Reinsurance Contracts Research Articles

Robust reinsurance contracts with risk constraint

ABSTRACTThis paper aims to investigate optimal reinsurance contracts in a continuous-time modelling framework from the perspective of a principal-agent problem. The reinsurer plays the role of the principal and aims to determine an optimal reinsurance premium to maximize the expected utility on terminal wealth. It is supposed that the reinsurer faces ambiguity about the insurance claim process. The insurer acts as the agent whose objective is to determine an optimal retention level in a proportional reinsurance to maximize the expected utility on terminal wealth. It is postulated that the insurer is subject to a dynamic Value-at-Risk constraint, which may be attributed to capital requirements specified by Solvency II. The Hamilton-Jacobi-Bellman (HJB) dynamic programming is adopted to discuss the optimization problems of the reinsurer and insurer. Explicit expressions for the optimal solutions of the problems are obtained in the case of exponential utility functions. Numerical examples are provided to illustrate economic intuition and insights.

Optimal excess-of-loss reinsurance contract with ambiguity aversion in the principal-agent model

ABSTRACTWe discuss an optimal excess-of-loss reinsurance contract in a continuous-time principal-agent framework where the surplus of the insurer (agent/he) is described by a classical Cramér-Lundberg (C-L) model. In addition to reinsurance, the insurer and the reinsurer (principal/she) are both allowed to invest their surpluses into a financial market containing one risk-free asset (e.g. a short-rate account) and one risky asset (e.g. a market index). In this paper, the insurer and the reinsurer are ambiguity averse and have specific modeling risk aversion preferences for the insurance claims (this relates to the jump term in the stochastic models) and the financial market's risk (this encompasses the models' diffusion term). The reinsurer designs a reinsurance contract that maximizes the exponential utility of her terminal wealth under a worst-case scenario which depends on the retention level of the insurer. By employing the dynamic programming approach, we derive the optimal robust reinsurance contract, and the value functions for the reinsurer and the insurer under this contract. In order to provide a more explicit reinsurance contract and to facilitate our quantitative analysis, we discuss the case when the claims follow an exponential distribution; it is then possible to show explicitly the impact of ambiguity aversion on the optimal reinsurance.

Nonlinearly transformed risk measures: properties and application to optimal reinsurance

ABSTRACTWe propose the novel class of nonlinearly transformed risk measures (NTRMs) and apply them to the standard reinsurance problem in which an insurant seeks the risk-minimizing reinsurance contract. NTRMs transform both the outcomes and the probabilities of the insurant's uncertain final wealth by means of nonlinear functions. We prove relevant properties of NTRMs and show that they include popular Conditional Value-at-Risk (CVaR), Weighted Expected Shortfall (WES), Tail Nonlinearly Transformed Risk Measure (TNT), and Disutility Based Risk Measure (DBRM) as special cases. Regarding the reinsurance problem, we show that, under NTRMs, the optimal contract is of stop-loss type. We determine the optimal deductibles and provide comparative statics with respect to the insurant's risk aversion and initial wealth. Regarding comparative risk aversion, we show that the recently proposed WES, TNT, and DBRM help to overcome the restrictive all-or-nothing reinsurance decisions that prevail under CVaR. We further address the comparative statics with respect to initial wealth and show that under CVaR as well as WES and TNT, initial wealth is irrelevant: increasing initial wealth does not alter the optimal deductible. We show that NTRMs are able to overcome this shortcoming when the nonlinear transformation function of the outcomes is appropriately chosen.

Transform approach for discounted aggregate claims in a risk model with descendant claims

We consider a risk model with three types of claims: ordinary, leading, and descendant claims. We derive an expression for the Laplace–Stieltjes transform of the distribution of the discounted aggregate claims. By using this expression, we can then obtain the mean and variance of the discounted aggregate claims. For actuarial applications, the VaR and CTE are computed by numerical inversion of the Laplace transforms for the tail probability and the conditional tail expectation of the discounted aggregate claims. The net premium for stop-loss reinsurance contract is also computed.

