Re-insurance

This paper shows how problems in 'non-life'-(re)insurance can be modeled as cooperative games with stochastic payoffs. Pareto optimal allocations of the risks faced by the insurers and the insureds are determined. It is shown that the core of the corresponding insurance games is nonempty. Moreover, it is shown that specific core allocations are obtained when the zero-utility principle is used for calculating premiums. Finally, game theory is used to give a justification for subadditive premiums.

In this paper we study the effect of network structure between agents and objects on measures for systemic risk. We model the influence of sharing large exogeneous losses to the financial or (re)insuance market by a bipartite graph. Using Pareto-tailed losses and multivariate regular variation we obtain asymptotic results for systemic conditional risk measures based on the Value-at-Risk and the Conditional Tail Expectation. These results allow us to assess the influence of an individual institution on the systemic or market risk and vice versa through a collection of conditional systemic risk measures. For large markets Poisson approximations of the relevant constants are provided in the example of an insurance market. The example of an underlying homogeneous random graph is analysed in detail, and the results are illustrated through simulations.

We model the influence of sharing large exogeneous losses to the reinsurance market by a bipartite graph. Using Pareto-tailed claims and multivariate regular variation we obtain asymptotic results for the Value-at-Risk and the Conditional Tail Expectation. We show that the dependence on the network structure plays a fundamental role in their asymptotic behaviour. As is well-known in a non-network setting, if the Pareto exponent is larger than 1, then for the individual agent (reinsurance company) diversification is beneficial, whereas when it is less than 1, concentration on a few objects is the better strategy. An additional aspect of this paper is the amount of uninsured losses which have to be convered by society. In the situation of networks of agents, in our setting diversification is never detrimental concerning the amount of uninsured losses. If the Pareto-tailed claims have finite mean, diversification turns out to be never detrimental, both for society and for individual agents. In contrast, if the Pareto-tailed claims have infinite mean, a conflicting situation may arise between the incentives of individual agents and the interest of some regulator to keep risk for society small. We explain the influence of the network structure on diversification effects in different network scenarios.

We model business relationships exemplified for a (re)insurance market by a bipartite graph which determines the sharing of severe losses. Using Pareto-tailed claims and multivariate regular variation we obtain asymptotic results for the Value-at-Risk and the Conditional Tail Expectation. We show that the dependence on the network structure plays a fundamental role in their asymptotic behaviour. As is well-known, if the Pareto exponent is larger than 1, then for the individual agent (re-insurance company) diversification is beneficial, whereas when it is less than 1, concentration on a few objects is the better strategy. The situation changes, however, when systemic risk comes into play. The random network structure has a strong influence on diversification effects, which destroys this simple individual agent's diversification rule. It turns out that diversification is always beneficial from a macro-prudential point of view creating a conflicting situation between the incentives of individual agents and the interest of some superior entity to keep overall risk small. We explain the influence of the network structure on diversification effects in different network scenarios.

In earthquake and tsunami risk-prone regions such as Chile, catastrophe models help insurers and reinsurers understand and quantify the potential financial losses caused by these perils. The 2010 Maule earthquake highlighted the need for quantifying losses not only from primary perils (earthquake) but also from secondary perils such as tsunamis, which contribute to the overall event losses but are not often modelled. This paper describes the methodology and application behind a new earthquake and tsunami catastrophe model for Chile developed by Impact Forecasting in collaboration with its Aon Benfield Research partners. The Chile earthquake and tsunami model is validated through comparison of the modelled and observed losses for client portfolios from the 2010 event.

In earthquake and tsunami risk-prone regions such as Chile, catastrophe models help insurers and reinsurers understand and quantify the potential financial losses caused by these perils. The 2010 Maule earthquake highlighted the need for quantifying losses not only from primary perils (earthquake) but also from secondary perils such as tsunamis, which contribute to the overall event losses but are not often modelled. This paper describes the methodology and application behind a new earthquake and tsunami catastrophe model for Chile developed by Impact Forecasting in collaboration with its Aon Benfield Research partners. The Chile earthquake and tsunami model is validated through comparison of the modelled and observed losses for client portfolios from the 2010 event.

In earthquake and tsunami risk-prone regions such as Chile, catastrophe models help insurers and reinsurers understand and quantify the potential financial losses caused by these perils. The 2010 Maule earthquake highlighted the need for quantifying losses not only from primary perils (earthquake) but also from secondary perils such as tsunamis, which contribute to the overall event losses but are not often modelled. This paper describes the methodology and application behind a new earthquake and tsunami catastrophe model for Chile developed by Impact Forecasting in collaboration with its Aon Benfield Research partners. The Chile earthquake and tsunami model is validated through comparison of the modelled and observed losses for client portfolios from the 2010 event.

