Executive Summary
Digital Public Infrastructure (DPI) — open, interoperable systems for identity verification, payments, and data exchange — represents the most capital-efficient development investment available to emerging economies today. The empirical evidence is now overwhelming. India's Unified Payments Interface (UPI) processed 14.8 billion transactions in December 2025 alone, valued at approximately $268 billion. Brazil's Pix instant payment system reached 170 million registered users within three years of launch. Kenya's M-Pesa mobile money ecosystem facilitates transaction volumes equivalent to 65% of the nation's GDP.
These are not isolated success stories — they represent a structural pattern. When governments invest in open, interoperable digital rails, the resulting economic multiplier effects range from 9–15x the initial capital deployed, far exceeding the returns from traditional physical infrastructure. This report synthesizes empirical evidence from three landmark DPI deployments to quantify the multiplier mechanism and outline the investment case for scaling DPI across emerging markets globally.
Defining Digital Public Infrastructure
DPI operates as a two-sided platform market, following the framework established by Rochet and Tirole (2003) in their foundational analysis of platform economics. Unlike traditional public infrastructure — roads, ports, electricity grids — DPI creates value not merely through direct usage but through the market interactions it enables between previously disconnected economic actors.
The canonical DPI stack comprises three layers. First, identity layers that provide verifiable digital identity to populations previously excluded from formal economic systems — India's Aadhaar biometric identity system has enrolled 1.4 billion individuals, creating the world's largest digital identity platform. Second, payment rails that enable real-time, low-cost value transfer — UPI in India, Pix in Brazil, and M-Pesa in Kenya each represent distinct architectural approaches to the same fundamental problem. Third, consent-based data sharing frameworks that allow individuals to share verified financial and personal data across institutions — India's Account Aggregator framework, launched in 2021, enables individuals to share financial data across banks, insurers, and lenders through a consent-management layer, reducing information asymmetries that have historically constrained credit access.
The critical distinction between DPI and conventional government IT systems is openness. DPI provides open APIs, standardized protocols, and interoperability requirements that allow private-sector participants to build services on top of public rails. This design choice transforms the government's role from service provider to market architect — creating the conditions for competition and innovation rather than attempting to deliver end-user services directly.
The Multiplier Mechanism: Why DPI Exceeds Traditional Infrastructure Returns
Traditional physical infrastructure — roads, bridges, ports — generates economic multiplier effects in the range of 1.5–2.5x per IMF estimates. Every dollar invested in a highway generates $1.50–$2.50 in economic activity through improved market access, reduced transportation costs, and agglomeration effects. This is the benchmark against which DPI returns must be measured.
DPI exceeds traditional infrastructure multipliers dramatically, and the mechanism is rooted in three fundamental economic properties.
First, the marginal cost of an additional user approaches zero. Once a digital payment rail is built, adding the 100 millionth user costs essentially the same as adding the 10 millionth. Physical infrastructure exhibits no such property — each additional kilometer of highway requires proportional material and labor inputs. This zero marginal cost structure means that DPI investment costs are largely front-loaded, while benefits scale with adoption in a near-linear fashion.
Second, network effects create superlinear value growth. Metcalfe's Law posits that the value of a network scales with the square of the number of connected users. While empirical research suggests the exponent may be somewhat less than 2 (Briscoe, Odlyzko, and Tilly, 2006), the fundamental insight holds: each additional participant in a DPI ecosystem increases the value for all existing participants. A merchant accepting UPI payments becomes more valuable as more consumers use UPI, and vice versa — the classic two-sided market dynamic.
Third, DPI enables market creation in previously informal sectors. This is perhaps the most economically significant mechanism. When transaction costs fall below the threshold required for market participation, entire populations and economic sectors shift from informal to formal activity. This is not merely a transfer of existing activity into digital channels — it represents genuine economic expansion through improved allocative efficiency.
India's Economic Survey 2024 estimates that UPI has saved the Indian economy $67 billion in transaction costs cumulatively since its 2016 launch. These savings represent not just efficiency gains but freed-up capital that has been redeployed into productive economic activity.
Case Study: India's Unified Payments Interface (UPI)
India's UPI represents the most comprehensively documented DPI success story. Launched in April 2016 by the National Payments Corporation of India (NPCI), UPI grew from zero to 14.8 billion monthly transactions in nine years — a trajectory without precedent in financial infrastructure history.
UPI's architectural design choices were decisive. Open APIs allowed any licensed entity to build payment applications, creating competition among front-end providers (PhonePe, Google Pay, Paytm, and over 300 others) while maintaining interoperability through the shared NPCI backbone. Zero merchant discount rate (MDR) for small-value transactions eliminated the cost barrier that had prevented merchant adoption of card-based payments. Real-time settlement — transactions clear in under 10 seconds — provided immediate liquidity that cash-dependent merchants and consumers demanded.
