In my experience leading Top Tier Impact, the reason for this gap is almost never risk appetite or return expectations. And it’s not due to the much-discussed “lack of an investable pipeline.”

The Myth of the Deal Flow Problem

According to many funders, a common reason why impact capital does not reach low- and middle-income countries (LMICs) fast enough is that there is a lack of investable deal flow. Yet the pipeline of investable businesses exists. What I see missing is the connective tissue: networks of trusted, embedded practitioners who can surface credible opportunities, do meaningful due diligence, and bridge the enormous information asymmetry between a capital allocator in London or Singapore and a founder in Dakar or Nairobi.

This asymmetry is not just financial. It is mostly relational, cultural and reputational. An investor who has never operated in a country or region cannot easily evaluate a fintech business there. It is difficult to assess from a distance which local regulators are genuinely open to new models, whether a founder’s claimed traction holds up in practice, or which institutional relationships actually influence outcomes. Without someone who knows the answers to these questions and is trusted by both sides, deals either do not happen — or they run into avoidable problems after investment, such as governance breakdowns, unrealistic growth plans, weak reporting and misaligned incentives.

This asymmetry rarely fixes itself. When capital continues to flow through familiar geographies and established intermediaries, high-quality entrepreneurs outside those networks remain systematically harder to discover and fund. That’s why, in my view, the real leverage comes from building these trust networks: the practitioners, connectors and market insiders who know which opportunities are real, which teams can execute, and how to bring the right parties into the same room.

What Trust Networks Actually Do

Trust networks consist of people with direct operating experience whose judgment has been tested over time. They are not simply networks of contacts. They function through repeated interactions, reputation and contextual knowledge: who has actually built in a market, which founders have what it takes to succeed, which investors behave constructively when things go wrong, and which risks matter locally but may not appear in a data room. Because participants put their own credibility behind introductions, these networks themselves become a form of filtering and due diligence. Their mechanics therefore look different from conventional intermediation through bankers, advisers or structured processes. Three patterns stand out.

First, active trust networks surface opportunities that never enter formal sourcing channels. Some of our most compelling deals over the past five years at Top Tier Impact came not from investment banks or pitch competitions but from informal referrals within practitioner communities. Many investable businesses sit outside the channels institutional investors typically use to source deals. An energy transition business in East Africa may never appear in a conventional sourcing pipeline, yet it may be well-known to practitioners who have worked alongside its team for years. The same is true in agricultural finance, where the strongest opportunities are often visible first to people who understand local credit cycles, land structures and cooperatives.

Second, trust networks compress due diligence timelines. When a credible network member with direct market knowledge vouches for an entrepreneur, investors can move faster and more confidently. That referral is a form of pre-validation that no financial model can replicate. In markets where windows close fast and founders have options, speed is a competitive advantage.

Lastly, trust networks create ongoing accountability, as the relationships within them tend to continue beyond the transaction itself. This accountability is often more personal and reputational than contractual, because future access depends on how participants behave over time. That changes the dynamic in ways that reduce post-investment friction considerably. When something goes wrong in a portfolio company (and something always does), having trusted practitioners in the local market who are invested in the outcome is worth more than most contractual protections. They provide an independent read of the deal that neither side can provide about itself objectively.

What Becomes Possible When Trust Infrastructure Works

Wave Mobile Money is one of our clearest examples of what happens when trust infrastructure actually works.

Founded in Senegal in 2018, Wave set out to do something most investors considered untenable: offer mobile money with 1% transaction fees in West Africa, aggressively undercutting Orange and MTN, whose transfer fees were roughly 6–10% at the time. To provide early institutional backing, potential investors such as development finance institutions (DFIs) had to adapt their domain focus.

Historically, DFIs have deep expertise in physical infrastructure (e.g., roads, energy grids, water systems, etc), which is where their risk frameworks were calibrated, their technical assistance teams had experience, and their boards felt comfortable. Digital financial infrastructure is a genuinely different category: intangible, fast-moving, and dependent on user behaviour change rather than engineering specifications. Those differences are important because the risks of digital finance are harder to underwrite with traditional infrastructure frameworks: adoption, distribution, regulation and network effects can matter more than physical asset quality or engineering performance. With a new category comes the need to assess a different set of risks and rewards.

Bridging this gap took more than a compelling model. We were among the advisers on Wave’s €90 million debt round arranged by the International Finance Corporation in 2022, which brought in a syndicate including Symbiotics, Blue Orchard, responsAbility, Lendable, Finnfund and Norfund. The round was significant not just in size but in what it represented: one of the largest institutional debt financings for an African fintech at the time, demonstrating the growing appetite of international lenders to finance digital financial infrastructure in West Africa.

This followed Wave’s landmark 2021 Series A, when the company became francophone Africa’s first unicorn at a $1.7 billion valuation. Today it has millions of users across nine African countries, has launched a full commercial bank in Côte d’Ivoire, and closed a further $137 million debt round in 2025 backed by British International Investment, Finnfund and Norfund.

The value of trust infrastructure in our efforts to help secure debt funding for Wave came from combining local context and trusted introductions with the lenders’ own underwriting processes, so they could assess the opportunity with a fuller picture. As this experience illustrates, trust networks don’t replace due diligence, but they make it more informed and easier to verify.

What Investors Can Do Differently

If you manage capital intended for LMICs — whether at a DFI, an impact fund or a family office — the most useful thing you can do before your next deployment cycle is to audit your network. Not your deal-sourcing pipeline, your actual network.

Ask yourself: Do we have trusted relationships with practitioners who have operated, not just invested, in the markets we are targeting, people who have built or scaled something there and who hold genuine credibility among local founders and regulators?

If the answer is no, that is the gap to close first. Capital without context is not impact investing. It is speculation with good intentions.

However, this is not an argument against financial rigour. It is about recognising that financial rigour alone is insufficient in markets where information is scarce and trust is a real currency. The investors who generate both returns and impact in LMICs don’t rely only on sophisticated financial modelling; they spend years building the relationships that reveal which businesses are primed for growth, and how best to support them.

The Need to Fund Trust Infrastructure

The impact investing community has spent the last decade debating topics like blended finance structures, concessional capital and first-loss tranches. These tools are valuable, but they work best when they sit on top of genuine trust infrastructure. And often, that part of the equation gets no dedicated resource allocation.

That’s why the sector needs to mobilise funding for building, convening and sustaining practitioner communities, and for generating the kind of on-the-ground intelligence that formal due diligence processes were never designed to capture. In markets where information asymmetry is the primary risk factor, these costs would be doing the same work as any other line in the investment budget.

Funding trust infrastructure also means being honest about the limits of what formal analysis can reveal. The gap between global capital and LMIC opportunity is partly a product of overconfidence. Investors assume that sophisticated financial analysis travels. It does not, not without context. The local people who know these markets best are usually not in the room when capital allocation decisions are made. Getting them into that room consistently, and treating trust as essential infrastructure, is the structural fix that makes everything else work.

