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.
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