Jeff Bohn, One Concern
ABSTRACT: As more property-related data are becoming available, unprecedented granular analyses have become facilitated with hybrid methodologies that incorporate machine learning (ML) into physics-based models. These modeling capabilities open the door to resilience analyses—especially with respect to climate-change scenarios—that are becoming important parallel assessments to other types of longer-term, non-financial (at least in the short term) focused, risk analyses that look at environment, social, and governance (ESG) drivers for business and property. This presentation will touch on these developments addressing ESG + R(esilience) in the context of risk assessment, selection, pricing, and transfer relevant for insurers, banks, and asset managers with exposure to commercial property risk.