Short Bio
INSURANCE, RISK MANAGEMENT & DATA SCIENCE
Matteo Lizzi is a fully Qualified Member of O.N.A. – Italian National Order of Actuaries. He has worked for 8 years in the Insurance Industry sector, mainly as a Life Actuary, and holds a Ph.D. in Actuarial Sciences from the Sapienza University of Rome, with a thesis project in “Improving mortality diagnostics and estimation through Contrast Trees”.
His research interests focus on the application of machine learning techniques to Actuarial Sciences.
His research interests focus on the application of machine learning techniques to Actuarial Sciences.
Selected Publications
- Levantesi, S., Lizzi, M., & Nigri, A. (2022). An application of contrast trees for mortality models diagnostic and boosting. In Book of short papers. IES 2022 Innovation & society 5.0: statistical and economic methodologies for quality assessment (pp. 219-224). PKE srl.
- Levantesi, S., Lizzi, M., & Nigri, A. (2024). Enhancing diagnostic of stochastic mortality models leveraging contrast trees: an application on Italian data. Quality & Quantity, 58(2), 1565-1581.
DOI: https://doi.org/10.1007/s11135-023-01711-x - Lizzi, M. (2024). A Contrast-Tree-Based Approach to Two-Population Models. Risks, 12(10), 152.
DOI: https://doi.org/10.3390/risks12100152
