Longitudinal modeling of insurance claim counts using jitters

Modeling insurance claim counts is a critical component in the ratemaking process for property and casualty insurance. This article explores the usefulness of copulas to model the number of insurance claims for an individual policyholder within a longitudinal context. To address the limitations of copulas commonly attributed to multivariate discrete data, we adopt a ‘jittering’ method to the claim counts which has the effect of continuitizing the data. Elliptical copulas are proposed to accommodate the intertemporal nature of the ‘jittered’ claim counts and the unobservable subject-specific heterogeneity on the frequency of claims. Observable subject-specific effects are accounted in the model by using available covariate information through a regression model. The predictive distribution together with the corresponding credibility of claim frequency can be derived from the model for ratemaking and risk classification purposes. For empirical illustration, we analyze an unbalanced longitudinal dataset of claim counts observed from a portfolio of automobile insurance policies of a general insurer in Singapore. We further establish the validity of the calibrated copula model, and demonstrate that the copula with ‘jittering’ method outperforms standard count regression models.     

Optimal insurance in the presence of reinsurance

This paper studies an optimal insurance and reinsurance design problem among three agents: policyholder, insurer, and reinsurer. We assume that the preferences of the parties are given by distortion risk measures, which are equivalent to dual utilities. By maximizing the dual utility of the insurer and jointly solving the optimal insurance and reinsurance contracts, it is found that a layering insurance is optimal, with every layer being borne by one of the three agents. We also show that reinsurance encourages more insurance, and is welfare improving for the economy. Furthermore, it is optimal for the insurer to charge the maximum acceptable insurance premium to the policyholder. This paper also considers three other variants of the optimal insurance/reinsurance models. The first two variants impose a limit on the reinsurance premium so as to prevent insurer to reinsure all its risk. An optimal solution is still layering insurance, though the insurer will have to retain higher risk. Finally, we study the effect of competition by permitting the policyholder to insure its risk with an insurer, a reinsurer, or both. The competition from the reinsurer dampens the price at which an insurer could charge to the policyholder, although the optimal indemnities remain the same as the baseline model. The reinsurer will however not trade with the policyholder in this optimal solution.     

Optimal Insurance Under Random Auditing

We provide a characterization of an optimal insurance contract (coverage schedule and audit policy) when the monitoring procedure is random. When the policyholder exhibits constant absolute risk aversion, the optimal contract involves a positive indemnity payment with a deductible when the magnitude of damages exceeds a threshold. In such a case, marginal damages are fully covered if the claim is verified. Otherwise, there is an additional deductible that disappears when the damages become infinitely large. Under decreasing absolute risk aversion, providing a positive indemnity payment for small claims with a nonmonotonic coverage schedule may be optimal.     

On the Lack of Participating Policy Usage by Stock Insurance Companies

Stock insurers can reduce or eliminate agency conflicts between policyholders and stockholders by issuing participating insurance. Despite this benefit, most stock companies don't offer participating contracts. This study explains why. We study an equilibrium with both stock and mutual insurers in which stockholders set premiums to provide a fair expected return on their investment, and with a policyholder who chooses the insurance contract that maximizes her expected utility. We demonstrate that stockholders cannot profitably offer fully participating contracts, but can profitably offer partially participating insurance. However, when the policyholder participation fraction is high, the fair‐return premium is so large that the policyholder always prefers fully participating insurance from the mutual company. Policies with lower levels of policyholder participation are optimal for policyholders with relatively high risk aversion, though such policies are usually prohibited by insurance legislation. Thus, the reason stock insurers rarely issue participating contracts isn't because the potential benefits are small or unimportant. Rather, profitability or regulatory constraints simply prevent stock insurers from exercising those benefits in equilibrium.     

保险市场逆向选择的信号传递博弈研究

在保险市场中,投保人比保险人更了解自己的风险状况,保险双方之间的这种信息不对称难以避免地会产生逆向选择问题,于是在保险人混同定价的情形下,低风险投保人要承受过高的费率而受损,高风险投保人因保险成本过低而削弱控制风险的激励,导致整个市场资源配置低效甚至因逆向选择螺旋而崩溃。通过引入信号传递机制来实现保险市场的分离定价,从...     

