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AI and emerging technologies: research working parties

The following are active research working parties overseen by the IFoA’s AI and Emerging Technologies Practice Board.

You can view their outputs and learn more about each party in our Virtual Learning Environment.

Volunteer for a working party

All members are encouraged to volunteer for a research working party. If you have your own ideas for member-led research you would like to pursue, please contact our Practice Communities Team below or refer to our Guidance for Research Working Parties (562 KB PDF).

Members interested in volunteering for a research working party should check our volunteer vacancies.

Research working parties

This working party will investigate tools and packages available to perform data visualisation and produce outputs that conform to best practice in the area.

Chair: Stephen Windell
Established: 2020

This working party will conduct a systematic review of AI applications in actuarial science, leaning towards practitioner's perspective.

The aim of this study would be to investigate whether the pricing/reserving/capital (actuarially driven departments in insurance companies) could improve their output through the use of AI-based tools and why. Both cases, where AI does not bring satisfiable results that would justify disruption and the converse should be examined, yielding a clear view of the direction of the actuarial profession.

Chair: Karol Gawłowski
Established: 2023

This working party will undertake research into the use of Bayesian methods.

Chair: Saunak Datta
Established: 2022

This group is developing resources to support the actuarial profession and our members with ethics and professionalism in relation to AI, data science and emerging technologies.

Chair: Matthew Byrne
Start: 2026

The aim of this working party is to:

  1. Broaden knowledge of Privacy Preserving ML methods and their application in insurance industry.
  2. Popularize Federated Learning Machine Learning techniques.
  3. Increase awareness of the industry on how the technology might change the way insurance works.
  4. Understand potential difficulties and risks in adopting FL technology in insurance and attempt to address those issues.
  5. Understand when it is worth collaborating and when companies should rely on their own data.

Chair: Malgorzata Smietanka
Established: 2020

This research will demonstrate NLP techniques through the research of sentiment analysis using Twitter data and will also undertake other AI focused research.

Chair: Lei Fang
Established: 2020

The aim of this working party is to focus on:

  • Members’ engagement and education (events, content).
  • DS-support of IFoA Education (exams, etc.).
  • Collaboration with DS WPs.
  • Content distribution channels.

Chair: Alexey Mashechkin
Established: 2018

The group will initially focus on three workstreams:

  1. Understanding the impacts of AI: Examine the environmental, social, and broader systemic impacts arising from increased adoption of AI technologies, including energy use, resource consumption, workforce implications, and potential inequities.
  2. Implications for corporate practice: Identify the considerations organisations should incorporate into their AI strategies (for example AI safety policies and policies for treating labour displacement) to responsibly manage business risks, ensure transparency, and minimise negative real world impacts on people and the environment.
  3. Role of the actuarial profession in shaping policy: Explore how the actuarial profession can collaborate with policymakers to define effective guardrails, standards, and governance frameworks that support safe, ethical, and sustainable deployment of AI across industries.

Chair: Clare Keeffe
Established: 2026

This working party will:

  • Looking at applications of data science techniques to solve climate-related problems.
  • Producing related content, including in collaboration with the Sustainability Board.

Chair: Pip King
Established: 2022

The aim of this working party is to:

  1. Demonstrate concepts behind XAI to IFoA members with a view to myth busting the notion that “Machine learning models are black boxes”.
  2. Provide guidance notes around embedding XAI practices in any future actuarial work relying on AI. (Note that there is potential crossover here into Ethical AI and attitudes to AI in general).

Chair: David Bennett
Established: 2017

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