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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.
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