Director, Insurance Specialist
Alexis is responsible for the advancement of Moody’s Analytics insurance activities in EMEA. He contributes to the development of Moody’s Analytics Solvency II client propositions, in particular with internal models and ORSA.
Before joining Barrie & Hibbert in 2008 – three years before its acquisition by Moody’s Analytics – he had extensive experience in ALM and economic capital modeling at Towers Watson in London and previously worked in risk management and valuation roles at Zurich Financial Services. Alexis is a fellow of the actuarial associations in the UK, France, and Switzerland and has an MA in Quantitative Finance from ETH Zurich.
Institutions are transforming their analytic capabilities to move beyond static reports that explain what happened in the past, to more modern analytics that can explain why an event occurred and what is likely to happen in the future.
This article reviews the analysis of an asset optimization problem where risk is defined by the capital required under Solvency II principles, and where the portfolio performance is defined by the net asset value at time T=1.
Asset optimization which focuses only on the distributional characteristics of an investment portfolio will fail to achieve an optimal portfolio from the perspective of value creation for a life insurance firm. In this paper we show how this issue can be resolved through the application of Least Squares Monte Carlo techniques.