Optimal dynamic reinsurance policies under a generalized Denneberg’s absolute deviation principle

This paper studies the optimal dynamic reinsurance policy for an insurance company whose surplus is modeled by the diffusion approximation of the classical Cramér–Lundberg model. We assume the reinsurance premium is calculated according to a proposed Mean-CVaR premium principle which generalizes Denneberg’s absolute deviation principle and expected value principle. Moreover, we require that both ceded loss and retention functions are non-decreasing to rule out moral hazard. Under the objective of minimizing the ruin probability, we obtain the optimal reinsurance policy explicitly and we denote the resulting treaty as the dual excess-of-loss reinsurance. This form of the optimal treaty is new to the literature and lends support to the fact that reinsurance contracts in practice often involve layers. It also demonstrates that reinsurance treaties such as the proportional and the standard excess-of-loss, which are typically found to be optimal in the dynamic reinsurance model, need not be optimal when we consider a more general optimization model. We also consider other generalizations including (i) allowing the insurer to manage its business through both reinsurance and investment; and (ii) N-piecewise Mean-CVaR premium principle. In the former case, we not only show that the dual excess-of-loss reinsurance policy remains optimal, but also demonstrate that investing in stock can further enhance insurer’s financial stability with lower ruin probability. For the latter case, we establish that the optimal reinsurance treaty can have at most N layers, which is also more consistent with practice.

On the existence of a representative reinsurer under heterogeneous beliefs

This paper studies a one-period optimal reinsurance design model with n reinsurers and an insurer. The reinsurers are endowed with expected-value premium principles and with heterogeneous beliefs regarding the underlying distribution of the insurer’s risk. Under general preferences for the insurer, a representative reinsurer is characterized. This means that all reinsurers can be treated collectively by means of a hypothetical premium principle in order to determine the optimal total risk that is ceded to all reinsurers. The optimal total ceded risk is then allocated to the reinsurers by means of an explicit solution. This is shown both in the general case and under the no-sabotage condition that avoids possible ex post moral hazard on the side of the insurer, thereby extending the results of Boonen et al. (2016). We subsequently derive closed-form optimal reinsurance contracts in case the insurer maximizes expected net wealth. Moreover, under the no-sabotage condition, we derive optimal reinsurance contracts in case the insurer maximizes dual utility, or in case the insurer maximizes a generic objective that preserves second-order stochastic dominance under the assumption of a monotone hazard ratio.

Dynamic Set-Up for Designing Optimal Reinsurance Contracts

In this paper, we consider a dynamic set-up for designing optimal reinsurance contracts. The main objective is to maximise the lifetime dividends of an insurance company. We study three problems. First, we consider a general dividend maximisation problem with just budget constraints; second, we add solvency conditions to the previous problem; and finally, we consider a problem with solvency constraints and a particular type of dividend functions. We show that the optimal solutions of the first and second problems do not evolve over time and can be found by solving a static problem, whereas the third problem's optimal solution evolves over time and depends on the problem specification and the state variables. We find the dual problem of the third problem and show that the optimal reinsurance contract always has a multilayer structure. Last, we consider some examples and show that in many cases, the contract is indeed a two-layer policy.

Reinsurance premium principles based on weighted loss functions

ABSTRACTIn this paper, we propose new reinsurance premium principles that minimize the expected weighted loss functions and balance the trade-off between the reinsurer's shortfall risk and the insurer's risk exposure in a reinsurance contract. Random weighting factors are introduced in the weighted loss functions so that weighting factors are based on the underlying insurance risks. The resulting reinsurance premiums depend on both the loss covered by the reinsurer and the loss retained by the insurer. The proposed premiums provide new ways for pricing reinsurance contracts and controlling the risks of both the reinsurer and the insurer. As applications of the proposed principles, the modified expectile reinsurance principle and the modified quantile reinsurance principle are introduced and discussed in details. The properties of the new reinsurance premium principles are investigated. Finally, the comparisons between the new reinsurance premium principles and the classical expectile principle, the classical quantile principle, and the risk-adjusted principle are provided.

Stochastic differential reinsurance games with capital injections

This paper investigates a class of reinsurance game problems between two insurance companies under the framework of non-zero-sum stochastic differential games. Both insurers can purchase proportional reinsurance contracts from reinsurance markets and have the option of conducting capital injections. We assume the reinsurance premium is calculated under the generalized variance premium principle. The objective of each insurer is to maximize the expected value that synthesizes the discounted utility of his surplus relative to a reference point, the penalties caused by his own capital injection interventions, and the gains brought by capital injections of his competitor. We prove the verification theorem and derive explicit expressions of the Nash equilibrium strategy by solving the corresponding quasi-variational inequalities. Numerical examples are also conducted to illustrate our results.

