Over the past two decades, there has been a step-function in the scientific understanding of natural hazards, from earthquakes to hurricanes and other climatic perils. Yet most of the use cases for this knowledge have centered around the research or forecasting communities, involving highly specialized computing and scientific resources. RMS, since spinning out from Stanford University in 1989, has built its business delivering commercially relevant catastrophe modeling software and analytics to the global financial services industry, enabling business practitioners in the re/insurance sector and investors in catastrophe-linked securities to quantify, manage, and hedge their risks to these perils throughout the world. In their talk, Hemant and Philippe discuss these business centric use cases, the modeling approaches behind them, and how the revolution in commercially available and scalable compute and analytic technologies are bringing ‘big science’ out of the lab and enabling corporations to incorporate these insights to the heart of their business processes and workflows.