A retrospective rating plan, whose insurance premium depends upon an insured's actual loss during the policy period, is a special insurance agreement widely used in liability insurance. In this paper, the design of an optimal retrospective rating plan is analyzed from the perspective of the insured who seeks to minimize its risk exposure in the sense of convex order. In order to reduce the moral hazard, we assume that both the insured and the insurer are obligated to pay more for a larger realization of the loss. Under the further assumptions that the minimum premium is zero, the maximum premium is proportional to the expected indemnity, and the basic premium is the only free parameter in the formula for retrospective premium given by Meyers (2004) and that the basic premium is determined in such a way that the expected retrospective premium equates to the expected indemnity with a positive safety loading, we formally establish the relationship that the insured will suffer more risk for a larger loss conversion factor or a higher maximum premium. These findings suggest that the insured prefers an insurance policy with the expected value premium principle, which is a special retrospective premium principle with zero loss conversion factor. In addition, we show that any admissible retrospective rating plan is dominated by a stop-loss insurance policy. Finally, the optimal retention of a stop-loss insurance is derived numerically under the criterion of minimizing the risk-adjusted value of the insured's liability where the liability valuation is carried out using the cost-of-capital approach based on the conditional value at risk.

In this study, we propose new risk measures from a regulator’s perspective on the regulatory capital requirements. The proposed risk measures possess many desired properties, including monotonicity, translation-invariance, positive homogeneity, subadditivity, nonnegative loading, and stop-loss order preserving. The new risk measures not only generalize the existing, well-known risk measures in the literature, including the Dutch, tail value-at-risk (TVaR), and expectile measures, but also provide new approaches to generate feasible and practical coherent risk measures. As examples of the new risk measures, TVaR-type generalized expectiles are investigated in detail. In particular, we present the dual and Kusuoka representations of the TVaR-type generalized expectiles and discuss their robustness with respect to the Wasserstein distance.

We consider a profitable, risky setting with two separate, correlated asset and liability processes (first introduced by Gerber and Shiu, 2003). The company that is considered is allowed to distribute excess profits (traditionally referred to as dividends in the literature), but is regulated and is subject to particular regulatory (solvency) constraints. Because of the bivariate nature of the surplus formulation, such distributions of excess profits can take two alternative forms. These can originate from a reduction of assets (and hence a payment to owners), but also from an increase of liabilities (when these represent the wealth of owners, such as in pension funds). The latter is particularly relevant if distributions of assets do not make sense because of the context, such as in regulated pension funds where assets are locked until retirement. In this paper, we extend the model of Gerber and Shiu (2003) and consider recovery requirements for the distribution of excess funds. Such recovery requirements are an extension of the plain vanilla solvency constraints considered in Paulsen (2003), and require funds to reach a higher level of funding than the solvency level (if and after it is triggered) before excess funds can be distributed again. We obtain closed-form expressions for the expected present value of distributions (asset decrements or liability increments) when a distribution barrier is used.

We propose a new approach to mortality prediction under survival energy hypothesis (SEH). We assume that a human is born with initial energy, which changes stochastically in time and the human dies when the energy vanishes. Then, the time of death is represented by the first hitting time of the survival energy (SE) process to zero. This study assumes that SE follows a time-inhomogeneous diffusion process and defines the mortality function, which is the first hitting time distribution function of the SE process. Although SEH is a fictitious construct, we illustrate that this assumption has the potential to yield a good parametric family of cumulative probability of death, and the parametric family yields surprisingly good predictions for future mortality rates.

Dans plusieurs études [1] Ammeter a démontré que la distribution binomiale négative généralisée peut être interprétée de différentes manières, à savoir comme

a. une contagion des probabilités (Pólya-Eggenberger);

b. une distribution de Poisson basée sur des probabilités fondamentales variables;

c. une distribution de Poisson où la probabilité fondamentale de sinistres n'est pas suffisamment connue;

d. une distribution de Poisson par rapport aux événements, où un seul événement peut comporter plusieurs prétentions de sinistres;

e. une distribution de Poisson basée sur une modification de la répartition des montants de sinistres.

On a, en effet, les relations suivantes:

a. la contagion des probabilités

où F(x, P, h, p(z)) représente la probabilité que le sinistre est au plus égal à x dans un intervalle de temps où le sinistre probable est P. x et P y sont exprimés en le sinistre moyen par événement. p(z)dz est la fonction de fréquence du sinistre par événement.

Nous posons est la convolution de p(z) avec p(z), faite r fois, tandis que h est la notation du paramètre qui figure dans la distribution binomiale négative. Si h est égal à ∞ nous obtenons comme fonction de répartition pour le nombre d'événements survenus la distribution de Poisson.

