PBSS Webinar – Introducing AI in Pension Planning

Funded pensions have gained considerable attention as a strategy for securing supplementary income in retirement. This presentation aims to provide a comparative analysis of two methods for estimating the replacement rate: a deep learning model and a Fuzzy Mamdani Inference System (FIS). Since AI has gained considerable ground in the actuarial universe, an obvious step would be to investigate AI techniques, such as neural networks and fuzzy logic, in the realm of pension planning. Initial results indicate that these methods provide accurate estimations, warranting further analysis.

Jennifer Alonso García is a tenured Professor of Actuarial Science in the Department of Mathematics. She is also an Associate Investigator at CEPAR and a Netspar Fellow. Her research bridges actuarial science, household finance, pensions, and quantitative finance, focusing on the design, risk-sharing, and financing of both funded and pay-as-you-go retirement income schemes. Jennifer is currently involved in research projects on household financial decision-making during retirement, life expectancy inequality, and the design and risk management of equity-linked retirement income products.

George Symeonidis holds a Doctorate in Economics of Insurance and is a fully qualified actuary. He serves as Chair of the Board of the International Association of Consulting Actuaries (IACA) and is an Executive Board Member of the Greek pensions regulator. Additionally, he is active in academia as a lecturer.