Work detail

Cyber risk modelling using copulas

Author: Mgr. Michal Spišiak
Year: 2020 - summer
Leaders: prof. PhDr. Petr Teplý Ph.D.
Work type: Finance, Financial Markets and Banking
Language: English
Pages: 87
Awards and prizes:
Abstract: Cyber risk or data breach risk can be estimated similarly as other types of operational
risk. First we identify problems of cyber risk models in existing literature. A large dataset
consisting of 5,713 loss events enables us to apply extreme value theory. We adopt
goodness of fit tests adjusted for distribution functions with estimated parameters. These
tests are often overlooked in the literature even though they are essential for correct
results. We model aggregate losses in three different industries separately and then we
combine them using a copula. A t-test reveals that potential one-year global losses due to
data breach risk are larger than the GDP of the Czech Republic. Moreover, one-year
global cyber risk measured with a 99% CVaR amounts to 2.5% of the global GDP. Unlike
others we compare risk measures with other quantities which allows wider audience to
understand the magnitude of the cyber risk. An estimate of global data breach risk is a
useful indicator not only for insurers, but also for any organization processing sensitive




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