Ce rapport n'a pas le but de résumer toute la littérature actuarielle sur les assurances non viagères: on se proposait de tracer le fil conducteur de quelques uns des développements d'idées où l'apport des mathématiques est plus profond et, en particulier, de ceux où il semble qu'il y aura encore à travailler longtemps. A ce compte, seulement quelques étapes pouvaient être explicitement mentionnées dans le texte, tandis qu'une bibliographic complète aurait dû suivre à la fin du rapport.

Maintes circonstances ont restreint le temps à disposition des rapporteurs et ont augmenté les difficultés d'un travail en commun à distance; sans doute quelques contributions ont échappé ou n'ont pas reçu le relief qu'il aurait fallu leur donner. Les auteurs prient de bien vouloir justifier les omissions par ces circonstances, et de les leur signaler.

L'assurance sur la vie et les assurances non viagères semblent présenter des différences essentielles, soit au point de vue de leur objet (indemnité d'une perte dans le deuxième cas, mais non dans le premier), soit au point de vue de leur méthode (théorie mathématique complétement développée dès longtemps pour le premier cas, mais non dans le deuxième).

Ya-t-il néanmoins une notion unique d'assurance, en général, qui comprenne toutes les deux? Est-il possible de concevoir d'une façon unique l'application du calcul des probabilités et des méthodes mathématiques qui le traduisent, dans le champ de l'assurance en général? Ou ya-t-il des limitations, ou des circonstances qui obligent à distinguer à cet effet les deux champs de l'assurance sur la vie et de l'assurance non viagère?

Une Compagnie d'assurances délivre par l'intérmediaire d'Agences de Voyage des contrats d'assurances individuelles garantissant les personnes prenant place dans des autocars contre les décès par accident. Le capital garanti est uniforme. Il sera pris égal à I par simplification.

Cette Compagnie prend à sa charge le paiement de i décès au maximum dans chaque accident et demande à un Réassureur de payer, aux termes d'un traité en excédent de sinistre, les autres décès; autrement dit, si un accident cause d décès, la Compagnie paie I, le Réassureur en excess paie d — I.

Il s'agit de calculer la prime de ce traité en excédent de sinistre?

La solution dépend de trois paramètres:

n nombre de passagers par autocar, égal au maximum au nombre de places; on supposera, pour fixer les idées, n = 502).

d nombre de décès survenus dans un même accident. C'est une variable stochastique comprise entre 0 et n.

Il n'y a pas lieu de faire intervenir la fréquence d'accidents (entraînant des morts) q, car celle-ci est un des éléments constitutifs du tarif appliqué par la Cédante et la prime de réassurance est exprimée comme une fraction de la prime originale. Si celle-ci est incorrecte, trop basse ou trop élevée, l'Assureur réalise une perte ou un bénéfice et il est normal que le Réassureur suive en cela la fortune de sa Cédante. La seule question est celle d'un partage équitable de la prime perçue, bonne ou mauvaise, entre la Cédante et le Réassureur.

In this paper an attempt is made to find an answer to the question, “What is the most advantageous size for the retention limit of a risk portfolio, given the fact that a certain stability requirement is to be satisfied?”

This problem will be approached from the viewpoint of an insurer who wishes to obtain a certain degree of stability at lowest cost.

It is assumed that in his choice of reinsurance methods, the insurer restricts himself to either a surplus treaty, a stop loss treaty or a combination of both these types.

Moreover it is assumed that “stability” can be adequately measured by the variance of the risks retained for own account.

We start to consider a reinsurance policy based on the surplus system where the amount of risk in excess of a retention limit u is ceded.

By thus limiting the potential loss on each risk individually, the variance is kept at a certain level, but at the expense of an amount of premium payable to a reinsurer.

The insurer could, of course, reduce the reinsurance cost by increasing his retention but he then is bound to incur a higher variance in his portfolio, which would mean a loss of stability.

One might ask, however, whether a suitably chosen stop loss coverage could bring the variance down again to the proper level at lesser cost than the profit obtained by taking a higher retention. A reduction in reinsurance cost would then have been effected.

The question leads to an optimization problem, which in a more general setting, has been discussed by K. Borch.

The Ministry of Social Affairs and Health, being the Supervising Office of Insurance in Finland, has established a special working group to investigate the problems involved with the solvency of insurers. A report will be compiled in a near future. The capacity of risk carriers is one of the problems dealt with, and it will be preliminarily reviewed in this paper.

The problem was treated by the working group parallelly by means of

1. an empirical approach observing actual fluctuations in underwriting gains of insurers, and

2. a theoretical approach, constructing a stochastic-dynamic model and studying its behaviour, especially its sensitivity to numerous background factors.

First the methods of investigation are described and their application is then demonstrated using some numerical data. Because a comprehensive report will be published by the working group separately, only the main schedule is given. For the same reason the consideration is limited here to stochastic risks, omitting the fact that the solvency of an insurer is also jeopardized by numerous “non-stochastic” risks such as failure in investments, political interference of the authorities, mismanagement of the company, or misappropriation of its property.

