Students can also apply for government loans and other external funding sources.
Student Support:
Bayes Business School provides comprehensive support services to students, including academic advising, career guidance, and personal well-being support.
Location:
The program is located in the heart of London, offering students access to a vibrant and diverse city with a wealth of opportunities for learning, career development, and personal growth.
Tuition Fees and Payment Information:
UK/Home fee September 2024 entry £15,000 MSc Tuition fees are subject to annual change. International fee September 2024 entry £24,700 MSc 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).City's Fee status assessment policy.
