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Data breaches: Goodness of fit, pricing, and risk measurement

Martin Eling and Nicola Loperfido ()

Insurance: Mathematics and Economics, 2017, vol. 75, issue C, 126-136

Abstract: Some research on cyber risk has been conducted in the field of information technology, but virtually no research exists in the actuarial domain. As a first step toward a more profound actuarial discussion, we use multidimensional scaling and goodness-of-fit tests to analyze the distribution of data breach information. Our results show that different types of data breaches need to be modeled as distinct risk categories. For severity modeling, the log-skew-normal distribution provides promising results. The findings add to the recent discussion on the use of skewed distributions in actuarial modeling (Vernic, 2006; Bolancé et al., 2008; Eling, 2012). Moreover, they provide useful insights for actuaries working on the implementation of cyber insurance policies. We illustrate the usefulness of our results in two applications on risk measurement and pricing.

Keywords: Cyber risk; Risk measurement; Multidimensional scaling; Goodness of fit; Skew-normal distribution (search for similar items in EconPapers)
JEL-codes: G22 G31 (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:75:y:2017:i:c:p:126-136

DOI: 10.1016/j.insmatheco.2017.05.008

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Insurance: Mathematics and Economics is currently edited by R. Kaas, Hansjoerg Albrecher, M. J. Goovaerts and E. S. W. Shiu

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