Experience

4most

• United Kingdom
• Financial Services
• 100 - 200 Employee

• Actuarial Consultant

  • Dec 2018 - Present

  - Development of capital aggregation partial internal models in Tyche on different bases (Solvency II, Bermuda, USGAAP).- Optimisation of RAFM stochastic models to reduce runtime and memory usage.- BAU developments and maintenance of RAFM models.- Review of equity release mortgage models.- Supporting clients on financial reporting cycles (e.g. Analysis of Change and Surplus, Sensitivity Analysis).



Pacific Life Re

• Bermuda
• Insurance
• 500 - 600 Employee

• Actuarial Modeller

  • Sep 2017 - Dec 2018

  - Migration of long-term protection models, under different reporting metrics, from MoSes to Tyche: drafting of business requirements, data validation, implementation, optimization and testing. - BAU developments and maintenance of existing MoSes modelling suite.- Modelling training and support to other actuarial functions of the company.



Willis Towers Watson

• Life Actuarial Analyst

  • Jul 2015 - Aug 2017

  - Model optimisation and migration processes from MoSes to RAFM.- Model development and maintenance of several large life insurers, including: ALM, pricing of financial instruments (e.g. bonds, options on equity, options on interest rates), projection of P&L items of life insurance contracts via MoSes and RAFM.- M&A valuations: validity assessment of assumptions (economic/ESG, non-economic, demographic) and review of the appropriateness of underlying modelling methodologies.- Education and training of both modellers and end-users of models.During this period, I have also been involved in the following Non-Life projects:- Implementation of operational risk models in Igloo.- Risk aggregation and optimisation of reinsurance structures to help clients develop appropriate cession strategies.



Department of Statistics and Quantitative Methods, University of Milano-Bicocca

• PhD candidate in Statistics

  • Nov 2011 - Dec 2014

  Dissertation title: “COGARCH processes: theory and asymptotics for the pseudo-maximum likelihood estimator”Abstract:COGARCH processes are Lévy driven continuous time version of well known GARCH models for modeling high-fequency and irregularly time spaced financial returns. After a brief introduction to the theory of Lévy processes and related stochastic calculus we focus on both symmetric and asymmetric COGARCH models. Probabilistic results about Markovianity, stationarity and moments are prerequisites to draw statistical inference from irregularly spaced observations. In particular, we propose a new version of the pseudo-maximum likelihood estimator in order to prove asymptotic properties, that are confirmed by means of a Monte Carlo simulation study.



Department of Mathematics, Technical University of Munich, Germany

• Visiting PhD candidate

  • Nov 2013 - Oct 2014

  Research activities on stochastic models applied to finance and actuarial sciences.- Statistical estimation of Lévy driven stochastic volatility models.- Algorithmic implementation via Matlab and R for simulation, inferentialprocedures and applications to high-frequency data.