The Solvency II Directive for insurance and reinsurance companies in the EU comes into force on December 31st 2012. The Directive mandates a much more stringent approach to capital adequacy, much in the same way that Basel II and the forthcoming Basel III impose such requirements on the banking sector.
To comply with Solvency II, companies must either use a standard model, which is effectively a “one size fits all” approach to calculating risk and, therefore, capital requirements; or they can build their own Internal Model. The latter is likely to be more efficient since it will be specific to the individual company. For this reason most major (re-)insurance companies have opted to take the latter approach. However, the Internal Model will have to be approved by supervisory authorities who will require a) that the model is evidence-based and b) that it is in use within the organisation—this is not just a theoretical exercise.
To ensure the accuracy of the Internal Model is going to be of paramount concern and this requires that the historic information used to build the model is complete and accurate and that current information about policies and policy holders is similarly valid and that it will remain so in the future. While we will touch on other elements required to support the creation of an Internal Model, and Solvency II more broadly, in this paper our primary focus is on this data quality element and the importance attached to it. We will also consider how any data quality and governance initiatives adopted to support Solvency II can be extended in order to provide additional business benefits.
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