Alessa Berg is the founder and CEO of Top Tier Impact.

Photo credit: Jacob Wackerhausen

Those are some of the questions at the heart of a new book, “The Impact Entrepreneur Breakthrough: A Field Manual for the Regenerative Economy,” by Laurie Lane-Zucker, the founder and CEO of Impact Entrepreneur, a global media platform and network with more than 70,000 members in over 200 countries.

In the interview below, he shares guidance from the book — and from his decades of work as a pioneering voice in the impact space — on how the sector can navigate the growing complexity of the global challenges it faces today.

1. After 15 years of running Impact Entrepreneur — on top of a noteworthy career working for social change — what made you decide to write this book, at this historical moment? What do you hope the book will accomplish?

Laurie Lane-Zucker

Two things came together, one in the world and one in the field.

In the world, the crises stopped taking turns. A drought becomes a food crisis, then a displacement crisis, then a security crisis, and institutions designed to handle one emergency at a time keep arriving late to all of them. I’ve come to see these as symptoms of a single design failure, an economy organized around extraction. A failure with a common root can be redesigned, which is why this became a book about design.

In the field, the work had matured. When I coined the term “impact entrepreneur” in 2011, I was naming something that was just emerging. Fifteen years on, there are enough working models, tools and hard lessons to fill a field manual. Much of that knowledge was scattered, though. It lived in case studies and legal templates, and in the heads of founders who learned what a bad term sheet costs by signing one. Publishing their stories for many years showed me how often the same lessons were being learned twice. I wanted to gather them in one place.

What I hope the book accomplishes is a change in the first question people ask of an enterprise or a fund. Today that question is usually some version of “How much good does it do?” I’d like it to become “What keeps it doing good when the founder leaves, the capital changes hands or the market turns?” If that becomes a routine question in boardrooms, investment committees and classrooms, the book will have done its work. It’s being taught this fall at NYU Stern, Parsons School of Design, and Wesleyan, which is a good place to start.

2. You’ve framed the book as “a field manual for the regenerative economy”: What makes it a “field manual” — and if you had to distill its guidance for impact entrepreneurs into a couple of key pieces of advice, what would they be?

It’s built to be used, and used out of order, by people who are already in the field and have no time to read cover to cover. Each of the 16 chapters ends with a tool kit, a set of exercises a team can run on its own enterprise. We turned those into 18 printable canvases, 17 chapter canvases plus a cross-cutting Impact Diligence Canvas, and put them on our site for free. The same goes for an implementation roadmap that opens with a 10-minute diagnostic and then lays out 90-day sprints for founders, investors, policy professionals and cultural workers.

If I had to distill the guidance into two pieces of advice, they would be these:

• Put the mission in the structure. Values that live in a founder’s head leave with the founder. Values written into ownership, governance and capital terms stay put. Chapter 5 closes with the questions I’d put to any founder, anywhere, before a term sheet is signed. Who controls the board? Who benefits from the value created? Who bears the risk? And underneath all three, the question that decides the rest: Do our capital terms entrench power, or share it? The William Davidson Institute and Acumen’s Founders in Focus survey asks entrepreneurs what happened to them after they signed. These questions ask what they might have refused first.
• See the system before you design for it, and then pull one lever all the way. Trace the problem back a few causes before building anything, and choose the cause your enterprise can actually change. When the whole book feels like too much, the roadmap offers the same advice I’d give in person: Pick one tool kit and finish it.

3. In the book and your broader work, you distinguish between “impact entrepreneurship” and “social entrepreneurship.” If I can paraphrase your thinking, you view “social entrepreneurship” as something that aims to address the consequences of the world’s extractive economic systems, whereas “impact entrepreneurship” aims to redesign those systems to be regenerative rather than extractive. Can you provide an example of each approach that helps illustrate these different concepts?

Your paraphrase is close to how I’d put it. I’d add one refinement: The two often work on the same problem, and the difference shows up in the structure of what they build.

The book uses a simple pair. Two entrepreneurs see food insecurity in the same community. One opens a food bank. It depends on donations, hands out whatever food is available and succeeds by serving more people each year, while the causes of the hunger stay put. The other maps those causes, from low wages to a neighborhood with no grocery store, and starts a worker-owned grocery cooperative there. It buys from local regenerative farms, pays a living wage and is owned so that the community controls its access to food permanently. It succeeds as the community becomes more food sovereign. Both founders mean well, and both work hard. Only the second changes the conditions that created the need.

Microfinance holds both approaches in a single story. The book opens its first chapter with Grameen Bank because Grameen redesigned the whole architecture of lending, starting with ownership: The bank is owned largely by its borrowers. The group-lending method spread around the world. The ownership design spread far less. Where the product traveled without the ownership, some lenders drifted toward the very extraction microcredit was invented to answer, and borrowers bore the cost.

None of this diminishes social entrepreneurs. I was one, and many of the people who built that field went on to build this one. Most enterprises move along the spectrum over time, as mission shifts from a discretionary gesture to a structural commitment. The useful question to ask of any of them is which way they’re moving.

4. A similar distinction has emerged in impact investing, where the market seems to be segmenting itself into “impact-first” and “finance-first” investing, based on the investor’s willingness to prioritize impact over financial returns. Do these distinctions reveal a schism of sorts in the impact sector, where some are content operating within the traditional economic system and its typical practices, while others aim to build something fundamentally different? If so, do you view this as a positive or negative development?

The labels describe something real, an investor’s willingness to trade financial return for impact, and they help founders find the right money. I’d resist reading them as a schism, for two reasons.

The first is that the two kinds of capital need each other. Much of the most useful money in emerging markets arrives as a stack. Philanthropic or concessional capital takes the first loss, which makes the risk tolerable for commercial investors who would never have come in alone. That’s how blended finance works: Impact-first and finance-first capital in the same deal, each doing the job it suits.

The second is that the return spectrum leaves out the variable I care about most. An impact-first investor can still demand board control, liquidation preferences and a fast exit, the terms that hollow out missions. A finance-first investor can earn a solid return from a steward-owned company whose voting rights stay in trust, protected from sale. The line I watch runs through the terms themselves: Do they share power or entrench it? That’s the ground the Founders in Focus survey covers from the founder’s side of the table, and I’m eager to see what it finds.

Whether the segmentation is healthy depends on honesty. Clear labels help, because founders deserve to know what kind of money they’re taking. The trouble starts when “finance-first” becomes a way to keep the impact label while dropping the substance, and when the patient, risk-absorbing work is left to a small pool of concessional capital. The GIIN’s 2025 State of the Market found most of the impact assets it surveyed going to high-income regions. The places NextBillion’s readers work need more capital willing to sit at the bottom of the stack, and much less argument over which label is purer.

5. However you define it, it has become clear that the impact sector isn’t growing nearly as fast as the problems it aims to address. With rising inequality, an escalating climate crisis, democratic backsliding, ongoing geopolitical conflicts, and the economic and workforce disruptions of AI, among other worsening challenges, how much time do we realistically have to turn things around? If you were an investor or other funder with the appropriate sense of urgency, where would you focus your funding right now?

