Academic journal article Journal of Risk and Insurance

Information about Multiple Risks: The Case of Building and Content Insurance

Academic journal article Journal of Risk and Insurance

Information about Multiple Risks: The Case of Building and Content Insurance

Article excerpt


Insurers traditionally use risk-specific characteristics of insureds to classify them according to risk. In this article, the practical relevance of information about multiple risks is demonstrated for the case of content insurance of a Swiss company. Two types of such information prove important: information about "spillover moral hazard" caused by mandated prevention affecting preventive effort in an unregulated line, and information about "common impulses" reflected in the loss experience of related lines. Both contribute to an improved prediction of loss probability.


Risk-based premiums are a necessity for insurers in a competitive market environment. The calculation of such premiums involves the prediction of an individual's (or firm's) loss probability and amount of loss. Three types of information have been used to this end (Boyer et al., 1992; Gourieroux, 1997). First, the static model incorporates the individual's risk-specific characteristics, which are typically time-invariant. Second, the dynamic model includes the insured's loss experience, which contributes considerably to the explanation of the probability and size of the loss. However, whether this correlation is due to true or spurious state dependence is not clear (Pinquet, 1997). The third type of information used is the insured's contract choice, e.g., the amount of deductible opted for. However, recent empirical work finds contract choice to have no informational content (Chiappori and Salanie, 1997; Dionne et al., 1997).

The common feature of these three types of information is that they reflect risk attributes specific to the risk being analyzed. In this article, we propose two additional sources of information for use in the calculation of risk-based premiums. They are of the "multiple risks" rather than the "specific risks" type in that they can be obtained from observing the insured's behavior with regard to other risks that are also covered by the insurer. Specifically, this additional information relates to "common impulses" and "spillover moral hazard."

These concepts are illustrated in Figure 1. Assume two risks, B and C, and the insurer attempts to calculate risk-based premiums for risk C. By using information about the insured's characteristics, loss experience, and contract choice, the insurer only takes account of the impulses specific to risk C. However, two additional sources of information exist. First, common impulses influence the two risks in a similar way, e.g., the insured's degree of risk aversion, regulation affecting several lines of insurance, or the general economic situation of the country. Note the difference between common impulses and the consumption of correlative goods proposed in Bond and Crocker (1991). The former have an impact on all the risks an individual faces, whereas the latter provide information specific to a certain risk. Second, spillover moral hazard caused by some regulation specific to risk B may lead to a change in preventive effort directed at risk B. Given optimizing behavior on the part of the insured, this change is likely to trigger an adjustment of preventive effort directed at risk C. In addition, technology may cause B-prevention to have a spillover effect on C-prevention and hence on the claims process of risk C.

In the following, information about multiple risks will relate to insurance against damage to contents caused by fire (C). Common impulses such as the insured's degree of risk aversion have an influence on the amount of damage caused to both the building (B) and its contents by water and other materials. Spillover moral hazard emanates from public regulation of fire prevention in buildings.

The remainder of this article is organized as follows. In the "Theoretical Basis for Spillover Moral Hazard" section we sketch a multiple-risks model incorporating prevention that can be used to predict spillover moral hazard effects between risks. …

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