William James (1919) characterises hypotheses as either live or dead. A hypothesis is live when it is taken into account as a 'real possibility'. We follow James' suggestion to not attribute intrinsic properties to hypotheses, but rather investigate how they came into being and look at the effects they generate. Expectations of digital technologies are a topic of vivid debate in the insurance industry. Before these expectations can become 'live', they have, in the first place, to be generated by market devices. We investigate how the reinsurance blogpost platform Open Minds functions as an 'expectation generation device' on the future of insurance markets. Combining Beckert's work on the role of fictional expectations with the pragmatist turn in sociology of markets, we propose to study 'expectation generation devices', provoking expectations on economic markets. In our empirical analysis, we demonstrate the explicit fictional character of the Open Minds contributions, and analyse how a contained space of openness is generated to provoke expectations. We demonstrate how Open Minds can become live through circulation to other expectation generation sites in the insurance industry and beyond. We conclude by reflecting on the importance of expectation generation devices as a particular type of market devices.

Since the nineteenth century, sociologists have studied the relationship between economic business cycles and increases in crime. According to the U.S. Chamber of Commerce, crime may be a factor in as many as 30 percent of all business failures. Despite other variables that may contribute to increases in criminal activity, the current economic recession will likely accelerate criminal activity ranging from shoplifting and robbery to fraud and embezzlement. In this paper, the researcher examines the role of prevention and detection of criminal activity and offers prevention as the most cost-effective means to reduce the impact on business.

Shapley value is a popular way to compute payoffs in cooperative games where the agents are assumed to have deterministic, risk-neutral (linear) utilities.This paper explores a class of Multi-agent constantsum cooperative games where the payoffs are random variables. We introduce a new model based on Borch’s Theorem from the actuarial world of re-insurance, to obtain a Pareto optimal allocation for agents with riskaverse exponential utilities. This allocation problem seeks to maximize a linear sum of the expected utilities of a set of agents and the solution obtained at this optimal value naturally maximizes the social welfare of the grand coalition. The four main axioms of the Shapely Value, namely, nullity, additivity, symmetry and efficiency are satisfied by this solution. We show the correspondence of our solution to the Shapley value. As a result we can directly obtain the Shapley value from the allocation values obtained at the Pareto optimum as the individual utility achievem...

Since the nineteenth century, sociologists have studied the relationship between economic business cycles and increases in crime. According to the U.S. Chamber of Commerce, crime may be a factor in as many as 30 percent of all business failures. Despite other variables that may contribute to increases in criminal activity, the current economic recession will likely accelerate criminal activity ranging from shoplifting and robbery to fraud and embezzlement. In this paper, the researcher examines the role of prevention and detection of criminal activity and offers prevention as the most cost-effective means to reduce the impact on business.

William James (1919) characterises hypotheses as either live or dead. A hypothesis is live when it is taken into account as a 'real possibility'. We follow James' suggestion to not attribute intrinsic properties to hypotheses, but rather investigate how they came into being and look at the effects they generate. Expectations of digital technologies are a topic of vivid debate in the insurance industry. Before these expectations can become 'live', they have, in the first place, to be generated by market devices. We investigate how the reinsurance blogpost platform Open Minds functions as an 'expectation generation device' on the future of insurance markets. Combining Beckert's work on the role of fictional expectations with the pragmatist turn in sociology of markets, we propose to study 'expectation generation devices', provoking expectations on economic markets. In our empirical analysis, we demonstrate the explicit fictional character of the Open Minds contributions, and analyse how a contained space of openness is generated to provoke expectations. We demonstrate how Open Minds can become live through circulation to other expectation generation sites in the insurance industry and beyond. We conclude by reflecting on the importance of expectation generation devices as a particular type of market devices.

In this paper, we discuss how access to health-related data by private insurers, other than affecting the interests of prospective policy-holders, can also influence their propensity to make personal data available for research purposes. We take the case of national precision medicine initiatives as an illustrative example of this possible tendency. Precision medicine pools together unprecedented amounts of genetic as well as phenotypic data. The possibility that private insurers could claim access to such rapidly accumulating biomedical Big Data or to health-related information derived from it would discourage people from enrolling in precision medicine studies. Should that be the case, the economic value of personal data for the insurance industry would end up affecting the public value of data as a scientific resource. In what follows we articulate three principles – trustworthiness, openness and evidence – to address this problem and tame its potentially harmful effects on the d...

