Emmi’s Climate Hazard Diagnostics uses a scenario-aligned, science-based approach to quantify how acute physical climate hazards—such as wildfire, tropical cyclones, and flooding—are projected to change at specific locations over time, and across different warming scenarios.

By focusing on changes relative to a historical baseline and employing standardised metrics for both severity and frequency, Emmi’s methodology isolates the climate-driven signal and enables consistent comparison across location, hazards, scenarios, and time horizons.

This modular framework is designed for seamless integration into portfolio screening, scenario analysis, and regulatory reporting, providing transparent, early indications of changes in asset risk.

In contrast, leading market alternatives typically rely on proprietary risk models that combine global climate projections with local infrastructure, land use, and vulnerability assumptions. The goal here is to estimate absolute risk or potential financial loss at the asset level.

These approaches often require integrating detailed engineering data, insurance loss records, or local adaptation measures, often unavailable in a screening context. These inputs aiming to deliver site-specific risk scores or loss estimates.

While this can provide granular outputs for individual assets, scaled usage of data can get expensive. It may also introduce variability due to differences in local data quality, model assumptions, and the treatment of future adaptation, making scenario-to-scenario and cross-portfolio comparisons more complex.