I’m wary of countdowns. Some thresholds won’t wait for us, in the climate above all, and I take them seriously. But a deadline tends to produce panic or paralysis, and neither one builds anything. What I’m sure of is that delay compounds. These crises feed one another, so every year spent reacting makes the next one more expensive.

That’s the logic behind what the book calls the Prevention Dividend™, the return on addressing causes before they become emergencies, and the evidence for it is strong. Ecosystem restoration returns $7 to $30 for every dollar invested. Early childhood education yields a 7 – 13% annual rate of return. Pandemic preparedness averts an estimated $1,102 in losses to the US economy for every dollar spent. Few investments in any portfolio or public budget perform like that, and few are so consistently underfunded.

With the right sense of urgency, I’d put money in four places. I’d start with prevention where exposure is highest: watersheds, mangroves and soils, community health workers, early childhood programs, early-warning systems. That is also where the money is thinnest. To take one example of this approach, African Risk Capacity, a specialized agency of the African Union, pools drought risk across member countries. When the rains fail, payouts arrive within weeks, early enough to act before families are forced to sell what they own.

Then I’d look at ownership. As founders retire and AI reshapes work, who owns productive assets will decide whether the gains spread or concentrate, and conversions to employee and community ownership deserve far more capital than they get.

Alongside them I’d back patient local lenders, meaning community lenders, savings cooperatives and the funds behind them, which can underwrite on relationships where an algorithm sees only risk.

Last, I’d focus on measurement that makes prevention visible to the people who set budgets. We built a public Prevention Ledger for that purpose, and it should be one tool among many.

6. What are your thoughts on the performance of the impact sector’s leaders over the past few years: Do you think they’ve met the moment? If not, what would you like to see these leaders do differently — and what can the rest of us do if we see our own leaders straying from the missions or principles we thought we were working toward?

Partly. The last decade produced real infrastructure: more than 10,000 Certified B Corps, benefit corporation laws in most US states and in countries from Italy to Colombia, shared standards for measuring impact, and a generation of funds with impact written into their mandates. People built those things against resistance, and I don’t want to wave them away.

Where leadership fell short, in my view, was on durability. We got very good at measuring what enterprises do and paid far less attention to who controls them, or to what happens to a mission when a company is sold or a fund needs its exit. And too many recent commitments took the form of pledges. A pledge costs little to make and less to drop, and when the mood around them shifted, a good many were dropped.

What I’d ask of leaders is easy to say and hard to do: Write commitments down where they bind. Put them in the bylaws, the partnership agreement and the ownership structure. We try to hold ourselves to that at Impact Entrepreneur. We’re a public benefit corporation, and our founding documents give a golden share veto power over mission-related decisions.

Everyone else has more say than they use. Employees, members, limited partners, grantees and customers can all ask structural questions out loud. What happens to the mission if this company is sold? Who sits on the investment committee? Does the endowment invest in line with the grants? Ask before a crisis, while the answer can still change something. And when a leader you trusted starts to drift, look at the structure before you look at the person, because drift usually starts where the design left room for it.

7. As the proprietor of one of the pioneering impact media publications, how do you view the role of media in perpetuating, and perhaps addressing, the global polycrisis? What should impact media publications be doing differently to respond to these overlapping challenges? Should impact sector funders be playing a larger role in supporting impact media — or even building or buying mainstream media outlets to help amplify the sector’s key messaging and mobilize public opinion around these issues?

I should declare an interest, since I run one of these publications.

Media shapes the polycrisis in two ways. One is the business model. Much of the attention economy earns more from outrage than from understanding, and its algorithms reward the story that inflames over the one that explains. The book treats attention as a commons, the shared cognitive infrastructure a society needs to deliberate and act, and it treats the erosion of that commons as a security problem. The other is form. News is organized around events, so crises get covered one at a time, and the successes of prevention, which are non-events by design, rarely get covered at all.

Impact media can do better on both counts. We can report on structure as seriously as we report on founders: ownership, terms, governance, and what became of the mission five years after the celebrated launch. We can be as skeptical of our own sector as of anyone else’s, because impact-washing does this field more damage than any critic. And we can build business models that reward depth, where readers pay for fewer, better stories.

Funders should play a larger role, provided they fund independence. Multi-year general operating support, with a clear wall between the money and editorial decisions, is worth more than any campaign grant. Media literacy deserves support too. Finland built it into its national curriculum from primary school through university, and it has held or shared first place in every edition of Europe’s Media Literacy Index.

I’d be much more careful about buying outlets to amplify the sector’s messaging. An outlet bought to carry a message loses the trust that made it worth buying. If funders want to own media, the book’s argument about ownership applies: Use structures that protect independence. The Guardian has been owned since 1936 by the Scott Trust, which was created to shield the paper from interference by future owners. That’s a form of media ownership I’d be glad to see funders copy.

James Militzer is the managing editor of NextBillion.

Main photo credit: ismagilov

Photo of Laurie Lane-Zucker: Christina Rahr Lane

That raises a harder question: What would infrastructure-grade redress actually require?

Every service needs a way to fix mistakes, but DPI raises a distinct version of the problem. A single user’s identity, payments and data are handled by separate institutions, so one failure can cascade — and even national DPI systems with strong complaints systems, like Brazil’s and India’s, are not built to track and resolve these intertwined issues across government agencies and tech platforms. Making this issue even more complex, DPI activity is increasingly extending across national borders, bringing multiple governments and their relevant processes, contractors and agencies into the picture.

Over the past several months, we at Integral, with our partners in-country, have explored this challenge in a research project supported by the Gates Foundation. We examined grievance redress mechanisms for 15 DPI systems in Brazil, India, South Africa, Benin and Ethiopia, spanning instant payment systems, digital identity systems and data exchange platforms. Our methods combined public-document review, “mystery shopping”-style market research of complaint channels, and interviews with operators and other stakeholders.

The research showed whether these mechanisms are operational and how well they function. But it also revealed a fundamental binding constraint: Redress has a standardization problem, since interoperability — the characteristic that makes DPI a type of infrastructure rather than merely a collection of unconnected digital services — largely stops when something goes wrong.

A stack with a missing bottom half

Think of the standards for grievance redress as a four-layer stack. At the top are principles: what a good grievance mechanism should achieve. Next come policy and governance: who is responsible, what rights users have and what obligations providers face. Then come semantics and structure: the language, categories and data structures used to describe a grievance. Finally comes measurement: the indicators that tell us whether redress mechanisms are functioning, and how well.

At the principles layer, our research found substantial international agreement on a number of key priorities that should underlie grievance redress. For example, the International Organization for Standardization (ISO) has published standards that include ISO 10002 on complaints handling and the newer ISO 32122 on online dispute resolution in e-commerce. The World Bank’s guidance on grievance mechanisms for social protection uses different language, but all these sources converge on several core principles for redressal, including accessibility, fairness, confidentiality, transparency, responsiveness and timeliness.

