Bio-Value-at-Risk: A Scenario-based Concept to Assessing the Implications of Biodiversity Risks on Financial Portfolio Management using Geospatial Analysis

Biodiversity loss poses an increasingly material risk to companies and investors, yet its integration into corporate and financial risk management remains limited due to data scarcity, methodological fragmentation, and a lack of spatial precision. This paper introduces the Bio-Value-at-Risk (BioVaR) framework, a bottom-up, scenario-based approach that quantifies the financial implications of biodiversity loss at the level of individual corporate assets. By overlaying geospatial biodiversity indicators derived from high-resolution remote sensing data with asset-level operational information, the method attributes localized ecosystem impacts to specific company sites. These physical impacts are translated into site-specific financial loss estimates through empirically calibrated cost functions, which incorporate both physical and transition risks, including regulatory and reputational effects. Aggregating these local losses across a firm’s operations allows the construction of biodiversity-conditioned financial statements and the estimation of valuation effects on equity and debt positions. When consistently applied across firms, these company-level valuations form the basis for portfolio-level risk measures such as BioVaR or biodiversity-related Expected Shortfall.

The framework generalizes established principles of operational risk management to nature-related risks and connects geospatial environmental data with financial valuation models and scenario analysis. It enables the derivation of probability distributions of biodiversity-related financial losses under globally consistent scenarios, including those conditioned on climate pathways or regional regulatory responses. Compared with prevailing top-down approaches, BioVaR provides higher spatial, temporal, and sectoral resolution, allowing investors, regulators, and policymakers to identify, price, and manage biodiversity risk exposures through targeted investment, lending, and credit decisions rather than sector-wide exclusions.

The study demonstrates that linking satellite-based biodiversity metrics with asset-level financial data enables consistent quantification, internalization, and aggregation of nature-related risks within corporate risk frameworks and portfolio management. The BioVaR concept thus advances the operationalization of spatial sustainable finance and offers a scalable, data-driven pathway toward integrating biodiversity considerations into financial risk analysis, disclosure, and strategic decision-making.