Advances in genomics and postgenomics have renewed interest in the impact of genomic health information on private life insurance across Europe. These developments reopen the issue of how genes – apart from being the object of discrimination (exclusion) – also operate as generators of solidarity (inclusion). This article traces several developments in regulating genetics and life insurance and its social implications in the European context. At first, genes were viewed as a source of differentiation, which led to fears of ‘genetic discrimination’ in life insurance. In response, genetic nondiscrimination regulations were enacted across Europe. Current debates on the use of genomic health information in life insurance have actually opened up possibilities for a form of genomic solidarity between ‘all of us’. The introduction of genes and genomes appears to turn private life insurance practices of actuarial risk discrimination increasingly into ‘discriminatory’ practices by challenging...

An online business organization spends millions of dollars on firewalls, anti-virus, intrusion detection systems, digital signature, and encryption, to ensure minimal security breach. Nonetheless, a new virus or a clever hacker can easily compromise these deterrents, resulting in losses to the tune of millions of dollars annually. To minimize the financial loss, we propose that online businesses should invest in e-risk insurance products as a complementary alternative, above the network security appliances. In this work, we develop a Copula aided Bayesian Belief Network (CBBN) model, to assist insurance companies to design e-insurance products. The CBBN model does an e-vulnerability assessment (e-VA) and e-risk quantification (e-RQ). We first draw a casual diagram (BBN) stating the probable reason for security failure in an organization. We assume the marginal distributions for each of the nodes of the

Security breaches deter e-commerce activities. Organizations spend millions of dollars on security appliances to make online transactions more secure. Nonetheless, a new virus or a clever hacker can easily compromise these deterrents and cause losses of millions of dollars annually. To reduce the impact of such losses, e-risk insurance is a viable complement to the security devices. Currently, e-risk insurance is in its developmental stage and small claim coverage is only available. In this paper, we provide a framework, for insurance companies to duly accept large e-risk. Splitting a large risk across layers reduces the overall variance of the loss. Also in case of a contingency the loss indemnification is shared. The inputs to the proposed model are the risk transfer proportion, overloading for premium, expected return on capital and undistributed risk at each layer. The model outputs the optimal number of layers in which the risk needs to be spilt by the insurance company and the interlayer relationships.

We provide necessary and sufficient conditions for optimality of mutual contracts for risk sharing under constraints on premiums or utility functions of participants of the agreement. These conditions are an extension of those of the Borch, Gerber and Bühlmann-Jewell ones. Some applications to optimal insurance contracts, optimal dividend sharing and optimal reinsurance are given.

This article addresses the reliance on genetic information as part of the private insurance industry’s practice of risk segmentation whereby underwritingdecisions are based on risk information about individuals and groups as compared to the general population. The author argues that there are a number of concerns regarding reliance on genetic information in insurance underwriting, including uncertainty about what constitutes genetic information and the predictive value thereof, possible conflicts with human rights values, potential reductions in access to insurance, and the legal and ethical obligations of individuals who undergo testing, health professionals, and insurers. This article reviews the solutions that have been adopted in other jurisdictions and concludes that the use of genetic information is consistent with standard insurance industry practices. However, it is recommended that a legislative framework be established in Canada to regulate the use of genetic information.

We provide necessary and sufficient conditions for optimality of mutual contracts for risk sharing under constraints on premiums or utility functions of participants of the agreement. These conditions are an extension of those of the Borch, Gerber and Bühlmann-Jewell ones. Some applications to optimal insurance contracts, optimal dividend sharing and optimal reinsurance are given.

We provide necessary and sufficient conditions for optimality of mutual contracts for risk sharing under constraints on premiums or utility functions of participants of the agreement. These conditions are an extension of those of the Borch, Gerber and Bühlmann-Jewell ones. Some applications to optimal insurance contracts, optimal dividend sharing and optimal reinsurance are given.

This paper investigates a mixed regular-singular stochastic control problem where the drift of the dynamics is quadratic in the regular control variable. More importantly, the regular control variable is constrained. The value function of the problem is derived in closed form via solving the corresponding constrained Hamilton-Jacobi-Bellman equation, and optimal controls are obtained explicitly. Applications and economic interpretations of the general results to two applied problems, from which the mathematical problem was originated, are discussed.

