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Most insurers in the European Union determine their regulatory capital requirements based on the standard formula of Solvency II. However, there is evidence that the standard formula inaccurately reflects insurers’ risk situation and may provide misleading steering incentives. In the second pillar, Solvency II requires insurers to perform a so-called “Own Risk and Solvency Assessment” (ORSA). In their ORSA, insurers must establish their own risk measurement approaches, including those based on scenarios, in order to derive suitable risk assessments and address shortcomings of the standard formula. The idea of this paper is to identify scenarios in such a way that the standard formula in connection with the ORSA provides a reliable basis for risk management decisions. Using an innovative method for scenario identification, our approach allows for a simple but relatively precise assessment of marginal and even non-marginal portfolio changes. We numerically evaluate the proposed approach in the context of market risk employing an internal model from the academic literature and the Solvency Capital Requirement (SCR) calculation under Solvency II.
Pursuant to art. 45 of the Solvency II Framework Directive, all insurance undertakings will be obliged to conduct an “Own Risk and Solvency Assessment” (ORSA). ORSA’s relevance is not limited only to the second pillar of Solvency II, where mainly qualitative requirements are to be found. ORSA rather exhibits strong interlinks with the first pillar and its quantitative requirements and may also serve as a trigger for transparency duties which form Solvency II’s third pillar. ORSA may thus be described in some respects as the glue that binds together all three pillars of Solvency II. ORSA is one of the most obvious examples of the supervisory shift from a rules-based to a principles-based approach. As such, ORSA has hitherto been only very roughly defined. Since it is for the undertaking to determine its own specific risk profile and to evaluate whether this risk profile deviates significantly from the assumptions underlying the standard formula, it seems only natural that the supervisor must specify in greater detail what these underlying assumptions are. The most practicable way to do so would be for EIOPA to establish a “standard insurer”, which implies a translation of the assumptions concerning the underlying probability distributions into directly observable characteristics. The creation of the standard insurer would be an important step towards relaxing the insurers’ fear of what ORSA might bring about.