About the PhD in Actuarial Science programme
The Faculty of Actuarial Science and Insurance is one of the leading academic actuarial departments in the world, with highly respected degree courses and research. It comprises 29 staff, including eight qualified actuaries.
The Faculty makes use of its position close to the heart of the City of London to enhance its research, teaching and external profile.
As such, the Faculty is proud of its PhD in Actuarial Science programme. On this programme you will have the full support of the faculty as well as access to the research and insights from one of the world’s leading actuarial departments.
The Faculty's research considers a range of theoretical and applied issues in:
- General and life insurance
- Health and social care
- Machine learning and analytics
- Mortality and longevity modelling
- Pensions and investment
- Risk management
- Stochastic modelling of risk in insurance and finance
Please visit the webpages of for individual faculty research interests or more information on the potential research topics they are willing to supervise.
You do not need to find a potential supervisor before you apply, but it is useful to indicate in your application the member of academic staff with research interests similar to your own. The final decision on supervisors is made by the PhD Director.
The Actuarial Science PhD is usually a four year programme. You are registered on the MPhil degree for the first two years during which you will follow a programme of taught courses and prepare your first research paper.
Year 1 - Theory and Methods
In the first year you will attend a number of taught courses aiming to provide training in your research field and exposure to wider research areas. You will be able to take PhD-level courses in Finance, as well as, if appropriate, drawn from Bayes MSc programmes. These courses are academically rigorous and you will need to be examined in them.
In parallel, you will commence your academic research, under the supervision of Bayes academics. At the end of the first academic year, you will submit a research dissertation, demonstrating a clear formulation of a suitable research topic and substantial progress towards your first academic paper.
Throughout your time as a Bayes MPhil/ PhD student, you will be attending research seminars held by the Faculty of Actuarial Science and Insurance.
In order to progress to the following year students will need to pass a minimum of three or a maximum of five modules and complete a dissertation in the third term.
Year 2 - Research and Teaching Skills
Your research training continues in the second year with workshops and seminars focused on further developing your research skills further and courses introducing you to the practice of learning, teaching and assessment.
Alongside this, you will continue your academic research in your chosen topics. The year culminates with the defence of your first research paper before a transfer panel committee, towards the end of term 2.
After the successful defence of your transfer panel paper you will move onto the final two years of the PhD programme.
Year 3 - Year 4
You complete your remaining research papers in years three and four and defend your work at the viva voce examination soon after completion of your thesis. The focus of training in the final two years shifts towards preparing you for an academic career.
You will be supported by Bayes academics to prepare for the viva voce and the academic job market, with the aim of you successfully defending your thesis and taking up an academic position at a leading academic institution or a research-oriented job at a financial institution.
Fees and Funding
UK (Home) Students
- Full-time: £4,690 per year
Non UK/EU (Overseas) Students
- Full-time: £12,000 per year
Facilities and research
PhD students on the PhD Actuarial Science programme have access to the state of the art research infrastructure, computing equipment, and extensive library resources.
Bayes Business School offers access to a wide range of databases, including:
- Thomson Reuters EIKON
- Thomson One and many others.