We consider a model of a corporation, which can choose a production/business policy among an available set of control policies with different expected profits and associated risks. In addition, there is a choice of the amount of dividends to be paid out to the shareholders. Notwithstanding any policy decision there is a constant payment of a corporate debt, such as bond liability or loan amortization. The objective is to find the policy which maximizes the expected total discounted dividend pay-outs until the time of bankruptcy. We model the dynamics of the corporate assets as a diffusion process with the diffusion and drift coefficients being affine functions of the risk control variable. In other words, the potential profit in our model is proportional to risk. The cumulative dividends are modeled by an increasing process. The resulting problem becomes a mixed regular-singular control problem for diffusion processes. We show that there exists an optimal level bl such that the optimal dividend policy is to keep the company's wealth below bL and pay out as dividends all the amounts in excess of this level, On the other hand, the profit/risk control policy depends on the ratio of the maximal possible expected profit to the liability payments. When this ratio is small, the optimal policy is always to undertake the maximal risk. When this ratio is large, the risk depends on the current amount of the company's wealth. The risk as a function of the wealth is monotone and increasing, reaching its maximum at some b0 < bl.

This paper shows how problems in 'non-life'-(re)insurance can be modeled as cooperative games with stochastic payoffs. Pareto optimal allocations of the risks faced by the insurers and the insureds are determined. It is shown that the core of the corresponding insurance games is nonempty. Moreover, it is shown that specific core allocations are obtained when the zero-utility principle is used for calculating premiums. Finally, game theory is used to give a justification for subadditive premiums.

With the development and increasing accessibility of new genomic tools such as next-generation sequencing, genome-wide association studies, and genomic stratification models, the debate on genetic discrimination in the context of life insurance became even more complex, requiring a review of current practices and the exploration of new scenarios. In this perspective, a multidisciplinary group of international experts representing different interests revisited the genetics and life insurance debate during a 2-day symposium 'Life insurance: breast cancer research and genetic risk prediction seminar' held in Quebec City, Canada on 24 and 25 September 2012. Having reviewed the current legal, social, and ethical issues on the use of genomic information in the context of life insurance, the Expert Group identified four main questions: (1) Have recent developments in genomics and related sciences changed the contours of the genetics and life insurance debate? (2) Are genomic results obtained in a research context relevant for life insurance underwriting? (3) Should predictive risk assessment and risk stratification models based on genomic data also be used for life insurance underwriting? (4) What positive actions could stakeholders in the debate take to alleviate concerns over the use of genomic information by life insurance underwriters? This paper presents a summary of the discussions and the specific action items recommended by the Expert Group.

Public concern about genetic discrimination, particularly access to insurance following genetic testing, has been reported in the literature. This paper aims to separate myths from realities regarding genetic discrimination in life insurance and to underline the positive aspects of allowing insurers access to relevant genetic information for underwriting purposes. We present a review of the literature pertinent to discrimination in life insurance and a comparative analysis of industries guidelines. There are few reported cases in the literature of validated genetic discrimination. However, the benefits to be gained by allowing insurers access to relevant genetic data could justify fostering a more active role in the use of genetic information by insurance companies.

Public concern about genetic discrimination, particularly access to insurance following genetic testing, has been reported in the literature. This paper aims to separate myths from realities regarding genetic discrimination in life insurance and to underline the positive aspects of allowing insurers access to relevant genetic information for underwriting purposes. We present a review of the literature pertinent to discrimination in life insurance and a comparative analysis of industries guidelines. There are few reported cases in the literature of validated genetic discrimination. However, the benefits to be gained by allowing insurers access to relevant genetic data could justify fostering a more active role in the use of genetic information by insurance companies.

Abstract Public concern about genetic discrimination, particularly access to insurance following genetic testing, has been reported in the literature. This paper aims to separate myths from realities regarding genetic discrimination in life insurance and to underline the positive aspects of allowing insurers access to relevant genetic information for underwriting purposes. We present a review of the literature pertinent to discrimination in life insurance and a comparative analysis of industries guidelines.

One of the most contentious topics in public policy debates on genetics has been the use of genetic information by private insurance companies. Confronted with legislation prohibiting the use of genetics in private insurance, the insurance industry has been prompted to deal ...

This article offers an analysis of the way private insurers deal with the issue of genetics and insurance. Drawing on specific written insurance sources, a reconstruction is made of internal debates on genetics and insurance within the private insurance world in Europe and the United States. The article starts by analyzing the way insurers initially framed the issue of genetics. It proceeds by showing how ideas with respect to this issue developed beyond public policy debates in the nineties. Although not a strictly linear development, a trend towards a change in perspective can be demonstrated: at the beginning most insurance companies took another stance than they do nowadays. The article concludes by questioning the effect of these changes within the insurance world for the definition of the problem with respect to genetics and insurance. Does taking into account the public concerns around genetics also include taking genetics as a public problem?