Multivariate Dependence Modeling of Cyber Breach Risks with Insurance Applications
31 Pages Posted: 20 Sep 2024
There are 2 versions of this paper
Multivariate Dependence Modeling of Cyber Breach Risks with Insurance Applications
Multivariate Dependence Modeling of Cyber Breach Risks with Insurance Applications
Abstract
Cyber breaches pose a significant threat to enterprises and society at large. Analyzing data on cyber breach incidents is crucial for enhancing cyber risk management and developing effective cyber insurance policies. However, modeling cyber risk presents several challenges due to its characteristics, such as sparsity, heterogeneity, heavy tails, and dependence. This work introduces a novel multivariate dependence model that captures both temporal and cross-group dependencies to more accurately represent multivariate cyber breach risks. The proposed framework employs a semi-parametric approach to model breach sizes, while the multivariate dependence is modeled via a copula approach. Our findings, supported by both empirical and synthetic studies, demonstrate that the proposed model captures the statistical characteristics of multivariate cyber breach risks well and outperforms commonly used models in the literature in terms of predictive performance. Additionally, we show that our approach can generate more profitable insurance contracts in the context of insurance pricing .
Keywords: copula, Heterogeneity, Heavy-tail risks, Rosenblatt transform, Sparsity.
Suggested Citation: Suggested Citation