Il est peu de problèmes, dans l'industrie de l'assurance, dont la solution occasionne autant de difficultés que celui consistant à fixer dans l'assurance Automobile une prime équitable du point de vue technique.

On a tenté, dans plusieurs pays, de s'attaquer à ce problème par le moyen d'un bonus progressif dont bénéficierait le souscripteur n'annonçant pas de sinistre. Cependant, tant les théoriciens que les praticiens sont très partagés sur l'opportunité de cette solution.

Certains mathématiciens et juristes repoussent catégoriquement le système du bonus et qualifient l'idée de la ristourne d'une partie de la prime à l'assuré n'ayant pas eu de sinistre comme étant contraire à la notion même de l'assurance. Lors d'un des derniers congrès internationaux d'actuaires, ce procédé aurait — avec un peu d'exagération — été défini comme suit: Le bonus est, en matière d'assurance, une renonciation organisée de l'assurance. Cette opinion est principalement défendue par certains actuaires franҁais ).

D'autres mathématiciens, cependant, sont d'avis que le bonus est une précieuse disposition permettant, sur la base des sinistres survenus, d'évaluer chaque risque individuel plus rigoureusement que si I'on renonҁait à cette pratique). Et, à leur avis, il est inopportun de ne pas faire usage de cet élément d'information.

2. “Absence de sinistres” et “Nombre de sinistres”

Normalement, les primes d'assurance dépendent d'un certain nombre de facteurs caractéristiques du risque, à l'exclusion cependant des sinistres concernant un contrat particulier.

In many risk theoretical questions a central problem is the numerical evaluation of a convolution integral and much effort has been devoted over the years to mathematical and computational aspects. The paper presented to this colloquium by O. Thorin shows the subject to be topical but the present note stems from a recent paper by H. L. Seal, “Simulation of the ruin potential of non-life insurance companies”, published in the Transactions of the Society of Actuaries, Volume XXI page 563.

In this paper, amongst other topics, Seal has presented some simulations of ruin probabilities over a finite time interval. Some years ago (Journal Institute of Actuaries Students' Society, Volume 15, 1959). I pointed out that the form of ruin probability could be expressed as a successive product of values of a distribution function. To my knowledge no one has attempted to see if this product form was capable of development and the numerical values in Seal's paper prompted me to spend a little time on the problem. In the time I had available it has not been possible to do more than experiment, but the conclusions reached may be of interest to other workers in this field. They showed that calculation is feasible but laborious. However, the knowledge that it can be done may suggest methods of improving the techniques.

Seal's first simulation example is the calculation of ruin probabilities when the distribution of the interval of time between the claims is negative exponential and the individual claim distribution is also negative exponential. Instead of following Seal's method we can determine the “gain per interval” and find that if λ is the security loading the frequency function for the gain z is

i.e. a Laplace distribution.

One of the most important properties of a distribution function is that it fits the data well enough for the decision-makers' or analysts' purposes. The statisticians' problem is to select a specific form for the distribution function and to determine its parameters from the available data. Various methods (graphical method, method of moments, maximum likelihood method) are available for that purpose.

In many real world situations a single distribution function, however, may not be appropriate over the entire range of the available data. This suggests that the underlying process changes over the range of the respective variable. This fact should be considered in curve fitting. A typical example of such a situation is given in Figure 1 representing third party liability losses for trucks.

It is interesting to speculate about the different raisons d'être (Seal [5]) for the observed discontinuity. It may be the result of out-of-court or in-court settlements or could stem from differences between bodily injury and property damages.

Il est un fait bien connu que la technique des assurances, qu'elles soient privées ou sociales, qui versent une indemnité en cas de maladie, se base premièrement sur la connaissance des fréquences et des durées moyennes de maladie, ou bien des coefficients de morbidité. Pour résoudre des problèmes particuliers, des instruments plus raffinés sont toutefois nécessaires, savoir:

a) la distribution des assurés d'après le nombre de cas dont ils ont été frappés au cours d'une année;

b) la distribution des cas d'après la durée en jours;

c) la distribution des assurés d'après les jours de maladie dont ils ont été frappés au cours d'une annèe.

Nous avons eu la possibilité d'elaborer les fiches de 44.829 travailleurs salariés (36.134 hommes et 8.695 femmes âgés de 15 à 65 ans) résidant à Rome et assurés obligatoirement auprès de l'Institut National d'assurance-maladie (Istituto Nazionale per l'assicurazione contro le malattie — INAM), et de relever les cas de maladie qui les ont frappés au cours de l'année 1960, en même temps que les durées correspondantes.).