The measurable economic impacts are substantial. Direct benefit transfer savings represent the most rigorously quantified impact: the Indian government's shift from cash-based subsidy distribution to Aadhaar-linked direct bank transfers eliminated intermediary leakage estimated at $33 billion cumulatively, according to World Bank analysis. These savings came not from reducing benefits to recipients but from removing ghost beneficiaries and corrupt intermediaries from the distribution chain.
Merchant digitization has transformed India's small business landscape. Reserve Bank of India survey data indicates that small businesses accepting digital payments saw revenue increases of 20–30%, driven by expanded customer reach, reduced cash handling costs, and access to formal credit markets enabled by digital transaction histories. The number of merchants accepting UPI grew from fewer than 1 million in 2017 to over 100 million by late 2025.
The multiplier calculation for UPI is striking. Total investment in UPI infrastructure — including NPCI development costs, bank integration expenditure, and government subsidies for merchant terminals — is estimated at approximately $1.5 billion over nine years. The annual economic value generated, including transaction cost savings, merchant revenue gains, financial inclusion benefits, and reduced subsidy leakage, is estimated at $17–23 billion. This yields an annual multiplier of 9–15x on cumulative investment — and the ratio continues to improve as fixed costs are amortized over an expanding user base.
Case Study: Brazil's Pix Instant Payment System
Brazil's Pix provides a compelling counterfactual to the argument that DPI success is uniquely Indian. Launched by the Central Bank of Brazil (Banco Central do Brasil) in November 2020, Pix reached 170 million registered users by 2025 in a country of 215 million — a penetration rate exceeding 79% of the total population and virtually 100% of the banked adult population.
Pix's adoption velocity exceeded even UPI's trajectory. Within its first year, Pix processed more transactions than Brazil's combined credit and debit card networks. By 2024, Pix accounted for over 45% of all electronic payments in Brazil. The Central Bank attributes this rapid adoption to three design decisions: mandatory participation by all licensed financial institutions (eliminating chicken-and-egg network adoption problems), 24/7/365 real-time settlement, and zero cost for individuals and micro-merchants.
The financial inclusion impacts are particularly significant. Central Bank of Brazil data show that approximately 40 million previously unbanked Brazilian adults gained access to the formal financial system through Pix-linked accounts — many opened specifically to access Pix services. This represents one of the largest financial inclusion expansions in Latin American history, achieved in under three years and at a fraction of the cost of traditional bank branch expansion.
For small and medium enterprises, Pix dramatically reduced payment acceptance costs. Card-based payment processing in Brazil historically carried merchant fees of 2.0–2.5% per transaction. Pix reduced this to effectively zero for small merchants, representing a direct margin improvement that the Brazilian Micro and Small Enterprise Support Service (SEBRAE) estimates boosted small business profitability by 8–15% on average.
The working capital impact has been equally transformative. Traditional card and boleto (payment slip) settlement in Brazil took 2–30 days. Pix's real-time settlement released an estimated $12 billion in working capital that had previously been trapped in settlement float across the SME sector. For cash-constrained small businesses, this liquidity improvement reduced reliance on expensive short-term credit — a significant factor in an economy where commercial lending rates frequently exceed 30% annually.
Case Study: Kenya's M-Pesa and the Mobile Money Ecosystem
Kenya's M-Pesa, launched by Safaricom in 2007, represents the earliest large-scale DPI success and provides the longest time series for studying economic impacts. While M-Pesa is a private-sector platform rather than a government-built system, it functions as de facto public infrastructure: M-Pesa processes transactions equivalent to approximately 65% of Kenya's GDP, and its agent network of over 300,000 locations provides financial access points that vastly exceed the country's bank branch network.
The most rigorous academic evidence for DPI's poverty reduction impact comes from Kenya. Tavneet Suri and William Jack's landmark 2016 study published in Science used a longitudinal dataset spanning nearly a decade to demonstrate that M-Pesa access lifted approximately 194,000 Kenyan households — 2% of the national total — out of extreme poverty. The mechanism they identified was precise: reduced transaction costs enabled market participation for previously excluded populations, increasing allocative efficiency across labor, goods, and financial markets.
Specifically, Suri and Jack found that M-Pesa access increased per-capita consumption by an average of $4.70 per month for households near M-Pesa agents — a 5.6% increase. The effects were concentrated among female-headed households, suggesting that mobile money disproportionately benefits populations facing the highest barriers to formal financial access. The poverty reduction mechanism operated through occupational shifts: women in areas with M-Pesa access were 9.2 percentage points more likely to move from subsistence agriculture into business or retail occupations.
Kenya's mobile money ecosystem has since expanded beyond payments into credit (M-Shwari, KCB M-Pesa), savings (M-Shwari lock savings), insurance (M-TIBA health insurance), and cross-border remittances. This ecosystem demonstrates a critical feature of DPI: initial payment rails serve as a foundation upon which increasingly sophisticated financial services can be built, each layer compounding the economic multiplier of the original infrastructure investment.
