About 655 million people worldwide lack access to electricity, and sub-Saharan Africa (SSA) accounts for nearly 85% of them. Development finance institutions, philanthropic organizations and impact investors have made significant commitments to close this gap, with international finance flows to developing countries for clean energy reaching $24.6 billion in 2024. But the growth in finance is not keeping up with the growth in energy demand. The 2024 finance flows grew by less than 1% from 2023, while flows to the least-developed countries fell by 11% to $3.7billion. Meanwhile, global demand for energy increased 2.2% that same year, with 80% of that growth in developing countries. Financing for electricity access is far smaller. The International Energy Agency estimates that less than $2.5 billion was committed to new electricity access connections in SSA in 2023, against the $15 billion needed each year to reach universal access by 2035.But the constraint is not solely the availability of capital. It’s the information environment in which allocation decisions are made.That gap unfolds at the transaction level. Energy enterprises, such as mini-grid developers and productive use of renewable energy (PURE) equipment distributors, typically seek financing ranging from tens of thousands to millions of dollars. Due diligence required to underwrite these transactions is largely a fixed cost. Market sizing studies, demand assessments, site visits and creditworthiness evaluations can consume resources disproportionate to the ticket size in consideration. This is especially prohibitive for small ticket sizes. Commercial investors therefore tend to prioritize larger, well-documented transactions. The result is a structural undersupply of finance to the enterprises delivering last-mile energy access. Capital concentrates where data availability reduces perceived risk, creating a cycle in which well-documented markets attract further investment while underserved areas remain invisible to capital allocators. Closing the financing gap requires breaking this cycle by reducing the cost of and increasing access to high-quality information available to inform due diligence.How Geospatial Analytics Transform Investment IntelligenceThe Energy Access Explorer (EAE) offers one way to address this challenge. EAE is a mapping platform that supports early-stage investment decisions. The platform integrates demand layers, such as population distribution and social infrastructure including schools, health facilities and agro-processors, with supply layers such as grid and off-grid infrastructure. Users can weight and filter these layers using their own prioritization criteria, translating geospatial data into a visualization of where demand, viability and project needs coincide.This allows investors and funders to cut costs from the early stages of the due diligence process by layering geospatial datasets within the multi-criteria framework. Investment screening that would otherwise require commissioned studies in specific geographies can be performed in a short time span. Potential sites can be narrowed to a short list and then proceed to field-level reconnaissance. The PURE Investment prospectuses developed for Kenya, Uganda and Tanzania demonstrate how using EAE can inform investment decisions. WRI and its partners used EAE to carry out geospatial analysis to identify subnational locations where agricultural activity, energy demand and energy-access deficits overlap. This mapping was then translated into an investment prospectus of PURE opportunities in solar irrigation, agro-processing and cold chain applications. The below analysis on the EAE illustrates two scenarios where investors or philanthropies could use EAE to prioritize where to deploy capital for energy solutions in Uganda under different models or circumstances. Scenario 1: Investors looking for areas where there is demand for energy solutions for agriculture and social services (health and education), and targeting populations or institutions with ability to pay and with access to credit facilitiesScenario 2: Philanthropy organizations looking for areas where there is demand for energy solutions for agriculture and social services (health and education), and targeting populations or institutions without ability to pay and without access to credit facilities. Layers use and filters for Scenarios 1 and 2Layer Plus ExplanationScenario 1Filters/UnitsScenario 2Filters/UnitsPopulation Count (demand for energy solutions) Number of people per square kmNumber of people per square kmRelative Wealth Index (populations living above or below the average household wealth, 0 being the average) >0 (potentially having ability to pay for energy solutions) <0 (would need philanthropy support/appropriate financial products) Health and Education Facilities (to filter areas with health and education facilities within 5km proximity) <5km proximity <5km proximity Crops (areas with demand for energy solutions for agriculture) Production measured in metric tons Production measured in metric tons Distribution Lines (areas without access to grid electricity connection) >2km proximity >2km proximity Global Horizontal Irradiation (areas with good potential for solar energy) >1,800 kwh/m2 >1,800 kwh/m2 Financial Services (filter areas within proximity to financial providers to access credit facilities or areas not within proximity to financial providers) <15km proximity (within range of easy access to financial services) >15km proximity (not within range of easy access to financial services) Scenario 1 outputs maps and analysis (for investors) Analysis outputs for Scenario 1, showing all the areas in Uganda meeting the analysis criteria. A total of 507,341 people live in areas with demand for energy services and solutions for household lighting, agriculture applications and for social services (health and education). They also have potential ability to pay since their incomes are above the average national household wealth while also living in areas within proximity to financial service