Puisqu'il s'agit, comme on le verra, de données très détaillées, il nous a paru utile d'étudier les caractéristiques principales des trois distributions en question et les relations existant entre elles: l'exposé de certains résultats obtenus dans ce sens constitue l' objet de la présente note.

It is often found even today in Europe that for certain statistical investigations the conclusion is drawn that the extent of the available statistical data is not sufficient. Going to the root of this pretention, however, we notice that there is a want of clear conception about the extent that is in fact necessary in order that a valid conclusion may with greater probability be arrived at. This, for instance, is the case when obvious tariff reductions are shirked from by entrenching oneself behind the law of large numbers, which by its very nature can in actual practice be never accomplished in its inherent sense.

Apart from a proper understanding of the limits within which a set of statistical data may subject to certain assumptions be ascribed full measure of credence, there is further a lack of the necessary tools that would permit, on the basis of ascertainable values alone, far-reaching conclusions to be drawn or a maximum of useful information to be gathered from an investigation of which the scope is evidently not sufficient.

Credibility Theory, of which Prof. Mowbray [4] may be regarded as the initiator, was evolved in the U.S.A. about 50 years ago to fill this lacunae. The development of Credibility Theory may be considered as one of the most significant contributions of American actuarial science, and it is frankly astonishing that apart from certain specific realisations in the collective risk theory which are fairly closely related to Credibility Theory, it is only in recent years that this interesting topic has met with the required attention in Europe.

Haberman and Sung (1994) have presented a dynamic model for a defined benefit occupational pension scheme which considered two types of risk: the “contribution rate” and the “solvency” risk. The current paper, extends this work by deriving optimal funding control procedures for determining the contribution rate for the case of a stochastic model with incomplete state information, making use of the separation principle. The stochastic inputs modelled are the investment returns and the benefit outgo.

When insurance claims are governed by fat-tailed distributions considerable uncertainty about the value of the tail-index is often inescapable. In this paper, using the theory of risk aversion, a new premium principle (the power principle – analogous to the exponential principle for thin-tailed claims) is established and its properties investigated. Applied to claims arising from generalized Pareto distributions, the resultant premium is shown to be the ratio of the two largest expected claims, for which the ratio of the actual claims is an unbiased as well as a consistent estimator. Whereas thin-tailed claim premiums are determined largely by the first two moments of the claims distribution, fat-tailed claim premiums are determined by the first two extremes. The context of risk-aversion leads to a natural model for incorporating tail-index uncertainty into premiums, which nevertheless leaves the basic ratio structure unaltered. To illustrate the theory, possible ‘premiums’ for US hurricane data are examined, which utilize the consistent pattern of observed extremes.

We present novel cross-sectional and longitudinal claim count models for vehicle insurance built upon the combinedd actuarial neural network (CANN) framework proposed by Wüthrich and Merz. The CANN approach combines a classical actuarial model, such as a generalized linear model, with a neural network. This blending of models results in a two-component model comprising a classical regression model and a neural network part. The CANN model leverages the strengths of both components, providing a solid foundation and interpretability from the classical model while harnessing the flexibility and capacity to capture intricate relationships and interactions offered by the neural network. In our proposed models, we use well-known log-linear claim count regression models for the classical regression part and a multilayer perceptron (MLP) for the neural network part. The MLP part is used to process telematics car driving data given as a vector characterizing the driving behavior of each insured driver. In addition to the Poisson and negative binomial distributions for cross-sectional data, we propose a procedure for training our CANN model with a multivariate negative binomial specification. By doing so, we introduce a longitudinal model that accounts for the dependence between contracts from the same insured. Our results reveal that the CANN models exhibit superior performance compared to log-linear models that rely on manually engineered telematics features.

This paper provides a method to assess the risk relief deriving from a foreign expansion by a life insurance company. We build a parsimonious continuous-time model for longevity risk that captures the dependence across different ages in domestic versus foreign populations. We calibrate the model to portray the case of a UK annuity portfolio expanding internationally toward Italian policyholders. The longevity risk diversification benefits of an international expansion are sizable, in particular when interest rates are low. The benefits are judged based on traditional measures, such as the Risk Margin or volatility reduction, and on a novel measure, the Diversification Index.

A practical method is developed for computing moments of insurance functions when interest rates are assumed to follow an autoregressive integrated moving average process.

Consider the set of functions

Obviously, π1(x) represents the net premium of the excess cover over the priority x, and the variance thereof.

If a distribution function F(x) = 1 − π0(x) is given, the set (1) can be generated by means of the recursion formulae

Let us study the special class of d.fs. F(x) which satisfy

where

If these conditions are met, the integrals (1) have the solution:

Aj(y) and Bj(y), respectively, are polynomials of rank jk and jk − 1. Their coefficients are determined by the equations:

The system (5) is obtained by differentiation of (4) with respect to y, and observing (2).