Cyber Insurance

Details

Supervisors

Hainaut, Donatien

Faculty

Faculté des sciences

Degree label

Master [120] en sciences actuarielles, à finalité spécialisée

Abstract

From the Global Risk 2021 report, cyber security attacks risk is listed among the risks with the highest likelihood. Cyber risk has been known since the 1990’s and its insurance market is still evolving up to now with predicted premiums expected to rise up to 20 bn dollars by 2025. This master thesis is composed in 3 parts: The first part consisted of highlighting the characteristics of insurability of cyber risk and the challenges encountered when it comes to correctly identify the risk, the asymmetry of information, evaluating the risks as cyber risks cause more intangible losses like those related to loss of reputation. Another difficulty is the presence of strong correlations between the organizations exposed to the risk. Secondly, to model cyber-attacks arrivals, the Hawke process which is a self-exciting point process was used. The Hawkes process parameters were estimated by the method of maximum likelihood estimation, in the univariate case. Overall, the Hawkes processes have the capacity to model the arrival frequency of the data breach. Then, the so-called thinning algorithm was used in order to simulate trajectories of Hawkes processes which are the projections of the process with past history. Since, arrival attacks can come in clusters, a way to capture that phenomenon was by studying the compound poisson process. Lastly, a form of pure premium was proposed for a coverage in case of data breach.