Life insurance in a contingent claim framework: Pricing and regulatory implications

In this paper we develop a contingent claim model to evaluate the equity and liabilities of a life insurance company. The limited liability of shareholders is explicitly modelled. We focus on a specific type of life insurance policy—namely, the profit-sharing policy. In this policy, the policyholder is entitled to a guaranteed interest rate and a percentage of the company's yearly financial revenues. The implicit equilibrium interest rate and profit-sharing ratio are derived and analyzed. We finally discuss regulatory measures frequently encountered in the life insurance business such as rate ceilings, capital ratios, and asset restrictions.     

Immediate Annuity Pricing in the Presence of Unobserved Heterogeneity

Abstract

One of the acknowledged difficulties with pricing immediate annuities is that underwriting the annuitantis life is the exception rather than the rule. In the absence of underwriting, the price paid for a life-contingent annuity is the same for all sales at a given age. This exposes the market (insurance company and potential policyholder alike) to antiselection. The insurance company worries that only the healthiest people choose a life-contingent annuity and therefore adjust mortality accordingly. The potential policyholders worry that they are not being compensated for their relatively poor health and choose not to purchase what would otherwise be a very beneficial product.

This paper develops a model of underlying, unobserved health. Health is a state variable that follows a first-order Markov process. An individual reaches the state “death” either by accident from any health state or by progressively declining health state. Health state is one-dimensional, in the sense that health can either “improve” or “deteriorate” by moving farther from or close to the “death” state, respectively. The probability of death in a given year is a function of health state, not of age. Therefore, in this model a person is exactly as old as he or she feels.

I first demonstrate that a multistate, ageless Markov model can match the mortality patterns in the common annuity mortality tables. The model is extended to consider several types of mortality improvements: permanent through decreasing probability of deteriorating health, temporary through improved distribution of initial health state, and plateau through the effects of past health improvements.

I then construct an economic model of optimal policyholder behavior, assuming that the policyholder either knows his or her health state or has some limited information. the value of mortality risk transfer through purchasing a life-contingent annuity is estimated for each health state under various risk-aversion parameters. Given the economic model for optimal purchasing of annuities, the value of underwriting (limited information about policyholder health state) is demonstrated.     

Spatial modelling of claim frequency and claim size in non-life insurance

In this paper, models for claim frequency and average claim size in non-life insurance are considered. Both covariates and spatial random effects are included allowing the modelling of a spatial dependency pattern. We assume a Poisson model for the number of claims, while claim size is modelled using a Gamma distribution. However, in contrast to the usual compound Poisson model, we allow for dependencies between claim size and claim frequency. A fully Bayesian approach is followed, parameters are estimated using Markov Chain Monte Carlo (MCMC). The issue of model comparison is thoroughly addressed. Besides the deviance information criterion and the predictive model choice criterion, we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. We give an application to a comprehensive data set from a German car insurance company. The inclusion of spatial effects significantly improves the models for both claim frequency and claim size, and also leads to more accurate predictions of the total claim sizes. Further, we detect significant dependencies between the number of claims and claim size. Both spatial and number of claims effects are interpreted and quantified from an actuarial point of view.     

Grenzen der Auskunfts- und Belegpflicht in der D&O Versicherung

A large number of claims brought under German D&O insurance regard Insured vs. Insured cases, i.e. claims brought by the company against its own directors and officers (Executive Directors, Supervisory Board Members etc.). After notification of and examination by the insurer of such an insured event, the insurer will in most cases opt to grant the insured defence cover in order to fight off the claim. The insurer hereby expresses that it regards the claim of the company (= its own policyholder) against the board member (= the insured) to be without merit. This situation—where the policyholder is at the same time the damaged party—though typical under (German) D&O-policies is uncommon for liability insurance cover in general. It, thus, raises the issue as to the limits of the policyholder’s duty to disclose information. The scope of said obligation is not unlimited. It rather has to be ascertained pursuant to Sect. 31 VVG (German Insurance Contract Act), by taking into account the policyholder’s interests in commercial and industrial confidentiality and the burden of poof as provided by Sect. 93 para. 2 AktG (German Stock Companies Act). In case legal proceedings ensue between the company and the insured, and, as a consequence, the insurer exercises its obligation to conduct the case for the insured or the insurer joins the lawsuit on the side of the insured (by declaring a Third Party Notice [Streiverkündung]), the insurer clearly becomes an adversary to the company. Under such circumstances, the company is irrevocably released from its duty to disclose information.     

