AI / Data Science
In Pursuit of Responsible AI – An Actuarial Profession Take
In 2024, the International Actuarial Association established a dedicated Task Force to guide the actuarial profession's response to Artificial Intelligence. After two years of work spanning governance, education, professionalism, and the evolving role of the actuary, the Task Force is proud to present three foundational papers on the responsible use of AI in this webinar.
Speaker: Bernice Lim, Chadwick Cheung, Dorothy Andrews
Moderator: Peter Withey
Speaker: Bernice Lim, Chadwick Cheung, Dorothy Andrews
Moderator: Peter Withey
Members Only
ERM
AFIR-ERM: Signature-based Validation of Real-world Economic Scenarios
Motivated by insurance applications, we propose a new approach for the validation of real-world economic scenarios. This approach is based on the statistical test developed by Chevyrev and Oberhauser (2022) and relies on the notions of signature and maximum mean distance. This test allows to check whether two samples of stochastic processes paths come from the same distribution. Our contribution is to apply this test to a variety of stochastic processes exhibiting different pathwise properties (Hölder regularity, autocorrelation, and regime switches) and which are relevant for the modelling of stock prices and stock volatility as well as of inflation in view of actuarial applications.
Speaker: Hervé Andrès
Session Moderator: Łukasz Delong
Speaker: Hervé Andrès
Session Moderator: Łukasz Delong
Professionalism
IAN 300: Professional Judgment
In this webinar hosted by the IAA’s Professionalism Committee, speakers introduce the key concepts presented in IAN 300 and explain how professional judgment differs from expert judgment. The Note highlights that professional judgment goes beyond technical expertise, incorporating ethical principles, professional standards, regulatory frameworks, public accountability, and contextual awareness.
The International Actuarial Association (IAA) released International Actuarial Note 300 (IAN 300) – Professional Judgment in Actuarial Practice in September 2025 as an educational resource for actuaries and professionals with an actuarial background.
This webinar provides valuable insights into how International Actuarial Note 300 (IAN 300) can support actuaries in applying sound professional judgment in their day-to-day practice.
The International Actuarial Association (IAA) released International Actuarial Note 300 (IAN 300) – Professional Judgment in Actuarial Practice in September 2025 as an educational resource for actuaries and professionals with an actuarial background.
This webinar provides valuable insights into how International Actuarial Note 300 (IAN 300) can support actuaries in applying sound professional judgment in their day-to-day practice.
Members Only
Pensions
PBSS: Risk Sharing Mechanisms in PAYG Public Pension Schemes
Classical public pension schemes combine usually PAYG mechanism and Defined Benefit architecture. Aging threatens clearly this kind of structure and motivates the development of hybrid solutions mixing on one side PAYG and Fully funding and on the other side DB and DC (Defined Contribution). The purpose of this presentation is to develop some of these hybrid plans and introduce actuarial tools in order to implement inter-generational and intra generational fairness and sustainability in these public programs.
Speaker: Pierre Devolder
Session Moderator: Jennifer Alonso Garcia
Speaker: Pierre Devolder
Session Moderator: Jennifer Alonso Garcia
Members Only
AI / Data Science
PBSS: AI for Pension Funds: Insights and Use Cases
Unlock how Artificial Intelligence is reshaping pensions and social security work. Join us for an insightful session featuring leading actuarial AI expert Ronald Richman, who will share practical applications of AI in longevity modelling, experience analysis, and actuarial workflow automation. This webinar will highlight real-world use insights, emerging opportunities, and what actuaries doing work in pensions and social security need to know to stay ahead in an AI-driven future.
Be sure to join us for what promises to be an informative and engaging discussion.
Speaker: Ronald Richman
Moderator: John Anderson
Be sure to join us for what promises to be an informative and engaging discussion.
Speaker: Ronald Richman
Moderator: John Anderson
Members Only
AI / Data Science
ASTIN: Explainable AI for Claims Reserving: Bridging Actuarial Practice and Machine Learning
This session brings together actuarial and machine learning perspectives to explore how AI can support reserving practices.
The actuarial perspective will cover the practical limitations of current reserving workflows, where judgment enters traditional methods and why consistency is difficult, and what actuaries need from AI, including transparency, validation, and governance. It will also include a case study comparing traditional results with AI-supported modeling and how ML results can serve as a second-opinion framework.
The machine learning perspective will cover the Bayesian ML framework, including its architecture, model selection based on predictive power and cross-validation, and how explainability is built into the model. It will also discuss why full distributions matter more than point estimates and share technical lessons from applying ML to insurance triangles.
Speakers: Ben Zickel and Yulia Nechay Moderator: Joana Raposo
The actuarial perspective will cover the practical limitations of current reserving workflows, where judgment enters traditional methods and why consistency is difficult, and what actuaries need from AI, including transparency, validation, and governance. It will also include a case study comparing traditional results with AI-supported modeling and how ML results can serve as a second-opinion framework.
The machine learning perspective will cover the Bayesian ML framework, including its architecture, model selection based on predictive power and cross-validation, and how explainability is built into the model. It will also discuss why full distributions matter more than point estimates and share technical lessons from applying ML to insurance triangles.
Speakers: Ben Zickel and Yulia Nechay Moderator: Joana Raposo