Individuals who join the IFoA having obtained the CAA qualification can continue their studies to Associate or Fellow of the IFoA. Along with the assessment requirements, these individuals are required to demonstrate their relevant work experience by completing PPD (personal and professional development).
The PPD requirement for CAA certified members is less than the requirement for IFoA students as CAA certified members have to complete a higher level of IFoA CPD (continuous professional development).
For CAA Certified members who are not looking to qualify as an Associate or Fellow, there is no annual PPD requirement.
PPD requirements for CAA certified members are as follows:
Desired qualification level
|Minimum work experience required||Minimum competencies required*||Minimum number of formal learning hours|
|Prior 2 January 2019||Associate||12 Months||
|Post 2 January 2019||Associate||24 Months||1.1, 2.1||0|
|Fellow||36 Months||1.1, 2.1||0|
|Members who join after 2 January 2019 need to achieve Associate status first, and then progress to Fellowship after a further 12 months of PPD recording.|
*Competencies 1.1 and 2.1 only need to be completed once before qualification, they do not need to be completed every year.
Complete the final sign off form
When Members are ready to transfer to either Associate or Fellow they should complete and send to us the below final sign off form to confirm they have completed all work experience requirements.
Member Services Team
Institute and Faculty of Actuaries, 1st Floor, Park Central, 40/41 Park End Street, Oxford, OX1 1JD
We aim to respond to all enquiries within two working days.
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This practical course is aimed at actuaries at any stage of their career who want to develop their own growth mindset and apply it to their work setting and personal or professional lifelong learning. The content of the course builds on the lecture given by Dr Helen Wright on Growth Mindset as part of the President’s 2021 Lecture series, and will be delivered over a period of 2 months, from mid-October to early December.
Actuaries need to take action now - but how? With a focus on climate change, this session will provide informed insight to enable you to improve your knowledge and understanding of the issues involved, demonstrate how it will impact advice to your clients, and highlight prospective opportunities for actuaries within pensions and wider fields.
A joint webinar from the CMI Mortality Projections and SAPS committees that will cover: recent mortality experience in the SAPS dataset and the general population; the CMI Model benchmarking survey; the MPC 2021 interim update paper; plans for CMI_2021; and initial thoughts on possible "S4" Series pensioner mortality tables.
The webinar will be presented by Cobus Daneel (Chair of Mortality Projections Committee) and Matthew Fletcher (Chair of SAPS Committee).
Pension scams have become more prevalent as a result of the pandemic, and Trustees have increased responsibilities to protect members, which means that actuaries need to be in a position to provide advice in this area. Our specialist panel will include a professional trustee, an IFA and head administrator, two of whom are members of PASA.
The Covid-19 pandemic creates a challenge for actuaries analysing experience data that includes mortality shocks. To address this we present a methodology for modelling portfolio mortality data that offers local flexibility in the time dimension. The approach permits the identification of seasonal variation, mortality shocks, and late-reported deaths. The methodology also allows actuaries to measure portfolio-specific mortality improvements. Results are given for a mature annuity portfolio in the UK
In this webinar, the authors of the 2021 Brian Hey prize winning paper present a new deep learning model called the LocalGLMnet. While deep learning models lead to very competitive regression models, often outperforming classical statistical models such as generalized linear models, the disadvantage is that deep learning solutions are difficult to interpret and explain, and variable selection is not easily possible.
The dominant underwriting approach is a mix between rule-based engines and traditional underwriting. Applications are first assessed by automated rule-based engines which typically are capable of processing only simple applications. The remaining applications are reviewed by underwriters or referred to the reinsurers. This research aims to construct predictive machine learning models for complicated applications that cannot be processed by rule-based engines.
With the Pension Schemes Act 2021 requiring a long term strategy from Trustees and sponsors, choosing a pensions endgame strategy has become even more critical. However, it is important that the endgame options available are adequately assessed before choosing one. With an ever-increasing array of creative and innovative options available, this decision may not be straightforward.