At the policy and governance layer, we found greater divergence among different countries’ approaches — something that is unsurprising and probably unavoidable. In the five countries studied, legal rights to redress for public services generally exist. But the mechanics are usually left to the discretion of individual DPI entities, and there are gaps in the definitions of which services are covered by public sector redress: for example, if government payments are delivered by private-sector providers, or if there’s involvement by a government agency (like a central bank) that is not classed as providing a public service.

In the bottom half of the stack, at the semantics and structure and measurement layers, we found something more consequential. There is very little common semantic infrastructure (i.e., shared vocabularies, taxonomies and data dictionaries) for grievances, and even less standardized measurement. In other words, even though different countries increasingly agree about what good redress should mean, they lack a common way to describe what actually went wrong. That makes even basic comparison surprisingly difficult for the financiers, government oversight agencies or other entities that aim to assess these systems’ performance and coordination.

One citizen, many systems

To better understand how this lack of standardization impacts DPI users, consider someone whose identity credentials have been compromised. A fraudster uses them to open or take control of a financial account and steal the victim’s money through an instant payment rail provided via DPI. The victim discovers the loss and complains to the government, since DPI was used to establish her identity and transfer the money.

From her perspective, this theft is a single event. But institutionally, it may involve an identity authority, a private sector bank or fintech, a payment operator, a regulator, the police, and perhaps an ombudsman. Our fieldwork repeatedly exposed an underlying feature of the public’s use of DPI: Citizens experience these systems as integrated digital journeys, while the institutions that manage them retain separate mandates, databases and complaint channels. This can become problematic, as a grievance that starts in one DPI system may impact another. For instance, an error in a digital identity system can cause a denied welfare payment, while wrong information passed through a data exchange can produce a service denial elsewhere, or even an unwanted loan. Resolving only the downstream event may leave the upstream problem untouched.

This is the kind of problem interoperability is supposed to solve, without merging mandates or changing national architectures. Yet today, the information needed for redress often cannot travel with the problem.

Start by agreeing on categories for recurring grievances

The first step in addressing this challenge need not be the development of an elaborate technical standard like an ISO standard. It could be simply to frame a common meta-taxonomy of grievances. Payment systems, digital identity and data exchanges generate different complaints; for instance, a failed biometric authentication is not the same as a failed payment. But we found considerable alignment one level higher, among the broader types of failures DPI users commonly encounter. Across all three types of DPI, grievances can be grouped around recurring categories: access and availability failures; erroneous outcomes; downstream harm or denial of service; time-sensitive or hard-to-reverse outcomes; consent and user-control problems; misuse of data; fraud and impersonation; difficulty correcting errors; and failures in redress or appeal itself.

It’s important to strike a balance between useful standardization and over-standardization at this category level, where there may be a need for more flexibility and potential changes. Sub-codes would remain DPI system-specific. Common parent categories would make it possible to aggregate, analyze and route grievances without pretending that all DPIs are identical. Financial regulators and private-sector payment card networks like Visa and Mastercard already use structured complaint categories and reason codes, which allow complaints to be tagged and organized so they can be triaged and tracked — but these are sectoral or proprietary and cannot currently travel between ecosystems. DPI needs something more horizontal.

Moving beyond categories to create a common data object for grievances

The next, more ambitious step is to standardize not just the category of a grievance but the data object that represents it. A common grievance data object might include the category and sub-category; complainant details where necessary; whether and how the complainant was authenticated; the system or transaction concerned; time and date; a case number or code that remains consistent across DPIs; the organizations that have handled the case; the current escalation level; and status and eventual disposition.

In DPI, the purpose of interoperability is to standardize the basis which allows a flow of data between systems, not the process or the entity responsible for delivering the public service. Every DPI system or government institution need not run the same complaints platform or follow an identical legal process. The goal is not a global mega-ombudsman for DPI, which even if feasible would likely be ineffective. It is closer to what messaging standards have done elsewhere in the digital economy: letting different systems understand enough of the same structured message to act on it.

India’s Open Network for Digital Commerce offers an instructive example. Its Issue and Grievance Management framework includes a 25-field data dictionary for complaints emerging across a multi-party e-commerce network. The reason codes are specific to e-commerce, which is not widely recognized as a category of DPI, but the underlying idea — a structured grievance data object that moves between organizations — is widely applicable to DPI. Open-source systems such as DIGIT and open protocol environments such as Beckn offer other building blocks.

These are all promising signs of progress, but they’re at a relatively early stage. To advance redress for DPI as a whole, the next step DPI operators, funders and system vendors should take is to create a data dictionary defining a common data object for grievances. The most important design priority is ensuring users’ privacy, because a grievance about identity theft or a benefit denial is itself sensitive information that shouldn’t be shared. The grievance object should carry references and status information rather than evidence, record the authentication level (i.e., how robustly and with which digital ID the person identified themself) rather than their specific personal details, and show each institution involved in redressing the grievance only what it is entitled to see.

Measurement and interoperability reinforce each other

We approached this problem initially from the bottom of the stack: measurement. We developed two experimental lenses to envision how various potential solutions could be applied to different real-world DPIs/grievance redress systems. The “liveness” measure asks whether a DPI has the minimum observable characteristics of a functioning grievance mechanism. Only four of the 15 systems met every criterion, although another eight were substantially underway. A richer “wellness” framework examines how fit-for-purpose a mechanism is, but it requires far more information from operators and was beyond the scope of this phase of the project.

The exercise revealed an opportunity for DPIs to create a beneficial feedback loop (something some of these systems have already implemented). Better measurement creates pressure for common definitions: We cannot compare grievance resolution rates if “complaint,” “dispute,” “fraud case” and “chargeback” mean different things in different systems. And semantic standardization makes better measurement possible. Eventually, comparable grievance data could show governments not merely whether a complaint channel exists, but where harms originate, where cases get stuck between institutions, which groups struggle to obtain remedy, and which system changes reduce repeat grievances. Complaint data then becomes not simply evidence of failure, but telemetry for the DPI itself.

Measurement matters for another reason. Redress failures rarely originate due to technical problems: These failures more often emerge from a lack of quality management at DPI systems, born of lack of knowledge, limited vision and, frankly, no reward for doing better.

Public, comparable scorecards could change the incentives that result in poor quality DPI management. This approach remains rare, and we’ve only encountered it in an embryonic form in India, in the country’s Grievance Redressal Assessment Index. Built on Centralized Public Grievance Redress and Monitoring System data, the Index allows the government to independently rank grievance redressal across different national public services based on transparent and independently collated metrics — though it doesn’t cover all forms of DPI. Nevertheless, it represents a promising step toward greater transparency and accountability in public services, since politicians, civil society and the general public can also monitor it. These types of shared conventions will not create quality government services, but they do make these services visible and comparable when they exist.

