Neural Networks Meet Least Squares Monte Carlo at Internal Model Data
8 & 15 June 2022 | 10:00-12:00 CEST
Solvency II aims at implementing a set of robust solvency rules for insurance companies, which takes the most material risks into account in an adequate way. In principle, the Solvency II framework requires the derivation of the full loss distribution of the available Own Funds, with the goal of deriving its correct Value-at-Risk. This particularly does not only involve a market consistent calculation of the economic balance sheet items at the valuation date but also its re-evaluation for each possible scenario at the risk horizon (one year within Solvency II).
Most insurance companies avoid this enormous effort by applying the standard formula approach to calculate the Solvency Capital Requirement (SCR). But the largest life insurers usually stick to the original Solvency II requirement and develop a full-scale internal model which allows them to calculate the economic balance sheet for thousands of one-year scenarios. The focus of this web session is on presenting a regression-based Monte Carlo approach in order to estimate the SCR. By doing so, we challenge the state-of-the-art Least Squares Monte Carlo approach based on polynomials by the most promising machine learning technique, namely ensemble of neural networks.
Your early-bird registration fee is € 200.00 plus 19% VAT for bookings by 27 April 2022. After this date, the fee will be € 270.00 plus 19% VAT.
