The God’s-Eye View of ESG

Imagine a technology that could see the entire Earth from above in real time and identify patterns as well as the average human analyst. What effect would this panoptic technology have on the global financial sector?

Many new financial products would be possible, and comparative advantages would accrue to agents with unequal access. But if enough agents had access, the market could perceive previously unseen negative effects of economic activity (externalities) and bring market prices closer to the social accounting that captures the true value of production and consumption. Such cost discovery could reallocate capital in line with growing preferences for sustainability and equity, making better financial information a lever for transformative economic change.

The technology we have described is not a fantasy. In fact, it is fast arriving. Optical imagery is currently commercially available at 0.30 m spatial resolution, and spy satellites likely operate at less than 0.1 m. Weather satellites in geostationary orbit can transmit images of the same area every 30 seconds, although the higher-resolution instruments most relevant to financial applications image the same area only once every five to 16 days. While finer spatial resolution typically means a smaller field of view and a longer revisit time, falling costs have enabled fleets of microsatellites to overcome this trade-off, making daily high-resolution imagery commercially available.

But even panoptic vision has its limits. Optical instruments have significant spatiotemporal gaps in which economic activity is unobserved, most notably due to cloud cover. And many of the economic externalities that investors care about are not physical phenomena. Social outcomes (such as income inequality) cannot be observed from space, although they may leave physical signatures that allow indirect measurement. Critically, nonphysical phenomena include the relationships between people that organize economic activity (such as land tenure and trading arrangements). Without a map of these relationships, merely observing externalities does not produce actionable information. How the overwhelming flow of data is summarized and presented to financial decision makers also matters for outcomes.

To realize the potential of spatial finance, we must understand how radical transformations in our ability to monitor Earth from space can translate into impact through the global financial system. Technological progress is advancing our abilities to identify externalities using Earth observation (EO) data, but uptake in finance is just beginning. For data on externalities to become useful information for financial agents, they must be attributed within supply chains and appropriately summarized for communication. A growing industry of environmental, social, and governance (ESG) metrics is seeking to meet this need, but much more can be done to deploy EO data within existing ESG frameworks.

Attributing Impacts

Despite an established industry in delivering EO data as business intelligence, the potential for current-generation sensors to measure corporate performance on ESG targets remains largely unrealized. Most (but not all) environmental values generate physical signals that are directly observable in EO data, whereas few (but not none) social and governance values do. However, emergent environmental values like biodiversity or ecosystem resilience can only be monitored indirectly, and the necessary image interpretation and model-building are costly and place a constraint on measurement accuracy. Other environmental impacts (e.g., in deepwater marine habitats) that do not alter either the radiative properties or the spatial configuration of the Earth’s surface cannot be observed with current technologies.

The ability of space-based sensors to identify social and governance values is more limited. Some social values have physical signals and can be measured by proxy (e.g., categorizing roofing material to measure household prosperity); others can be inferred by combining data layers (e.g., proximity of housing by income strata to polluting assets). Comparing corporate commitments and actions against the EO data record can support inferences about governance quality.

For identified externalities to affect prices, they must be attributed to global financial activity. There is no technological replacement for traditional data sources (e.g., tax or customs records) in tracing the complex links whereby the financial sector funds harmful activity, is exposed to related transition risks, and invests in sustainability. Voluntary corporate disclosure cannot fill the gap, because while high-performing leaders benefit from disclosures that distinguish them from the competition, laggards do not. Blockchain doesn’t solve this incentive problem, although trusted supply-chain records do make it harder for bad actors to avoid detection. Machine learning can be used to map physical assets (e.g., farms, infrastructure) in the EO data record, but traditional data are still required to link these assets to financial institutions (e.g., investment portfolios). Computational resources can help coordinate multiple data streams, but success ultimately depends on data availability, and thus traditional relationship-building and data discovery.

The financial users of Earth observation data products commonly overestimate the importance of spatial resolution.

For EO data to have maximum impact, firms must be forced to self-report. International frameworks and standards for sustainability reporting are still largely voluntary, but this norm may change. In 2021, finance ministers and central bank governors from the Group of Seven (G7) countries committed to “moving towards mandatory climate-related financial disclosures,” and the European Union is poised to adopt the Corporate Sustainability Reporting Directive, which will require a broad array of listed firms doing business in the EU to disclose ESG impacts.

