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Largest Claims Reinsurance (LCR). A Quick Method to Calculate LCR-Risk Rates from Excess of Loss Risk Rates

Published online by Cambridge University Press:  29 August 2014

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Let us denote by E(x) the pure risk premium of an unlimited excess cover with the retention x and by H(x) and m(x) the corresponding expected frequency and severity.

We thus have E(x) = H(x) · m(x).

H(x) is a non-increasing function of x and for practical purposes we can assume that it is decreasing; H′(x) < o. The equation H(x) = n has then only one solution xn, where n is a fixed integer.

Let En denote the risk premium for a reinsurance covering the n largest claims from the bottom.

Let us define Intuitively we feel that is a good approximation for En.

We shall first show that when the claims size distribution is Pareto and the number of claims is Poisson distributed, is a good approximation for En, being slightly on the safe side. We further include a proof given by G. Ottaviani that the inequality always holds.

In the Pareto case we have

where the Poisson parameter t stands for the expected number of claims in excess of 1 (equal to a suitably chosen monetary unit) and

.

Type
Research Article
Copyright
Copyright © International Actuarial Association 1978

References

[1] Ammeter, H., The Rating of “Largest Claim” Reinsurance Covers. Quarterly Letter from the Algemeene Reinsurance Companies Jubilee Number 2, July 1964.Google Scholar
[2] Berliner, B., Correlations between Excess of Loss Reinsurance Covers and Reinsurance of the n Largest Claims. The ASTIN Bulletin Vol. VI, Part III, May 1972.Google Scholar