Climate-adjusted probability of default model: A framework for integrating physical climate risk for residential mortgage

Climate change poses significant threats to financial stability, particularly for residential mortgage portfolios exposed to physical risks like floods and wildfires. We propose an empirically grounded framework that integrates physical climate risk into probability of default (PD) modeling by applying climate multipliers—scenario-based adjustment factors derived from granular property-level hazard data. Climate multipliers amplify PD estimates, particularly under high-emission scenarios (e.g., SSP5–8.5), with the most pronounced effects in high-exposure regions. Most loans experience minimal adjustment, though a subset in hazard-prone areas exhibit PD increases exceeding 20× baseline values. Climate-adjusted PD models with add-on climate multipliers preserve the architecture of existing regulatory models, enabling scalable climate stress testing while supporting alignment with evolving supervisory expectations. This approach addresses critical gaps in current credit risk practices by bridging forward-looking climate data with borrower-level vulnerabilities, offering financial institutions a pragmatic tool to enhance resilience against climate volatility.