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Affirmative and silent cyber coverage in traditional insurance policies: Qualitative content analysis of selected insurance products from the German insurance market

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  • Dirk Wrede

    (Gottfried Wilhelm Leibniz Universität Hannover, Institute for Risk and Insurance)

  • Tino Stegen

    (Gottfried Wilhelm Leibniz Universität Hannover, Institute for Risk and Insurance)

  • Johann-Matthias Schulenburg

    (Gottfried Wilhelm Leibniz Universität Hannover, Institute for Risk and Insurance)

Abstract

This paper examines the design of affirmative and silent coverage in view of the cyber risks in traditional insurance policies for select product lines on the German market. Given the novelty and complexity of the topic and the insufficient coverage in the literature, we use two different sources. We analysed the general insurance terms and conditions of different traditional insurance lines using Mayring’s qualitative content analysis. Also, we conducted interviews with experts from the German insurance industry to evaluate how insurers understand their silent cyber exposures, and what measures they take to deal with this new exposure. The study shows a considerable cyber liability risk potential for insurers in the considered insurance lines. This arises from the affirmative as well as silent cover inclusions and exclusions for cyber risks, which result from imprecise wordings of insurance clauses and insufficient descriptions of the contractually specified scope of the insurance coverage.

Suggested Citation

  • Dirk Wrede & Tino Stegen & Johann-Matthias Schulenburg, 2020. "Affirmative and silent cyber coverage in traditional insurance policies: Qualitative content analysis of selected insurance products from the German insurance market," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(4), pages 657-689, October.
  • Handle: RePEc:pal:gpprii:v:45:y:2020:i:4:d:10.1057_s41288-020-00183-6
    DOI: 10.1057/s41288-020-00183-6
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    References listed on IDEAS

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