Reinsurance contract design with adverse selection

ABSTRACTIn light of the richness of their structures in connection with practical implementation, we follow the seminal works in economics to use the principal–agent (multidimensional screening) models to study a monopolistic reinsurance market with adverse selection; instead of adopting the classical expected utility paradigm, the novelty of our present work is to model the risk assessment of each insurer (agent) by his value-at-risk at his own chosen risk tolerance level consistent with Solvency II. Under information asymmetry, the reinsurer (principal) aims to maximize his average profit by designing an optimal policy provision (menu) of ‘shirt-fit’ reinsurance contracts for every insurer from one of the two groups with hidden characteristics. Our results show that a quota-share component, on the top of simple stop-loss, is very crucial for mitigating asymmetric information from the insurers to the reinsurer.

Optimal reinsurance contracts under the reinsurer’s risk constraint with VaR risk measures

Most researchers in insurance field have not been considering the reinsurer’s risk. Theoretically, the quantity of reinsurer’s risk is not limited. However, in the real-world insurance industry, reinsurer always put a limit on coverage, otherwise the reinsurer will experience a heavy financial burden when the insurer bears an unexpected large loss. In this paper, we review the optimal reinsurance problem under VaR risk measures framework when the limitation for reinsurer’s risk exposure are limited by a constant. By analyzing the VaR of the insurer’s total risk exposure, optimality can be fulfilled and end up in obtaining the expected reinsurance policy. Through the study, it is reveal that the stop-loss reinsurance with a policy limit is constantly the optimal reinsurance policy under VaR risk measures. Determination of optimal quantity of ceded risk depends on the confidence level, the safety loading and the limitation of the constant. A numerical analysis on company claims data is carried out in order to find the optimal ceded loss function.

Reinsurance contract design when the insurer is ambiguity-averse

This paper investigates proportional and excess-loss reinsurance contracts in a continuous-time principal–agent framework, in which the insurer is the agent and the reinsurer is the principal. Insurance claims follow the classic Cramér–Lundberg process. The insurer believes that the claim intensity is uncertain and he chooses robust risk retention levels to maximize the penalty-dependent multiple-priors utility. The reinsurer designs reinsurance contracts subject to the insurer’s incentive compatibility constraints. The analytical expressions of the two robust reinsurance contracts are derived. Our results show that the robust reinsurance demand and price are greater than their respective standard values without model ambiguity, and increase as the insurer’s ambiguity aversion increases. Moreover, the reinsurer specifies a decreasing reinsurance price to induce increasing demand over time. Specifically, the price of excess-loss reinsurance is higher, relative to that of proportional reinsurance. Further, only if the insurer’s risk aversion is high or the reinsurer’s risk aversion is low, the insurer prefers the excess-loss reinsurance contract.

Exposure Modelling in Property Reinsurance

Exposure curves play significant role in modelling of property per risk excess of loss non-proportional reinsurance contracts, especially in the situations when not enough historical data is available for applying experience-based methods or if the underlying exposure changed significantly. The paper deals only with the first loss scale (FLS) approach which is frequently used in Europe. An alternative approach is based on ISO´s PSOLD methodology which is typical for the U.S. The first research into FLS approach was done by Ruth E. Salzmann in 1963 and some further curves have been developed since that time, however, their availability is limited. According to the authors´ knowledge only limited number of articles were published on this topic and no comprehensive publication which would describe the methodology to a larger extent exists. The paper provides a comprehensive description of the FLS exposure rating methodology, aims to summarise both historical and latest developments in this area and also includes various authors´ own practical considerations. The theory is illustrated on numerical examples.

Dynamic risk-sharing game and reinsurance contract design

This paper studies the optimal risk-sharing between an insurer and a reinsurer. The insurer purchases reinsurance for risk-control and decides her retention level with an objective to minimize her ruin probability. The reinsurer has control over the reinsurance price and aims to maximize her expected discounted profits up to the time when the insurer goes bankrupt. In a stochastic differential game-theoretic framework, we determine the insurer’s optimal reinsurance strategy and specify the reinsurance contract by solving a system of coupled Hamilton–Jacobi–Bellman equations. We obtain explicit solutions for the game problem when both the insurance and the reinsurance premiums are calculated according to the standard-deviation principle or the expected value principle, respectively. Our results show that, depending on the model parameters, the reinsurance contract is either provided with a peak price when the insurer has sufficient cash reserve and with a minimum price when otherwise, or is always provided with a peak price. We also perform some numerical analyses and provide economic interpretations for the results.

