The Actuarial Monitoring Scheme (AMS) is a system for monitoring the work of actuaries. It is designed to improve the effectiveness of actuarial regulation in the public interest, provide meaningful, credible, independent feedback to members and their employers and promote ongoing reinforcement and continuous improvement.
The AMS forms an important part of a professionalism framework designed, through carefully balanced interventions and support, to provide evidence of the quality of actuarial work and to promote best practice. It will allow us to consider, in time, issues of relevance to members across the profession, wherever they are practising.
In the summer of 2018 the IFoA consulted on proposals to introduce monitoring of the quality of actuarial work. Following one of the largest response rates to a regulatory consultation that we have ever received, we announced in late 2018, the decision of the IFoA’s Regulation Board to proceed with the introduction of:
- Regular Thematic Reviews looking at particular topics, roles and/or areas of work relevant to actuaries; and
- Data Gathering activities on a scheduled and ad hoc, thematic basis. To include (but not limited to) questionnaires, surveys, analysis of insights shared by co-regulators, workshops, focus groups and information obtained from the IFoA's Quality Assurance Scheme.
The outcome of these reviews and data gathering will be used to continuously improve, and, if necessary, adapt the AMS, to ensure that those forms of monitoring are working effectively.
For more information please contact the Actuarial Review Team
Level 2, Exchange Crescent · 7 Conference Square · Edinburgh · EH3 8RA
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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.