For elements of financial portfolios untouched by ESG disclosures, attributing externalities relies on aggregates (e.g., national trade statistics, production shares, or power mixes). Such broad-brush attribution forfeits the power of high-resolution identification and can produce perverse outcomes. Reducing exposure to ESG impacts is easy for investors with a global reach, and high-performing firms in low-performing (on average) jurisdictions, such as many developing countries, may find themselves cut off from the very sources of values-led finance that could fuel sustainable development.

The information that reaches financial decision makers is what alters behavior (and thus prices). The enormous volume of data associated with portfolio-wide economic activity ensures that choices about what information to communicate (and how) have far-reaching implications. ESG ratings providers play this vital communications role, but ratings may not be delivering the information that financial actors need to prioritize sustainable activities and assess exposure. Differences in (proprietary) metrics produce marked divergences in reported sustainability, and indicators are selected to maximize participation rather than scientific rigor. In practice, indicators often measure corporate processes (e.g., disclosure) rather than ESG impacts on the ground. Aggregation, error propagation, and selection bias present further complications.

Policy Priorities

EO data can strengthen financial levers for advancing economic sustainability by attributing costs, adjusting prices, and reallocating capital, but parallel approaches are needed to maximize impact. Commercial banks, for example, need trustworthy and scalable ESG metrics that communicate values alignment to retail investors, while investment banks can employ a broader suite of specialized EO-based products. Central banks require economy-wide data layers for macroeconomic modeling and financial risk and stability assessments, including for values such as carbon storage or biodiversity loss. Using EO data to meet these needs can help identify risks, redirect investment, change capital costs (e.g., debt-issuance terms), and support new financial instruments (e.g., performance-linked products) that bring capital to bear on sustainability challenges.

We offer the following recommendations for realizing the potential of spatial finance. First, the limited uptake of EO data within ESG reporting frameworks demonstrates the need to strengthen interdisciplinary connections between finance and remote sensing. Existing voluntary and mandatory regulatory frameworks must be revised (and new ones built) to become compatible with emerging EO data streams, such as global asset identification and monitoring. To further ensure future compatibility, geospatial coordinates for all assets and machine readability must be required in disclosure frameworks. Leading efforts, such as the EU’s Corporate Sustainability Reporting Directive, should now include such requirements in reporting guidance.

For policy makers, creating the conditions for collaboration is important. Initiatives such as the United Kingdom’s National Space Strategy have a vital role to play in fostering interdisciplinary exchange. Building shared literacy will accelerate progress. For example, scientists recognize that the quality of EO data matters for sustainability-linked financial products but are largely unaware of the role played by increased temporal frequency in finance. Conversely, the financial users of EO data products commonly overestimate the importance of spatial resolution. Shared competencies also help avoid mistakes, such as overlooking data limitations.

Second, limited availability of attributional data is currently bottlenecking the ability of EO data to create price adjustments within the financial system. This challenge cannot be overcome by the private sector alone, since many economic actors do not benefit from increased disclosure. Efforts to mandate disclosure through financial regulation and supervisory authorities are an important advance, but they have succeeded in only some jurisdictions—and do not yet affect nonlisted enterprises or small or medium firms. After decades of rapid progress in space-based observation and machine-enabled pattern recognition, the quality and availability of traditional economic data has arguably become the limiting factor in accountability-led financial transformation.

Solving the attributional challenge is not easy, but focused attention from high-profile initiatives on corporate and financial sustainability can help. (Take, for example, the UN-convened Net-Zero Asset Owner Alliance or the Network for Greening the Financial System [NGFS].) Where basic economic statistics are inaccessible, business leaders must strive to create transparency and disclosure norms to reveal global supply chains. Funding and training national statistical institutes in the least economically developed countries to enable subnational mapping of production locations would be an important advance, and more can be done to incentivize voluntary disclosure by connecting leading firms to sources of values-led finance. 

A final set of policy issues concern equity and privacy. The capacity to turn data into actionable information is not evenly distributed, and the legitimacy of increased use of EO data for monitoring and assessment within the global financial system should not be assumed. Developers must proactively anticipate impacts and invite participation from marginalized economic actors (e.g., smallholder farmers whose land-use change is targeted by a deforestation-free supply chain commitment). This effort is pressing given the growing private-sector leadership in space.

In our global market economy, better information should generate more efficient outcomes. With the right enabling conditions, the ongoing revolution in monitoring economic activity from space can help investors get the greener, cleaner, and fairer world we want. If externalities can be attributed and the full potential of Earth observation data realized, spatial finance holds the promise of radically increasing economic accountability—and thus global sustainability.