The Investment Gap and Policy Recommendations
Despite the demonstrated returns from DPI investment in India, Brazil, and Kenya, the majority of emerging and developing economies lack functional DPI systems. The World Bank estimates a global DPI investment gap of $200–400 billion — the capital required to build identity, payment, and data-sharing infrastructure across countries that currently lack these systems.
This investment gap persists for identifiable structural reasons. DPI exhibits classic public goods characteristics — non-rivalrous and partially non-excludable — which means private markets systematically underinvest. The returns to DPI accrue broadly across the economy rather than to the investing entity, creating a gap between social and private returns that discourages private capital. Additionally, the coordination challenges inherent in building two-sided markets create chicken-and-egg adoption problems that require patient, long-horizon capital — the type that commercial investors typically avoid.
Three policy recommendations emerge from the evidence:
1. Establish multilateral DPI investment funds modeled on climate finance mechanisms. The Green Climate Fund and similar vehicles demonstrated that blended finance structures — combining concessional public capital with commercial private investment — can mobilize resources for high-social-return, long-horizon infrastructure. A dedicated DPI fund of $50–100 billion, structured as a first-loss facility to de-risk private investment, could catalyze $200+ billion in total DPI deployment across 50–80 countries over a decade.
2. Develop open-source DPI reference architectures building on India Stack's example. India's decision to open-source key components of its DPI stack through the MOSIP (Modular Open Source Identity Platform) initiative has already enabled countries including Morocco, the Philippines, and Ethiopia to deploy digital identity systems at a fraction of the cost of building from scratch. Expanding this approach to payment rails and data-sharing frameworks could reduce DPI deployment costs by 60–80% for adopting countries, according to estimates from the Centre for Digital Public Infrastructure.
3. Create regulatory sandboxes for DPI experimentation. Brazil's Central Bank demonstrated the value of regulatory flexibility by designing Pix's framework iteratively, incorporating feedback from a controlled pilot phase before national rollout. Regulatory sandboxes — controlled environments where DPI systems can be tested with real users under relaxed compliance requirements — allow countries to experiment with DPI designs without committing to a single architectural approach prematurely.
Implications for GDEF
The Finance & Economy Working Group occupies a critical position in the global DPI landscape. As a multi-stakeholder forum spanning governments, multilateral institutions, private-sector technology providers, and civil society organizations, GDEF is uniquely positioned to facilitate the knowledge transfer and coordination that DPI deployment requires.
Three specific roles are warranted. First, DPI investment advocacy: the empirical evidence presented here — 9–15x multiplier effects, documented poverty reduction, measurable financial inclusion gains — constitutes a compelling investment case that the Working Group can present to finance ministers, multilateral development banks, and institutional investors. Second, technical standards coordination: interoperability across national DPI systems will be essential as cross-border digital trade expands, and GDEF's convening authority can facilitate the standards harmonization process. Third, knowledge transfer facilitation: the operational lessons from India, Brazil, and Kenya — architectural design choices, regulatory frameworks, adoption strategies, and failure modes — represent invaluable institutional knowledge that the Working Group can systematize and disseminate to countries at earlier stages of DPI development.
The Finance & Economy Working Group's forthcoming DPI Economics Initiative will develop detailed implementation playbooks based on the analytical framework presented in this report, with targeted recommendations for presentation at the 2026 GDEF Annual Summit.
References & Sources
- World Bank, The Global Findex Database 2024: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. worldbank.org/en/publication/globalfindex
- Reserve Bank of India, Annual Report 2024-25. rbi.org.in/Scripts/AnnualReportMainDisplay.aspx
- Banco Central do Brasil, Pix Statistics. bcb.gov.br/estabilidadefinanceira/estatisticaspix
- GSMA, State of the Industry Report on Mobile Money 2025. gsma.com/mobilemoneymetrics
- NPCI, UPI Product Statistics. National Payments Corporation of India. npci.org.in/what-we-do/upi/product-statistics
- Suri, T. & Jack, W. (2016). "The Long-Run Poverty and Gender Impacts of Mobile Money." Science, 354(6317), 1288–1292. doi.org/10.1126/science.aah5309
- Rochet, J.-C. & Tirole, J. (2003). "Platform Competition in Two-Sided Markets." Journal of the European Economic Association, 1(4), 990–1029. doi.org/10.1162/154247603322493212
- Government of India, Economic Survey 2023-24: Chapter 4 — Digital Public Infrastructure. Ministry of Finance. indiabudget.gov.in/economicsurvey
- MOSIP (Modular Open Source Identity Platform). mosip.io
- World Bank, ID4D Global Dataset: Identification for Development. id4d.worldbank.org/global-dataset