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The geospatial Agent-Based Model (ABM) framework outlined in this article enables financial institutions, including insurers, to quantify direct and cascading climate risks, capturing spatial and temporal dynamics and supply chain disruptions overlooked by traditional models. It supports climate scenario analysis for enhanced risk assessment and portfolio management, revealing systemic risks affecting even indirectly exposed agents. The framework evaluates cost-effective adaptation strategies, showing how firms’ adaptive behaviors, like pre-emptive capital increases, reduce climate impacts. By integrating geospatial climate data with economic models, it bridges gaps between climate projections and financial decision-making, aiding risk management and capital allocation.

"We model a setting where a firm must choose when to adapt to climate-induced resource scarcity based on objective expectations of climate change (climate projections), and is influenced by both risk (annual variability in climate projections) and ambiguity (inability to assign probabilities to various climate projections)."