Making grievances legible to one another

The need for interoperability is growing as DPI crosses borders. National instant-payment systems are interconnecting, users’ credentials are being designed for recognition abroad, and data exchange will follow. Yet cross-border interoperability is being engineered faster than cross-border redress. Formal international standards may eventually be needed here, but they are not the right place to start. Instead, DPI grievance redress systems should move toward standardizing their operating conventions across countries, beginning with DPI operators and the vendors of the case-management systems they use within individual countries — something that doesn’t require formal, whole-of-government approval.

The first generation of DPI interoperability focused on building society-scale digital systems that can transact — whether that transaction involves data or payments. The next must ask: When a transaction goes wrong, can information about the problem travel across DPI systems until the issue is resolved? The global movement toward DPI does not need a single redress institution or identical national rules. But it does need a shared vocabulary, a common grievance object, persistent case identifiers and interoperable handoffs among national entities and across borders where needed.

If DPI is interoperable when it works, redress must become interoperable when it doesn’t.

David Porteous is the founder of Integral: Governance Solutions; Maria Luciano is a policy analyst specializing in technology policy, inclusive data governance and digital government; Deepti George is founder of Yutadhi; Sahana Arun Kumar is co-founder of Amarante Consulting.

Photo credit: Infinite Creations

Sadly, this was a crisis foretold.

In July 2016, Cambodia’s microfinance industry convened an all-day event: “Let’s Talk about Over-indebtedness, Now!”. The microfinance CEOs and investors in attendance heard presentations from multiple analysts, including economists from the International Monetary Fund, all of whom conveyed the same message: The sector’s growth had to slow.

That same month, the International Finance Corporation (IFC), the World Bank’s private investment arm, arranged a $90 million loan and gave its “Stamp of Approval” to PRASAC, the largest and fastest-growing of Cambodia’s leading microfinance institutions (MFIs).

After a decade of escalating growth across the sector — along with escalating cases of over-indebtedness, as documented by Cambodian civil-society groups and international human-rights organizations — IFC’s watchdog, the Compliance Advisor Ombudsman (CAO) published its own findings in June 2026. Its two-year investigation concluded that not only had clients been harmed, but that this harm was related to IFC’s failure to identify and monitor the social risks created by its investments. In its response, IFC’s Board of Executive Directors acknowledged that borrowers had been harmed. But in an unprecedented move, it rejected the Ombudsman’s findings, siding with management’s argument that the harms suffered by borrowers aren’t covered by IFC’s Policy on Environmental and Social Sustainability.

In other words, the Board didn’t say the CAO’s findings were wrong — it simply found them irrelevant.

I was directly involved in several of these events: I spoke at the July 2016 industry meeting on over-indebtedness, sharing the findings from my MIMOSA report on market saturation. I later helped draft the Lending Guidelines discussed below, and subsequently served as an external advisor to the CAO during its Cambodia investigation.

In that work, I’ve noticed a gap in the debate over who is to blame. Client advocates point to the failings of the sector at large, which are real. Sector institutions point to their efforts to strengthen client protection, which are also real. But neither side has explained how the sector went off the rails, or who drove it there. And in a world where everyone is guilty, nobody is.

As with most financial crises, Cambodia’s wasn’t caused by any one entity. But some actors bear far more of the blame than others, and IFC stands out: Its role was not only integral to the crisis — it helped undermine the sector’s own efforts to avert it.

Early Warnings of an Overheating Sector

Half a year before my 2016 MIMOSA report placed Cambodia among the most credit-saturated microfinance markets in the world and explicitly warned that the sector had to slow, the International Monetary Fund’s November 2015 report called on Cambodia’s authorities “to address growing financial stability risks by stabilizing and moderating the pace of credit growth to more reasonable levels.”

Cambodia’s central bank didn’t act on that advice. Its one notable regulatory response — an interest-rate cap in 2017 — failed to slow growth, and it fell to others to fill the gap.

In December 2016, the Cambodian Microfinance Association published its Lending Guidelines, which set explicit limits on the practices most likely to deepen over-indebtedness. These limits initially focused on reducing additional lending to borrowers who were already carrying several loans, and later extended to the practice of early refinancing into substantially larger loans. The Guidelines had no legal enforcement behind them: Compliance ultimately rested only on the willingness of microfinance lenders to follow them. But they did feature a monthly dashboard, produced by the Credit Bureau of Cambodia, that showed each lender’s standing against the Guidelines and against its peers. It was exactly the kind of independent monitoring that interested investors could easily use to track their investees’ compliance — and its existence was widely known among microfinance investors, many of whom had also endorsed the Guidelines.

There was also another set of actors who relied on the Lending Guidelines: the sector’s Client Protection Certification system, along with the rating agencies that conducted these certifications. To receive and maintain certification, Cambodian microfinance lenders had to show that they were compliant with the Guidelines.

The link between excessive credit growth and over-indebtedness is indirect, but it is not especially complicated. Think of credit as water in a lake and lending safeguards — such as the Lending Guidelines and Client Protection Certification — as the dam that holds back the water. Well-designed safeguards can ensure a steady flow, enabling small businesses to invest productively and helping households to manage their cash flows. But even the best-designed ones will be overwhelmed by an excessive supply of credit, drowning large numbers of clients in debt that they cannot afford. And just as a dam fails when its reinforcements break, the system fails when lenders — especially the largest ones — stop observing the rules and respecting the safeguards. In Cambodia, both of these things happened: The largest lender broke ranks, and the water kept rising.

The Dangers of Growth at All Costs

In 2015, the largest microfinance institution in Cambodia was PRASAC, nearly double the size of its nearest rival. Founded in 1995 as a rural development project and later transformed into a for-profit company, it was also the fastest-growing among Cambodia’s leading MFIs, averaging growth of 46% from 2008 to 2015, compared to 35% for the rest of the microfinance sector (according to my calculations, based on data from the Cambodian Microfinance Association and PRASAC). IFC got behind PRASAC in the early 2010s, lending it $35 million between 2012 and 2015, and arranging a $90 million syndicated loan in 2016, with $20 million from its own account and another $70 million drawn from private lenders. The loan was meant to “support [PRASAC’s] further growth in the market” and to leverage IFC’s “Stamp of Approval” to help it “establish relationships with international banks and obtain investors’ validation of the Company’s business model.”

That $90 million was only about a quarter of PRASAC’s borrowings at the time, but IFC’s endorsement mattered more than its money. In 2015, PRASAC’s lenders included eight development finance institutions, 13 microfinance fund managers and nine commercial lenders. By 2020, its commercial lenders had grown to 43 — mostly Asian banks — while its number of microfinance lenders had nearly halved. By its own stated objectives, IFC’s loan was a success.

The immediate period after that IFC loan saw another key development. In March 2017 a Sri Lankan financial conglomerate that already held a minority stake took control of PRASAC and pushed its growth even higher: Its growth rate hit 50% that same year, compared to 22% for the rest of the microfinance sector. That was also PRASAC’s first full year operating with the Lending Guidelines in effect, which it violated repeatedly, leading to the withdrawal of its Client Protection Certification in November 2018. Whatever the effects PRASAC experienced from that loss of certification, they weren’t financial; commercial lenders kept arriving, and in 2020, the company was sold for $603 million — netting the owner a 121% return in three years.

