Ioannis Kyriakou

Professor Ioannis Kyriakou is a leading academic in actuarial finance and quantitative methods at Bayes Business School, City St George's, University of London, where he serves as Professor of Actuarial Finance and Director of the MSc in Actuarial Science and MSc in Actuarial Management. He holds a visiting professorship at the University of Eastern Piedmont and has previously served as affiliate faculty at the Cyprus International Institute of Management. His research spans actuarial science, derivatives pricing, risk management, computational finance, and machine learning applications in finance and insurance.

His research interests focus on quantitative finance, stochastic modeling, numerical methods, and machine learning, particularly in the context of derivative pricing, pension product design, energy and commodity markets, and investor sentiment. He has developed advanced computational techniques such as moment-based approximations and transform methods for financial modeling. His work integrates simulation, optimization, and data-driven approaches to solve complex financial and actuarial problems.

The recent publications reflect a strong trend toward interdisciplinary research, combining machine learning with financial economics, energy efficiency forecasting, mutual fund performance, and climate risk. His work frequently appears in top journals like Operations Research, Journal of Financial and Quantitative Analysis, and European Journal of Operational Research, showcasing expertise in both theoretical and applied finance.

• European Journal of Operational Research (2020) Editors' Award for Excellence in Reviewing
• Cass Business School (2014) Prize for Excellence in Teaching and Learning
• Dimitris N. Chorafas Foundation (2009) Prize for outstanding PhD research work
• EPSRC Doctoral Training Award (2008)

He supervises several PhD students in areas such as derivatives pricing, machine learning in actuarial science, and pension optimization. He has received research support through editorial leadership, consultancy (e.g., with Lloyd’s Treasury), and academic collaboration. He is actively involved in organizing conferences and workshops, including the Finance and Business Analytics Conference.

He is affiliated with research groups focusing on financial modeling, actuarial computation, and machine learning in insurance, contributing to both academic and industry-facing initiatives. His co-authored book Machine Learning in Insurance (MDPI, 2020) highlights his leadership in bridging data science with actuarial applications.