Measuring uncertainty of solvency coverage ratio in ORSA for non-life insurance | Zendy

Frédéric Planchet | Zendy; Quentin Guibert | Zendy; Marc Juillard | Zendy

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Measuring uncertainty of solvency coverage ratio in ORSA for non-life insurance

Author(s) -

Frédéric Planchet,

Quentin Guibert,

Marc Juillard

Publication year - 2012

Publication title -

european actuarial journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.661

H-Index - 13

eISSN - 2190-9741

pISSN - 2190-9733

DOI - 10.1007/s13385-012-0051-7

Subject(s) - solvency , solvency ratio , actuarial science , context (archaeology) , econometrics , asset (computer security) , log normal distribution , economics , mathematics , computer science , statistics , finance , geography , archaeology , market liquidity , computer security

International audienceWe apply a simple model to project the Solvency Capital Requirement (SCR) over several years, using an Own Risk Solvency Assessment (ORSA) perspective, in order to assess the probability of achieving a solvency coverage ratio. To do so, we rely on a simplified framework proposed in Guibert (Bulletin Français d’Actuariat 10(20), 2010) which provides a detailed explanation of the SCR. Then, we take into account temporal dynamics for liabilities, premiums and asset returns. Here, we consider guarantees in non-life insurance. This context, when simplified, allows us to use a lognormal distribution to approximate the distribution of the liabilities. It leads to a simple and tractable model for measuring the uncertainty of the solvency ratio in an ORSA perspective

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