The problem with PRASAC wasn’t the entry of Asian banks, it was the growth they were funding. In 2016, I warned that without enforceable rules, “lenders seeking to slow down on their own will simply see their market positions replaced by more aggressive competitors — a particularly vicious competitive dynamic that rewards short-term gains and undermines long-term sustainability.” Here the aggressor turned out to be the largest MFI in the market, carrying IFC’s imprimatur, and pursuing precisely the short-term growth my report had warned about.

Having watched PRASAC grow at double the pace of the rest of the sector in 2017, its competitors soon followed: They averaged 30% annual growth during 2018-2019. The Lending Guidelines had been cast aside, and the warnings to slow growth had been ignored. Worse yet, even as MFI portfolios exploded, the number of Cambodian clients served by microfinance institutions barely budged. Growth was driven almost entirely by increasing the amounts lent to clients, many of whose incomes weren’t keeping up.

This is how financial crises unfold.

By 2022, when the CAO complaint was filed, Cambodia was the third most credit-saturated country in the world. And by 2023, the average microfinance loan had grown to $4,578, up from $409 in 2006 — a jump from 67% of per capita GDP to 188%.

An Incoherent Microfinance Strategy

Key to understanding IFC’s actions during this period is the disconnect between its two arms: Advisory Services and Investment Services.

IFC’s advisory arm has worked since 2008 to build the infrastructure a responsible market needs: It supported the creation of the Credit Bureau of Cambodia (launched in 2012), backed the Lending Guidelines, and helped establish the Client Protection Certification system. By IFC’s own account, its work with Cambodia’s regulator and industry associations aimed “to reduce the risks of overheating of the credit market and over-indebtedness.” These are real actions with real value, which came at a time when IFC’s advisory arm was already identifying the risks building in Cambodia. In July 2015 it published a report warning that pressure from competitors could push Cambodian lenders into “sub-prime” lending — “the type of competitive pressure that … led to the catastrophic financial crisis in 2007.”

A year later, IFC’s investment arm gave a key boost to the largest and fastest-growing of Cambodia’s leading microfinance institutions, which was looking to grow still more — on the heels of multiple warnings that growth was the key driver of over-indebtedness risk in Cambodia. When PRASAC failed to abide by the sector’s own Lending Guidelines and had its Client Protection Certification withdrawn, IFC’s investment arm took no action — despite the fact that IFC had the means to exercise oversight even after the loan had been made, since it “incorporates affirmative covenants in its legal agreements requiring its microfinance institution clients to maintain … procedures and controls for responsible finance and consumer protection.” Inaction in the face of wrongdoing is a form of silent consent, and its 2016 loan to PRASAC closed out only in October 2020, well after the damage had been done.

What’s the point of creating a client protection infrastructure if IFC’s own investment arm supports its largest violator? It’s incoherent.

The only way to understand that incoherence is to recognize that IFC’s two arms — advisory and investment — are acting like two distinct organizations, guided by their own separate objectives. While the former works on protecting clients, the latter pursues growth, with client protection at best an afterthought. And when forced to defend its actions, IFC combines the two activities: Statements like “IFC’s clients in Cambodia have reached more than 400,000 microenterprises and 1.7 million farmers” sit alongside a laundry list of client protection efforts. At no point does IFC recognize that in Cambodia, its two objectives, growth and client protection, have been working at cross-purposes since at least 2016.

The Accountability Gap

After its own Ombudsman found that IFC failed to ensure that the clients of its investees were protected from harm, IFC didn’t respond by acknowledging the failures that led to this point and rethinking its strategy. It simply stated that the findings are not applicable. The CAO’s head, Janine Ferretti, resigned the very next day.

Less than two weeks later, the Board went further, directing the CAO to “suspend processing of the ongoing CAO cases” and to “not take any cases relating to Financial Consumer Protection in microfinance.” This stance isn’t just about Cambodia: Concerns are growing that the decision sets a dangerous precedent that will reduce the World Bank’s accountability and even influence other development banks. Worse yet, whatever accountability may have been sparked by borrower complaints to the CAO has now been deferred until the completion of IFC’s Sustainability Framework review process — that is to say, until late 2028 at the earliest. In the interim, IFC’s only customer complaints channel remains closed to microfinance borrowers.

There are multiple experts and advocates calling for IFC to completely rethink its approach to protecting microfinance clients. IFC would do well to consider them. However, for any reforms to work, it must first acknowledge the serious errors it has committed along the way. That’s what accountability means.

Unfortunately, IFC’s approach to accountability remains as incoherent as its microfinance strategy. In its management response to the CAO’s findings, this incoherence is on full display: It calls for more work on market infrastructure, more training, and more hotlines and working groups from its advisory arm, and for tighter due diligence and supervision of its investees from its investment arm. But at no point does IFC make any link between the two — or any commitment that its investments will be bound by the very safeguards its advisory arm helps build.

Its Board has, however, sent one clear signal: This incoherence is set to continue. Twelve days after promising to fund a financial ombudsman in Cambodia, it silenced its own.

Daniel Rozas is an inclusive finance consultant focusing on client protection, and co-founder of the MIMOSA Project, which tracks market saturation in microfinance. He has also been commissioned by IFC for research and advisory work, including on Cambodia.

Photo credit: patpitchaya

Yet despite the importance of getting these practices right, too many organizations’ IMM standards and norms have prioritized measurement over management. As a result, they end up focusing on compliance, instead of collecting data to inform and enhance their operations and impact.

Based on our extensive engagement with other IMM practitioners over the years, most of the impact data being collected is not actually informing decisions. It tends to be gathered mainly to satisfy investors’ requirements, and often ends up gathering digital dust. This is because IMM infrastructure was built for the investors that own or manage the capital, rather than the enterprises and non-profits that do the work. Indeed, those organizations often find that arduous reporting requirements can actually constrain their ability to create the impact they’re expected to measure. Too often, this reporting does not benefit them, or the communities and individuals they serve.

When organizations fail to manage their impact, they miss opportunities to increase the breadth and depth of this impact, weakening the performance of impact investing as a sector.

In March, almost 100 advanced IMM experts — including asset owners, asset managers, standard setters and measurement experts — gathered in Montreal. During a breakout session facilitated by the authors of this piece, we asked ourselves three questions which led to the five takeaways in this article:

• How can we help investors make more informed and intentional decisions to improve impact?
• How can we support business and non-profit leaders in their value creation processes by integrating impact decision-making throughout their strategy and operations?
• How can we more closely align IMM with investee processes, capacity and operations to inform improvements in practices that enhance impact?

In the article below we’ll highlight several actions we can take today, as asset owners, asset managers, measurement experts or impact-producing entities, to right-size IMM and make it fit for investees.

