Economies of Integrated Risk Management? An Empirical Analysis of the Swiss Public Insurance Approach to Natural Hazard Prevention


In this paper we discuss the impact of prevention programmes Swiss property insurers undertake to reduce damage claims. While the cantonal public law insurer KGV tends to spend notable amounts of money on prevention programmes to avoid or decrease damage due to natural hazard, the private insurers in the so-called GUSTAVO cantons rather do not. We investigate the interaction of prevention spending, claims and premiums in the KGV system. Furthermore, for the KGV system, we check the causality direction of influence of prevention on the claims and find that increases in damage cause increased prevention. This may seem counterintuitive at first glance, but can be explained by political pressure on public insurers caused by increasing damages of natural hazards.

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  1. 1.

    Geneva, Uri, Schwyz, Ticiano, Appenzell Innerrhoden, Valais and Obwalden, known jointly as the GUSTAVO cantons.

  2. 2.

    In frequently held cantonal direct polls citizen groups and politicians often argue with the outcomes in cantons in their vicinity, e.g. lower premiums and higher services quality, to make the case for a reform of their cantonal insurance system.

  3. 3.

    Every year, private households and public institutions spend an average of 3 billion CHF (2.76 billion EUR) on reducing the vulnerability of buildings with respect to natural hazard damage with the help of constructional, biological and spatial planning measures, and assistance for emergency planning and preparation for natural disasters, as well as on research and planning. A good quarter of this (741 million CHF or 682 million EUR) is spent on private and public insurance in Switzerland. By contributing to the prevention of damage caused by natural disasters, this is instrumental in creating social responsibility for natural hazard management within the insurance sector.

  4. 4.

    Please note that the KGV prevention data also include spending on fire safety and fire services and consumables (i.e. intervention spending).

  5. 5.

    The GAR 2013 recommendations for insurance-related instruments of disaster risk reduction are partly grounded and further explained by Suarez and Linnerooth-Bayer (2011).

  6. 6.

    For an overview of additional ENHANCE case studies, see A survey of novel insurance instruments for risk reduction is provided by Surminski et al. (2015).

  7. 7.

    Data are for the combined natural hazard and fire premium (NH + F) for a single family house (SFH). For the private GUSTAVO cantons, this value comprises the statutory natural hazard premium of 0.46 per mille and a mid-range fire premium of 0.39 per mille from consistent market analyses.

  8. 8.

    KGV (low) and KGV (high) compare the set of costs and premiums of the KGV with lowest and highest cost and premium in our sample.

  9. 9.

    Another comparison of standardized insurance cases (including industrial cases) for the canton of Grisons came to the same conclusion: For a private property valued at 500,000 CHF, an inhabitant of Grisons pays an annual premium of 150 CHF while with eight comparable private insurers, the premium would cost an average of 373.50 CHF. For industrial buildings and hotels (valued at 4,800,000 CHF each), the policyholder would pay an insurance premium of between 2,376 and 2,592 CHF whereas with private insurers they would pay around twice that amount: from 5,065 to 5,341 CHF (see Advantis Versicherungsberatung 2009).

  10. 10.

    All of the aforementioned steps were, however, applied to every type of claim and analyzed individually.

  11. 11.

    Adjusting the claims (measured in monetary terms) for the sum insured is an (implied) inflation adjustment, since the sum insured itself is an inflation proxy.

  12. 12.

    A test was conducted to determine whether a fixed effects (FE) estimator or a random effects (RE) estimator was better suited to addressing the heterogeneity issue. Fixed effects are present when individual effects remain constant over time. Random effects do not need to be constant over time but do require strict exogeneity. The Hausman test was applied and showed that, in this case, an RE estimator was the better choice.

  13. 13.

    We can infer on increased economic welfare from lower insurance production costs because, in a regulated monopoly, cost reductions translate into cheaper premiums and, in turn, result in an increase in consumer surplus (increase in prosperity from the customer perspective).


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Correspondence to Carsten Croonenbroeck.

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Schwarze, R., Croonenbroeck, C. Economies of Integrated Risk Management? An Empirical Analysis of the Swiss Public Insurance Approach to Natural Hazard Prevention. EconDisCliCha 1, 167–178 (2017).

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  • Risk management
  • Insurance
  • Buildings
  • Natural hazards