Zimbidis Alexandros

Zimbidis Alexandros serves as Assistant Professor of Stochastic Analysis with applications to Insurance and Finance at the Department of Statistics, School of Information Sciences and Technology, Athens University of Economics and Business (AUEB). He concurrently acts as a consultant for pension funds in both private and public sectors.

His academic credentials include:

• First-class Mathematics degree from University of Athens
• MSc with distinction in Actuarial Science from City University of London
• PhD in Actuarial Science from City University of London

Dr. Zimbidis specializes in Actuarial Science and Stochastic Analysis applied to insurance and financial systems, with particular expertise in earthquake risk modeling, pension fund sustainability, and competitive insurance market dynamics. His research integrates advanced stochastic processes, control theory, and catastrophe modeling to address solvency requirements and risk assessment challenges.

Recent publications (2022-2024) reveal a pronounced focus on fault-specific earthquake risk quantification using neural networks and epidemic-type models, alongside innovations in IFRS17 compliance and pension contribution optimization through H∞-control theory. His work consistently bridges theoretical stochastic analysis with practical regulatory and industry applications.

Key recognitions include:

• Acknowledgment by The Institute of Actuaries of Japan for earthquake risk research
• Acknowledgment by Institute & Faculty of Actuaries of London for earthquake risk research
• Dedicated session at Casualty Actuarial Society (CAS) Annual Meetings for insurance pricing research

With extensive industry experience as former director of a multinational insurance company and inaugural President of Greece's National Actuarial Authority, Dr. Zimbidis has developed numerous actuarial studies for corporate and social security pension systems. His six university textbooks and journal publications demonstrate significant contributions to actuarial methodology and risk modeling.