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Zurich Insurance Uses Data Analytics to Leverage the BI Insurance Proposition

Author

Listed:
  • Kamil J. Mizgier

    (Department of Management, Technology, and Economics, Swiss Federal Institute of Technology Zurich, 8092 Zurich, Switzerland)

  • Otto Kocsis

    (Zurich Insurance Company Ltd., 8045 Zurich, Switzerland)

  • Stephan M. Wagner

    (Department of Management, Technology, and Economics, Swiss Federal Institute of Technology Zurich, 8092 Zurich, Switzerland)

Abstract

As the interdependencies due to global trade and interconnected value chains have grown, firms and their value chains have become more prone to disruptions. Consequently, many firms resort to business interruption (BI) insurance to transfer the disruption risk. Given the limited amount of literature available about BI loss and claims characteristics, insurance companies and their customers will benefit from the insights that resulted from the project underlying this study. The project involved a collaboration between Zurich Insurance and the Swiss Federal Institute of Technology Zurich, in which we extracted a large amount of data pertaining to BI claims from various data sources and analyzed these data. We found, for example, that the average share of BI losses has increased significantly over the past 15 years. Moreover, the BI risk exposure, measured as BI share of the total insurance claims, the average recovery time, and the increased costs of working, differs significantly based on the industry affiliation of the firm experiencing the loss. Our results have implications for the targeted risk assessment of BI risk exposures and the development of tailored supply chain risk management practices and risk transfer along the value chain.

Suggested Citation

  • Kamil J. Mizgier & Otto Kocsis & Stephan M. Wagner, 2018. "Zurich Insurance Uses Data Analytics to Leverage the BI Insurance Proposition," Interfaces, INFORMS, vol. 48(2), pages 94-107, April.
  • Handle: RePEc:inm:orinte:v:48:y:2018:i:2:p:94-107
    DOI: 10.1287/inte.2017.0928
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    References listed on IDEAS

    as
    1. Bernardo Nicoletti, 2016. "Innovation in Insurance," Palgrave Studies in Financial Services Technology, in: Digital Insurance, chapter 1, pages 6-46, Palgrave Macmillan.
    2. Mizgier, Kamil J. & Wagner, Stephan M. & Jüttner, Matthias P., 2015. "Disentangling diversification in supply chain networks," International Journal of Production Economics, Elsevier, vol. 162(C), pages 115-124.
    3. David Simchi-Levi & William Schmidt & Yehua Wei & Peter Yun Zhang & Keith Combs & Yao Ge & Oleg Gusikhin & Michael Sanders & Don Zhang, 2015. "Identifying Risks and Mitigating Disruptions in the Automotive Supply Chain," Interfaces, INFORMS, vol. 45(5), pages 375-390, October.
    4. Lingxiu Dong & Brian Tomlin, 2012. "Managing Disruption Risk: The Interplay Between Operations and Insurance," Management Science, INFORMS, vol. 58(10), pages 1898-1915, October.
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    Cited by:

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    2. Qin, Xuwei & Shao, Lusheng & Jiang, Zhong-Zhong, 2020. "Contract design for equipment after-sales service with business interruption insurance," European Journal of Operational Research, Elsevier, vol. 284(1), pages 176-187.
    3. Emer Owens & Barry Sheehan & Martin Mullins & Martin Cunneen & Juliane Ressel & German Castignani, 2022. "Explainable Artificial Intelligence (XAI) in Insurance," Risks, MDPI, vol. 10(12), pages 1-50, December.
    4. Melinda Malau, 2020. "Earning Informativeness is Moderating Investment Opportunity, Return on Asset, and Leverage on Prudence Measurement," Journal of Accounting, Business and Finance Research, Scientific Publishing Institute, vol. 9(2), pages 57-63.

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