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Tuesday, August 3 • 9:00am - 10:30am
3A3 Unraveling heterogeneity in cyber risks using quantile regressions

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Kwangmin Jung, POSTECH (Pohang University of Science and Technolkogy); Jeungbo Shim, University of Colorado-Denver; Martin Eling, Institute of Insurance Economics

This paper discusses two important issues in the cyber-insurance market: 1) adequate cyber-insurance pricing and 2) claims calculation of data breach events, which are the main type of risk covered by cyber-insurance policies. We use quantile regressions to consider heterogeneous firm-specific effects over different loss quantiles with one of the largest cyber risk databases offering both the total economic loss amount and the number of breached records. We identify that the firm size is a key factor in cyber-insurance pricing; a size effect of the breached records is also present in claims calculation with higher cost per record for small-sized loss events. The coefficients of key variables at extreme quantiles show on average 37.8% deviation from those of the OLS fit, implying that cyber losses are heterogeneous in their impacts and cyber insurers need to adapt this heterogeneity in pricing cyber policies. We consider this heterogeneity in the application to pure premium calculation in comparison with a two-part GLM and the Tweedie model. Our approach and findings are material for cyber insurers and policymakers, who aim to assess the impacts of firm-specific factors in insurance pricing and claims calculation.


John Houston

University of Stirling


Kwangmin Jung

POSTECH (Pohang University of Science and Technology)

Martin Eling

University of St. Gallen

Tuesday August 3, 2021 9:00am - 10:30am EDT