1: Treat investees as drivers of impact, not just data sources

Business and non-profit leaders building products and services that benefit people and planet got into this work to address real challenges. They don’t need others to convince them that impact matters. In fact, by the time they receive IMM mandates from an investor, they are often already measuring and managing for impact, through models designed around the needs of the communities they serve. They see firsthand how their work interacts with the wider systems around them. Imagine what becomes possible when asset owners and managers consult their investees, and adapt their frameworks accordingly. Investees often care more about impact than anyone else, and IMM can be a resource that supports that commitment rather than a tax on their time.

The current system extracts from these organizations: their time, their staff capacity, their goodwill. And it too rarely gives anything back. Sometimes an investee receives a benchmark they can use, a helpful peer insight, or a reflection on how they are doing compared to others. But more often, their data simply goes into a report that feeds into a fund’s portfolio management system, never to surface again.

This is not only extractive, it’s also inefficient and redundant.

IMM could instead treat investees as the core partners and drivers of impact that they are, not just as data sources. When IMM professionals and investors close the feedback loop and co-create IMM metrics and data collection systems with these organizations, they target the type of data that can help them make better-informed decisions about how to deliver broader, deeper and more equitable impact. This kind of data collection can actively enhance impact, building on what is already working in an organization’s core model to unlock greater depth and scale. Investors are well placed to encourage and enable this collaboration.

2: Reduce the burden of data collection

More data does not equal more impact. This seems obvious, yet the default mode of impact investing has long been accumulation: more indicators, more frameworks, more reporting cycles. The implicit logic was that rigor required volume, and that volume meant credibility. In fact, the opposite is true; we risk drowning in data and losing relevance.

IMM is at its most powerful when it is driven by the decisions an organization needs to make, rather than by pre-defined indicators or reporting templates. When every data point traces back to a question that impacts the investee’s operations, the surveys and data forms get shorter and the data actually gets used.

It also helps to be clear about which decision the data serves. For instance, the information an investor needs to decide whether to invest (e.g., the depth and credibility of the impact thesis, who the investee serves, and the risks that could threaten its impact) is a larger, one-time ask which fits naturally in due diligence. Ongoing monitoring can then be lighter: a small set of indicators tied to decisions the investor and investee will actually make together during the investment, such as where to focus support, when to adjust strategy, or whether the impact thesis is holding up.

Too often, the depth of due diligence carries over into quarterly reporting, and that is where the burden builds up. It is important to be clear about the tradeoffs (costs and benefits) of capturing and using the associated data. In practical terms: Apply a utilization screen to IMM by identifying the question/s you are trying to answer, and what a “good enough” level of evidence looks like. Map your IMM metrics to the decisions they will inform and to what is actually being used. Letting go of data that isn’t used frees up the investee’s time and attention to sharpen its remaining indicators, so each one is key to improving understanding and informing decisions.

3: Align data requests with investees’ capacity, maturity — and limitations

A seed-stage venture working with its first 50 customers or a non-profit with a staff of three people is not in the same place as a growth-stage company or large non-profit with a proven model and significant human and financial resources available. Expecting the same data sophistication from both doesn’t make the seed-stage company or small non-profit more rigorous; it distracts them from core operations and likely reduces the impact they can create.

But right-sizing is not only about volume: It is also about asking for the right kind of data. A seed-stage venture or small non-profit can tell you who it is reaching, share what customers or beneficiaries say about the product, and assess early signals of whether its model is working. It usually cannot tell you about long-term outcomes or impact it can clearly attribute to its work, because that evidence does not exist yet. Asking for it produces hypotheses dressed up as evidence. IMM at small non-profits or early-stage companies should instead aim to be a fast-learning engine, testing key assumptions and generating quick feedback, with more rigorous outcome measurement growing alongside the model.

Guidance calibrated by stage of growth and type of capital would encourage a data collection process better aligned to investees’ realities and limitations. Investees should be empowered to advocate for IMM approaches that evolve with their model. That starts with involving them in selecting metrics and co-creating data collection approaches that align with their reality. It also means lowering the cost of collecting data. Before building new portals or bespoke reporting systems, leverage the operational software, native workflows and lightweight tools investees already use to automate data capture and analysis. For early- and growth-stage teams, integrating data collection into existing processes can help make IMM practices sustainable.

4: Raise awareness of IMM requirements that don’t improve impact

Where there is money, there is power — and there are also demands. IMM requirements should be open to negotiation, and funding conversations are an opportunity to co-create shared expectations on impact.

Asset owners answer to trustees and public bodies, and they carry the reputational risk if their investment decisions lead to harmful or disappointing outcomes. Asset managers answer to their own reporting obligations. Donors operate within frameworks set by their boards and funding priorities. Under current practices, the path of least resistance has been to accept whatever IMM requirements come attached to a check. This has shaped a generation of impact measurement standards and systems that serve capital providers more than they serve enterprises, non-profits or communities.

IMM practitioners often work in this chain, setting and serving IMM requirements. In solidarity with those delivering the impact, we can thoughtfully push back on IMM requirements that don’t improve impact, by educating and influencing capital providers and standard setters. When a requirement doesn’t add value, we can and should say so. When a framework doesn’t fit the stage or sector of portfolio investees, we can propose one that does. And when we’re building IMM systems, we should ask ourselves: Does this serve the people closest to the problem, or does it serve the people furthest away?

That said, the institutions with the most leverage in this system (asset owners, asset managers and other standard setters) have the greatest opportunity to model right-sized IMM, and the most power to shift practices in that direction.

5: Pay for the full IMM system while demonstrating its value

IMM isn’t free, but many investors have been pretending it is.

Investees are expected to collect data, report on it, and continuously refine their approaches with little or no additional resourcing. Technical assistance is offered intermittently, if at all. The “data pipeline” from collection to reporting and action requires sustainable investment, in people, systems and time.

When the time investees spend on IMM is funded, it opens the door to capacity building, hands-on support and learning — including learning from failure. Learning is not just a byproduct of IMM, it is an outcome worth funding in its own right. Learning means making sense of what the data shows, including the parts that reveal that a strategy isn’t working, and using that understanding to change what happens next. It comes from structured reflection, honest documentation of what failed and why, and time set aside to synthesize patterns across a portfolio, not simply from collecting more numbers. Without it, IMM produces reports but doesn’t change decisions, and investees end up repeating mistakes that could have been avoided if they had captured and responded to these learnings in the first place.

Asking investees to measure their impact should also involve an offer to help them do it well, financially and technically. Smaller companies and non-profits will likely need more support, while larger, more established companies and non-profit organizations may have systems and resources already in place.

IMM is not free, especially at the early stages, but it has value — as we learned in the Founders in Focus survey. Done well, demonstrating impact can create real value for the investee itself, providing a market opportunity, not merely a reporting burden. It’s time for investors and IMM practitioners to understand investee needs more deeply than we currently do. That starts with understanding what they already do, then asking how demonstrating impact can support them directly: Does it build more loyal customers, reach more beneficiaries equitably, help attract further investment, sharpen understanding of client/beneficiary and market needs and context, or reveal potential for product or market expansion? The strongest IMM is tied directly to the investee’s underlying economics and core drivers, so that performance and impact reinforce one another rather than compete. Approached this way, IMM stops competing with the investee’s other needs for time and resources, and becomes part of how it evolves to achieve its mission.

