A Quantitative Framework for Cyber Risk Modeling under Uncertainty: Frequency–Severity, Tail Risk, and Board-Level Decision Coupling

This deposit contains a methodological preprint proposing a probabilistic framework for cyber risk modeling under uncertainty. The manuscript develops a quantitative frequency–severity architecture for cyber loss, explicitly incorporating overdispersed event frequencies, heavy-tailed severities, reporting thresholds, truncation, censoring, uncertainty propagation, and governance coupling through risk appetite constraints and control optimization. The paper is positioned as a methodological preprint rather than an empirically finalized validation study. Its primary contribution is the formal specification of a quantitative modeling framework and an audit-capable governance architecture for board-level cyber risk decision support. Empirical validation, executable reproducibility artifacts, and extended sensitivity outputs are identified as the next stage of work.