This report explains that location has always been crucial for assessing both impacts and risks, especially in sustainable finance, where geography can determine SDG financing eligibility. Thanks to geocoded data for millions of facilities, financial institutions can now conduct large-scale geospatial analysis across loans and investment portfolios.

By linking asset coordinates with maps showing land use, protected areas, wildfire risk, water stress, and chokepoints, financiers can better identify environmental and geopolitical risk exposure. This development is driven by regulatory pressure, technological advances, and growing attention to nature-related issues. Geospatial big data also allows financial analysis to move from isolated micro-level assessments to broader bottom-up portfolio analysis. It can help detect facility-level issues such as deforestation risks and support engagement with asset operators.

However, important limitations remain. Corporate asset data is still incomplete, especially in emerging markets, and it is often difficult to connect facilities with legal entities. In addition, geospatial data usually captures inherent exposure rather than actual operations, productivity, or mitigation measures. Therefore, geospatial analysis should be combined with other ESG-related data sources. Despite these limitations, geo-bigdata has strong potential, especially for impact investing, where local context is essential.