Mapping Physical Climate Risk Exposure in Euro Area firms: Linking E-PRTR and RIAD with a Fuzzy Match

We develop a methodology to assess the exposure of euro area companies to physical climate risks by incorporating the geographic distribution of their production facilities. We apply this approach by linking company-level data from the Register of Institutions and Affiliates Data (RIAD) with facility-level data from the European Pollutant Release and Transfer Register (E-PRTR) using a fuzzy string matching algorithm enhanced with machine learning. The methodology is applied to estimate expected annual losses (EAL) from floods and windstorms, following the framework developed by the European System of Central Banks. Our findings show that accounting for local units significantly affects the quantification of flood risk exposure, for both river and coastal floods, while the impact on windstorm risk is limited. We further analyze the spatial distribution of EAL differences across NUTS 3 regions, highlighting areas where relying solely on headquarter locations leads to substantial underestimation of risk.