Creating Customer Value in Participating Life Insurance

The value of a life insurance contract may differ depending on whether it is looked at from the customer's point of view or that of the insurance company. We assume that the insurer is able to replicate the life insurance contract's cash flows via assets traded on the capital market and can hence apply risk‐neutral valuation techniques. The policyholder, on the other hand, will take risk preferences and diversification opportunities into account when placing a value on that same contract. Customer value is represented by policyholder willingness to pay and depends on the contract parameters, that is, the guaranteed interest rate and the annual and terminal surplus participation rate. The aim of this article is to analyze and compare these two perspectives. In particular, we identify contract parameter combinations that—while keeping the contract value fixed for the insurer—maximize customer value. In addition, we derive explicit expressions for a selection of specific cases. Our results suggest that a customer segmentation in this sense, that is, based on the different ways customers evaluate life insurance contracts and embedded investment guarantees while ensuring fair values, is worthwhile for insurance companies as doing so can result in substantial increases in policyholder willingness to pay.     

A data driven binning strategy for the construction of insurance tariff classes

We present a fully data driven strategy to incorporate continuous risk factors and geographical information in an insurance tariff. A framework is developed that aligns flexibility with the practical requirements of an insurance company, the policyholder and the regulator. Our strategy is illustrated with an example from property and casualty (P&C) insurance, namely a motor insurance case study. We start by fitting generalized additive models (GAMs) to the number of reported claims and their corresponding severity. These models allow for flexible statistical modeling in the presence of different types of risk factors: categorical, continuous, and spatial risk factors. The goal is to bin the continuous and spatial risk factors such that categorical risk factors result which captures the effect of the covariate on the response in an accurate way, while being easy to use in a generalized linear model (GLM). This is in line with the requirement of an insurance company to construct a practical and interpretable tariff that can be explained easily to stakeholders. We propose to bin the spatial risk factor using Fisher’s natural breaks algorithm and the continuous risk factors using evolutionary trees. GLMs are fitted to the claims data with the resulting categorical risk factors. We find that the resulting GLMs approximate the original GAMs closely, and lead to a very similar premium structure.     

An optimal stopping problem in risk theory

Abstract

In classical risk theory often stationary premium and claim processes are considered. In some cases it is more convenient to model non-stationary processes which describe a movement from environmental conditions, for which the premiums were calculated, to less favorable circumstances. This is done by a Markov-modulated Poisson claim process. Moreover the insurance company is allowed to stop the process at some random time, if the situation seems unfavorable, in order to calculate new premiums. This leads to an optimal stopping problem which is solved explicitly to some extent.     

An Equilibrium Model of Catastrophe Insurance Futures and Spreads

This article presents a valuation model of futures contracts and derivatives on such contracts, when the underlying delivery value is an insurance index, which follows a stochastic process containing jumps of random claim sizes at random time points of accident occurrence. Applications are made on insurance futures and spreads, a relatively new class of instruments for risk management launched by the Chicago Board of Trade in 1993, anticipated to start in Europe and perhaps also in other parts of the world in the future. The article treats the problem of pricing catastrophe risk, which is priced in the model and not treated as unsystematic risk. Several closed pricing formulas are derived, both for futures contracts and for futures derivatives, such as caps, call options, and spreads. The framework is that of partial equilibrium theory under uncertainty.     

Ex Post Moral Hazard and Bayesian Learning in Insurance

We study a dynamic insurance market with asymmetric information and ex post moral hazard. In our model, the insurance buyer's risk type is unknown to the insurer; moreover, the buyer has the option of not reporting losses. The insurer sets premia according to the buyer's experience rating, computed via Bayesian estimation based on buyer's history of reported claims. Accordingly, the buyer has strategic incentive to withhold information about losses. We construct an insurance market information equilibrium model and show that a variety of reporting strategies are possible. The results are illustrated with explicit computations in a two‐period risk‐neutral case study.     

