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Inside the Solvency 2 Black Box: Net Asset Values and Solvency Capital Requirements with a least-squares Monte-Carlo approach

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  • Floryszczak, Anthony
  • Le Courtois, Olivier
  • Majri, Mohamed

Abstract

The calculation of Net Asset Values and Solvency Capital Requirements in a Solvency 2 context–and the derivation of sensitivity analyses with respect to the main financial and actuarial risk drivers–is a complex procedure at the level of a real company, where it is illusory to be able to rely on closed-form formulas. The most general approach to performing these computations is that of nested simulations. However, this method is also hardly realistic because of its huge computation resources demand. The least-squares Monte Carlo method has recently been suggested as a way to overcome these difficulties. The present paper confirms that using this method is indeed relevant for Solvency 2 computations at the level of a company.

Suggested Citation

  • Floryszczak, Anthony & Le Courtois, Olivier & Majri, Mohamed, 2016. "Inside the Solvency 2 Black Box: Net Asset Values and Solvency Capital Requirements with a least-squares Monte-Carlo approach," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 15-26.
    • Handle: RePEc:eee:insuma:v:71:y:2016:i:c:p:15-26
    DOI: 10.1016/j.insmatheco.2016.07.005
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    References listed on IDEAS

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    Cited by:

    1. Makam, Vaishno Devi & Millossovich, Pietro & Tsanakas, Andreas, 2021. "Sensitivity analysis with χ2-divergences," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 372-383.
    2. Hainaut, Donatien & Devolder, Pierre & Pelsser, Antoon, 2018. "Robust evaluation of SCR for participating life insurances under Solvency II," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 107-123.
    3. Claus Baumgart & Johannes Krebs & Robert Lempertseder & Oliver Pfaffel, 2019. "Quantifying Life Insurance Risk using Least-Squares Monte Carlo," Papers 1910.03951, arXiv.org.
    4. Hongjun Ha & Daniel Bauer, 2022. "A least-squares Monte Carlo approach to the estimation of enterprise risk," Finance and Stochastics, Springer, vol. 26(3), pages 417-459, July.
    5. Hainaut, Donatien & Akbaraly, Adnane, 2023. "Risk management with Local Least Squares Monte-Carlo," LIDAM Discussion Papers ISBA 2023003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Le Courtois Olivier & Majri Mohamed & Shen Li, 2021. "Utility-Consistent Valuation Schemes for the Own Risk and Solvency Assessment of Life Insurance Companies," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 15(1), pages 47-79, January.
    7. Pierre-Edouard Arrouy & Alexandre Boumezoued & Bernard Lapeyre & Sophian Mehalla, 2022. "Economic Scenario Generators: a risk management tool for insurance," Post-Print hal-03671943, HAL.
    8. Alfonsi, Aurélien & Cherchali, Adel & Infante Acevedo, Jose Arturo, 2021. "Multilevel Monte-Carlo for computing the SCR with the standard formula and other stress tests," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 234-260.
    9. Aur'elien Alfonsi & Adel Cherchali & Jose Arturo Infante Acevedo, 2019. "A full and synthetic model for Asset-Liability Management in life insurance, and analysis of the SCR with the standard formula," Papers 1908.00811, arXiv.org.
    10. Aur'elien Alfonsi & Adel Cherchali & Jose Arturo Infante Acevedo, 2020. "Multilevel Monte-Carlo for computing the SCR with the standard formula and other stress tests," Papers 2010.12651, arXiv.org, revised Apr 2021.
    11. Massimo Costabile & Fabio Viviano, 2021. "Modeling the Future Value Distribution of a Life Insurance Portfolio," Risks, MDPI, vol. 9(10), pages 1-17, October.
    12. Massimo Costabile & Fabio Viviano, 2020. "Testing the Least-Squares Monte Carlo Method for the Evaluation of Capital Requirements in Life Insurance," Risks, MDPI, vol. 8(2), pages 1-13, May.
    13. Borgonovo, Emanuele & Clemente, Gian Paolo & Rabitti, Giovanni, 2024. "Why insurance regulators need to require sensitivity settings of internal models for their approval," Finance Research Letters, Elsevier, vol. 60(C).
    14. Pierre-Edouard Arrouy & Alexandre Boumezoued & Bernard Lapeyre & Sophian Mehalla, 2022. "Economic Scenario Generators: a risk management tool for insurance," Working Papers hal-03671943, HAL.

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