4 résultats pour « Cyber risk »

Cyber Risk Taxonomies: Statistical Analysis of Cybersecurity Risk Classifications

Cyber risk classifications often fail in out-of-sample forecasting despite their in-sample fit. Dynamic, impact-based classifiers outperform rigid, business-driven ones in predicting losses. Cyber risk types are better suited for modeling event frequency than severity, offering crucial insights for cyber insurance and risk management strategies.

Cyber Risk Taxonomies: Statistical Analysis of Cybersecurity Risk Classifications

This paper argues that traditional cyber risk classifications are too restrictive for effective out-of-sample forecasting. It recommends focusing on dynamic, impact-based classifications for better predictions of cyber risk losses, suggesting that risk types are more useful for modeling event frequency rather than severity.

An Integrated Study of Cybersecurity Investments and Cyber Insurance Purchases

This study explores cyber risk in businesses, suggesting cybersecurity investment and insurance as key strategies. Using a network model, it examines firms' interconnected decisions, defining a Nash equilibrium where firms optimize cybersecurity and insurance. Findings highlight their interdependence and how network structures affect choices, reinforced by numerical analyses.

Improving Data for Managing Cyber Risk and Building Resilience

“Gaps in the data available for assessing cyber risk have limited the development of metrics that would help the public and private sectors prevent and recover from cyberattacks and reduce systemic risk. Cyber incident disclosure rules, introduced to close the data gaps, help but fall short in supporting the effective management of cyber risk. This article examines current and proposed reporting requirements, especially in the financial sector, where they are the most advanced.”