Feasible fraud and auditing probabilities for insurance companies and policyholders

Insurance claims fraud is counted among the major concerns in the insurance industry, the reason being that excess payments due to fraudulent claims account for a large percentage of the total payments each year. We formulate optimization problems from the insurance company as well as the policyholder perspective based on a costly state verification approach. In this setting??while the policyholder observes his losses privately??the insurance company can decide to verify the truthfulness of incoming claims at some cost. We show simulation results illustrating the agreement range which is characterized by all valid fraud and auditing probability combinations both stakeholders are willing to accept. Furthermore, we present the impact of different valid probability combinations on the insurance company??s and the policyholder??s objective quantities and analyze the sensitivity of the agreement range with respect to a relevant input parameter. This contribution summarizes the major findings of a working paper written by Müller et?al. (Working Papers on Risk Management and Insurance (IVW-HSG), No. 92, 2011).     

The Demand for Insurance With an Upper Limit on Coverage

The demand for insurance is examined when the indemnity schedule is subject to an upper limit. The optimal contract is shown to display full insurance above a deductible up to the cap. Some results derived in the standard model with no upper limit on coverage turn out to be invalid; the optimal deductible of an actuarially fair policy is positive and insurance may be a normal good under decreasing absolute risk aversion. An increase in the upper limit would induce the policyholder with constant absolute risk aversion to reduce his or her optimal deductible and therefore this would increase the demand for insurance against small losses.     

Optimal Insurance With Costly Internal Capital

We introduce costly internal capital into a standard insurance model, in which a risk‐averse policyholder buys insurance from a risk‐neutral insurer with limited liability. The unique optimal contract and internal capital lead to a strictly positive probability for insurer default. Some risks are uninsurable in that the insurer chooses not to provide insurance against such risks. An increase in the cost of capital may lead to a higher optimal amount of internal capital. The results extend to multiple policyholders in a symmetric setting. Our extension of the classical model to include costly internal capital provides a fruitful approach to many real world insurance markets.     

Determinanten des Kundenwerts von Versicherungsnehmern

This paper discusses how the customer equity concept can be transformed to fit to insurance policy holders. The finding is that the equity of a policyholder can not be calculated in line with concepts of other classes of business, because the insurance industry shows special features in its core business. The stochastic characteristics of such a business must be integrated into the concept. These include its service nature and specific supervisory regulations for the capital investments as well as the distribution of profit. In terms of the insurance company, the following equity-determiners of a policyholder are important and should be part of the customer equity model: Firstly the equity of the customer with regard to the past, his future potential and his cross-selling equity as the monetary determiners. Secondly the equity which can be generated through word-of-mouth and customer information. The remaining determiners of the concept used in other branches of business, notably the equity of synergy, cooperation and loyality of a customer are already incorporated in the mentioned components.     

Wer trägt das Terrorrisiko?

This article deals with insuring terrorism risks and it focuses on the situation in Germany after the events of September 11^th 2001. After a brief introduction to the general problems of insuring against terrorism the authors explore how terrorism affects different lines of insurance business in Germany and examine Extremus, the German specialist insurer with government backing for insuring property risks against terrorism. A thorough analysis of different aspects of risk transfer follows. This analysis also addresses different pricing strategies for insuring against terrorism. In this section the authors focus on the question to what extend one can really speak of a risk transfer through insurance in respect to terrorism. Scenarios are developed of how large losses would affect the insurance industry as well as the customers. In regard to those scenarios it becomes visible that the risk transfer from the policyholder to the insurer is not complete.In their conclusion the authors examine some scenarios of increased and decreased terrorist activity and the effects that each of these scenarios will have on the solution of insuring against terrorism through Extremus.     

Geologisches Risikomanagement für Versicherungen

The application of Geoinformationsystems under geological, hydrological and hydrogeological aspects for the risk management is a further development of the geographical underwriting of the insurance industry. The knowledge of the geology, hydrology and hydrogeology is fundamental for the understanding and spatial analysis of insured objects before and during loss events for example with contaminations of the aquifer. Furthermore possible loss scenarios could be prevented or minimized if the subsurface geology and hydrogeology are already known and integrated in the initial insurance appraisal. The modelling and classification of the geoscientific knowledge also enables the definition of Action Zones, which allow a better appraisal and assessment of the insurable objects. This leads to an optimized and transparent premium calculation for both, the insurance and the policyholder (Münchener Rück 2002). The visualization of the geoscientific subsurface information in Geoinformationsystems is simple and economical feasible, it is quick to analyze and combinable with additional information and gives important insights in the subsurface structures. The paper describes a workflow how such Action Zones could be assessed and the additional information for the premium is generated.