Low Fat Modeling and Reinsurance Induced Solvency
J. Henk von Eije
Abstract
J. Henk von Eije
Abstract
The evaluation of the impact of reinsurance on solvency of primary insurance companies is generally based on financial ratios. Ratio-analysis, however, lacks theoretical rigor and it may even lead to flagrant misunderstandings if reinsurance is sought for non-solvency reasons. This article indicates how measures based on financial theory can be used to improve reinsurance performance measurements. Normally these performance measures do not indicate the impact of reinsurance in the margin and are therefore useless in generating advise on reinsurance strategy. Answers to reinsurance policy questions may, however, be found if a low fat model is used in representing the main processes within insurance companies. The application of such a model is shown in estimates of the marginal impact of reinsurance in 13 of the largest non-life insurance companies in the Netherlands.
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The evaluation of the impact of reinsurance on solvency of primary insurance companies is generally based on financial ratios. Ratio-analysis, however, lacks theoretical rigor and it may even lead to flagrant misunderstandings if reinsurance is sought for non-solvency reasons. This article indicates how measures based on financial theory can be used to improve reinsurance performance measurements. Normally these performance measures do not indicate the impact of reinsurance in the margin and are therefore useless in generating advise on reinsurance strategy. Answers to reinsurance policy questions may, however, be found if a low fat model is used in representing the main processes within insurance companies. The application of such a model is shown in estimates of the marginal impact of reinsurance in 13 of the largest non-life insurance companies in the Netherlands.
Key concepts: Reinsurance, Solvency, Actuarial science, Business, Margin (machine learning), Solvency ratio, Econometrics, Economics