A1178
Title: Time dynamics of cyber risk
Authors: Dingchen Ning - University of St. Gallen (Switzerland) [presenting]
Rustam Ibragimov - Imperial College London and St. Petersburg State University (United Kingdom)
Martin Eling - University of St Gallen (Switzerland)
Abstract: The purpose is to utilize three large databases to understand better the characteristics of cyber loss events, especially how to deal with data biases and how cyber losses evolve over time. The problem of report delay is faced with an extended two-stage model in combination with detailed information in the data. Then, the frequency and severity of different categories of cyber events (such as malicious and negligent events) are analyzed using state-of-the-art statistical methods to detect structural changes. It is documented that the frequency is increasing rapidly as malicious cyber events have grown exponentially in the past two decades, but there is no significant change in loss severity. The tail dynamics are also explored, and it is found that the heavy-tailedness of cyber events is persistent over time. Finally, a conceptual model is developed with the documented empirical features (delayed information and heavy-tailedness), showing that they lead to significantly lower insurance demand. It might help explain the low volume of the cyber insurance market observed today.
