Risk management is a critical part of every industrial activity. In recent years, due to the complexity, importance and potential impacts of industrial processes, risk analysis has taken advantage of increasing computational availability to deliver tools at every level of the risk management spectrum. Bow-tie models, so called because of their generalized shape, are used at various levels in the risk analysis process, fundamentally because their presentation aggregates complex, real-world scenarios in consistent, reducible and communicable ways. As a result, vendors have sought to map additional capabilities onto the Bow-tie extending their applicability into qualitative, semi-quantitative, and quantitative risk assessment modalities. In this paper we present a generalized computational framework for risk analysis using Bow-tie models that simultaneously perform all such analytical modes.