Golden options in financial mathematics

This paper deals with the construction of “smooth good deals” (SGD), i.e., sequences of self-financing strategies whose global risk diverges to minus infinity and such that every security in every strategy of the sequence is a “smooth” derivative with a bounded delta. Since delta is bounded, digital options are excluded. In fact, the pay-off of every option in the sequence is continuos (and therefore jump-free) with respect to the underlying asset price. If the selected risk measure is the value at risk, then these sequences exist under quite weak conditions, since one can involve risks with both bounded and unbounded expectation, as well as non-friction-free pricing rules. Moreover, every strategy in the sequence is composed of a short European option plus a position in a riskless asset. If the chosen risk measure is a coherent one, then the general setting is more limited. Indeed, though frictions are still accepted, expectations and variances must remain finite. The existence of SGDs will be characterized, and computational issues will be properly addressed. It will be shown that SGDs often exist, and for the conditional value at risk, they are composed of the riskless asset plus easily replicable short European puts. The ideas presented may also apply in some actuarial problems such as the selection of an optimal reinsurance contract.

On optimal reinsurance treaties in cooperative game under heterogeneous beliefs

In this paper, we study the optimal reinsurance policies as the result of a two-person cooperative game. We assume that both the insurer and the reinsurer are risk averse and expected-utility maximizers. In addition, we assume that they “agree to disagree” on the distribution of the underlying losses in the contract negotiation.In our analysis, we consider two scenarios. In the first one, the reinsurance premium is fully negotiable, whereas in the second one, the premium is determined by the reinsurer using the expected value premium principle. For both scenarios, we first derive the set of Pareto-optimal reinsurance contracts and then identify the reinsurance contract corresponding to the Nash bargaining solution as well as that corresponding to the Kalai–Smorodinsky bargaining solution.

A Reinsurance Approach in a Two-Dimensional Model with Dependent Risks

We consider an insurer having two classes of insurance risks dependent through the number of claims of each risk in a given period of time. We assume that the insurer chooses a reinsurance strategy related to the first class of risk by means a proportional reinsurance contract; we also assume that the reinsurance strategy related to the second class of risk is of Excess of Loss reinsurance type. Within this paper, we study the possible optimal couples of proportional retention level and Excess of Loss retention limit.

Analytic Expressions for Multivariate Lorenz Surfaces

The Lorenz curve is a much used instrument in economic analysis. It is typically used for measuring inequality and concentration. In insurance, it is used to compare the riskiness of portfolios, to order reinsurance contracts and to summarize relativity scores (see Frees et al. J. Am. Statist. Assoc.106, 1085–1098, 2011; J. Risk Insur.81, 335–366, 2014 and Samanthi et al. Insur. Math. Econ.68, 84–91, 2016). It is sometimes called a concentration curve and, with this designation, it attracted the attention of Mahalanobis (Econometrica28, 335–351, 1960) in his well known paper on fractile graphical analysis. The extension of the Lorenz curve to higher dimensions is not a simple task. There are three proposed definitions for a suitable Lorenz surface, proposed by Taguchi (Ann. Inst. Statist. Math.24, 355–382, 1972a, 599–619, 1972b; Comput. Stat. Data Anal.6, 307–334, 1988) and Lunetta (1972), Arnold (1987, 2015) and Koshevoy and Mosler (J. Am. Statist. Assoc.91, 873–882, 1996). In this paper, using the definition proposed by Arnold (1987, 2015), we obtain analytic expressions for many multivariate Lorenz surfaces. We consider two general classes of models. The first is based on mixtures of Lorenz surfaces and the second one is based on some simple classes of bivariate mixture distributions.

On randomized reinsurance contracts

In this paper we discuss the potential of randomizing reinsurance treaties for efficient risk management. While it may be considered counter-intuitive to introduce additional external randomness in the determination of the retention function for a given occurred loss, we indicate why and to what extent randomizing a treaty can be interesting for the insurer. We illustrate the approach with a detailed analysis of the effects of randomizing a stop-loss treaty on the expected profit after reinsurance in the framework of a one-year reinsurance model under regulatory solvency constraints and cost of capital considerations.

On Optimal Reinsurance Treaties in Cooperative Game under Heterogeneous Beliefs

In this paper, we study the optimal reinsurance policies as the result of a two-person cooperative game, where both parties in the negotiation are risk averse and are trying to maximize their expected utility. We incorporate information asymmetry by assuming that the insurer and the re-insurer have different beliefs on the distribution of the underlying losses. Our analysis consists of two parts. The first part deals with the situation when the reinsurance premium is fully negotiable; whereas the second part deals with the situation when the premium is determined by an actuarial premium principle. For both parts, we first derive the Pareto-optimal reinsurance contracts, then the reinsurance contracts in the Nash equilibrium as well as in the Kalai-Smorodinsky equilibrium are identified.