providers. One such location is highlighted above.Scenario 2 outputs maps and analysis (for philanthropies) Analysis outputs for Scenario 2, showing all the areas in Uganda meeting the analysis criteria. A total of 3,692,531 people live in the areas with demand for energy services and solutions for household lighting, agriculture applications and for social services (health and education). They also do not have potential ability to pay since their incomes are below the average national household wealth while also living in areas without proximity to financial service providers. One such location is highlighted above.Applications for Philanthropic CapitalPhilanthropy’s comparative advantage over commercial investors in energy-access finance is its ability to deploy catalytic and patient capital through grants, first loss positions, results-based financing and technical assistance. EAE amplifies this advantage in three distinct ways:Targeted de-risking. Instruments such as results-based financing windows are most effective when placed where market failure is real rather than assumed. EAE allows funders to geospatially assess market needs by mapping the boundary between commercially viable geographies and those where energy service provision requires subsidies. Concessional capital targeted at this boundary can expand markets, whereas concessional capital deployed within the commercially viable zone risks displacing private investment. Under a joint project by Ethiopia’s Ministry of Water and Energy World Bank, EAE supported the prioritization of off-grid investments serving 19 million people across 145 woredas through a results-based financing scheme.Pipeline development. Data does not become a transaction on its own. The investment prospectuses that WRI and its partners developed for Kenya, Uganda and Tanzania illustrate that geospatial intelligence can support a co-development process for pipeline projects involving financiers, energy equipment developers and suppliers, subnational governments and potential project beneficiaries. Philanthropic funders are uniquely positioned to finance this transition from data to deal by converting EAE outputs into bankable opportunities that private commercial financiers can subsequently absorb. In Kenya, Makueni County, one of the inaugural counties to develop a PURE-focused investment prospectus, committed its own public budget (approximately 26 million Kenyan shillings or just over $200,000) to solarize Makueni County Referral Hospital. This is an example of how a well documented pipeline informed by geospatially backed feasibility studies can guide subnational governments’ capital.Market shaping. EAE provides a shared operating overview across funders, helping coordinate the function that philanthropy increasingly plays in fragmented markets, avoiding duplication among philanthropic institutions and informing where to seed ecosystem partnerships. For example, The Tanzanian Renewable Energy Association utilizes EAE for Tanzania’s mini-grid geospatial analysis, thereby generating custom market prospects informed by screening locations to expand businesses and introduce targeted investment for electricity service solutions. Limitations Using geospatial intelligence to inform investment decisions and capital allocation comes with a couple of constraints worth noting. The first relates to data availability and quality. Collecting, cleaning-up and validating the datasets used in EAE can be time consuming and updates can lag changing conditions on the ground. Ongoing work to apply artificial intelligence to data collection and integration is expected to shorten these update cycles significantly. The second relates to data access. Data provider agreements or commercial sensitivities may limit access to some layers or restrict who can use them. EAE uses a hybrid access model in which most geospatial layers are openly available, while sensitive layers can be restricted to authorized users. The third limitation concerns the uncertainty in translating geospatial analysis to project execution. Results depend on the scale of the analysis, the assumptions used and the weighting criteria applied. Different choices may produce different results: A location can score highly on every demand and supply indicator and still host a project that fails due to management capacity, governance or procurement challenges. Geospatial screening narrows the field but does not underwrite the transaction. Final investment decisioning typically requires company-wide financial statements and commercially sensitive counterparty information.Moving ForwardThe energy-access financing gap will not be closed by a single instrument. Universal energy access requires capital mobilization across the full spectrum, from grant funding to commercial debt. Geospatial intelligence can improve the efficiency with which that spectrum operates. When philanthropic and concessional funders integrate EAE into their initial capital allocation decisions, they can generate geospatially verified evidence of market opportunity, identify de-risking entry points and support co-developed pipelines. These are the conditions under which private capital follows. For philanthropic and concessional funders, one practical step is to make geospatial screening a routine part of the program design carried out before derisking instruments are deployed. Commercial investors and lenders can take a similar step at investment origination using geospatial screening to build pipelines in markets they would otherwise overlook and to focus their own due diligence on locations where demand and project viability are already evidenced. Development partners can enable this by continuing to invest in the development of the EAE platform and the capacity of private financiers to use it. Geospatial analysis will not close the financing gap on its own. What it can do is help philanthropic funders place limited concessional capital where it is most likely to be additional, and give follow-on private financiers a clearer starting point for their own due diligence.