Evolving toward IMM that works — a call for action

The convening last March that led to these takeaways generated both honest assessments of the shortcomings of current IMM practices, and a drive to right-size them. It was clear to all of us that our systems have too often rewarded compliance over impact, extracting more from investees than they’ve given back. And we all shared the conviction that when IMM is designed for real-world use — aligned to actual decisions, and integrated into core operations rather than bolted on as a reporting layer — it sharpens strategy, improves outcomes and unlocks funding.

Looking ahead, we see an opportunity for IMM to go further still: not just making non-profit and business models work, but helping them evolve. IMM rooted in systems and equity asks who gains and who bears the costs. It can help investees use resources more efficiently, share value more fairly across their supply chains, and collaborate with peers and communities rather than compete with them. This wasn’t part of the Montreal conversation, but we believe it’s the next question the field needs to take on.

Good IMM is one of the sector’s most powerful levers — not because it produces more data, but because it produces sharper understanding, better-informed decisions, and a clear view of an organization’s impact and financial performance, even when the data is imperfect. Done right, it creates value, drives collaboration among investees, investors and communities, and is worth the effort and money it requires. That’s why we’re calling on investors and other funders to empower IMM professionals to measure what matters, collaborate, innovate and lead.

Who’s with us? Click here to register your interest in following and informing the ongoing conversation on right-sizing IMM.

These takeaways represent a synthesis of perspectives from the breakout session at the inaugural IMM Convening for Advanced Practitioners, and continued collaboration after the event, including feedback from Laura Budzyna (Beyond Measure), Catherine Dun Rappaport (Social Finance), Kusi Hornberger (IDB-Lab), Luan Mans (while at Acumen, now at BII), C. Sara Minard (Columbia University, Manarine LLC), Belissa Rojas (Fondaction Asset Management), and Dan Waldron (Acumen).

Additional contributors to the session in Montreal include: Lillian Alexander (Prosper Global Ventures), Malika Anand (Community Investment Management), Thomas Hannaford (Power Sustainable), Laura Hollod (Hollod Impact), Marie-Josée Parent (Raven Impact Foundation), Laurentia Perrin (Common Approach to Impact Measurement), Kate Ruff (Common Approach to Impact Measurement), Luba Shabal, Ember Infrastructure, and Becca Shepherd (Independent Consultant).

Julia Mensink is Director of Impact at Acumen; Heather Esper is Director of Performance Measurement and Improvement at the William Davidson Institute at the University of Michigan. 

Photo credit: AndreyPopov

I’m referring to Donor-Advised Funds (DAFs), a type of specialized charitable giving account that lets someone donate cash or assets, take an immediate tax deduction, and direct that money to nonprofits as individual grants over time. These funds are popular with the general public: To take one prominent example, around 48% of Fidelity Charitable DAF accounts had less than $25,000 in assets at the end of 2025. They’re also popular with wealthy families and other high net-worth individuals, who favor them due to their tax advantages and the greater simplicity they provide compared to alternative philanthropic approaches, like setting up a foundation. And they are growing: As of FY 2024 (the most recent data year), more than $327 billion was sitting in U.S. DAFs, earmarked for the public good.

The money has, from a legal and tax perspective, already been gifted to a charitable entity (the DAF), and the donors have already enjoyed the tax benefits of making the donation. But too often, the process stops there. Unlike a private foundation that is required by law to donate 5% of its assets each year, a DAF’s sponsor — often an entity within a larger financial institution — has no obligation to donate anything on a defined timescale. In the meantime, the money sits in an account, invested in the market, growing tax free. That, of course, benefits the company managing the DAF, many of whom are paid a percentage of the funds under management.

Only around $65 billion (~20%) was disbursed as grants from U.S. DAFs in 2024, with the rest remaining in these funds. And though sustainable investment options for those funds exist, and can have incredible impact, other DAF sponsors funnel donors into a narrow menu of options that default to the conventional index funds used by their parent companies. 

While donors deliberate on where to deploy the capital, or defer the decision until later, these billions of dollars already committed for the public good can even be financing high-emission sectors like the fossil fuel industry, which is emitting billions of tons of CO₂ per year. 

Meanwhile, innovative climate startups are in need of funding to accelerate their solutions.

Philanthropy can and should be a key part of the solution, not part of the problem.

Purchasing future carbon credits in Kenya

To understand the sort of impact that could be made if this funding were mobilized, take the example of Kenya-based Octavia Carbon, Africa’s first direct air capture company. They had a strong business case from the start: Use the region’s abundant geothermal energy to power technology that pulls planet-warming carbon from the atmosphere and locks it away. That pairing turns clean power into an exportable product in the form of carbon removal credits sold to global buyers. 

What Octavia needed was buyers for their carbon removal credits. But as with many innovations, carbon removal needs to demonstrate its value before commercial buyers will feel confident that it works. 

Terraset, a climate-focused nonprofit, aims to bridge that gap by paying now for carbon removal to be delivered later. Over the past three years, we have pooled philanthropic funding, including from many DAFs, to purchase future greenhouse gas removal from more than two dozen early-stage climate companies. Each ton of gas removed is represented by one “carbon credit,” a unit that buyers in the voluntary market can purchase to fund climate solutions or offset their own emissions.

Buying carbon credits before the services are delivered is known as a “pre-purchase,” and it provides necessary, early funding to accelerate and build the market for carbon removal, methane abatement and other climate solutions in emerging markets. We’ve noticed that climate technology developers that make it from pilot to institutional finance almost always have both early backers and early customers. The ones that stall, despite validated technology and strong teams, often don’t.

Pre-purchases create the demand signal that helps a company prove its model, develop the monitoring, reporting and verification (MRV) protocols that buyers and regulators require, and reach the commercial milestones that make institutional finance possible. Without this bridge capital, even a technically sound business with cost advantages can stall, and even die, between pilot and scale.

Since 2024, Terraset has made a series of pre-purchases from Octavia, totaling around $300,000. In that same time period, Octavia reports that it has created 160 jobs — 98% of which have been filled by Kenyan youth — and the company is establishing itself as a hub for carbon removal innovation across sub-Saharan Africa. With steady partners and investors like The Catalyst Fund, as well as a $5 million seed round led by African VC firms Lateral Frontiers and E4E Africa, Octavia’s journey illustrates the impact of unlocking different kinds of capital for promising climate innovators. 

The commercialization gap that grants can’t fill

Octavia’s story highlights one way funders can overcome a structural gap in how philanthropic capital typically reaches early-stage climate businesses in emerging markets. Most philanthropic giving is designed around grants: one-time disbursements to support a project, a study or an organization’s operations. Grants are valuable tools, but by not requiring delivery of a product (in this case carbon removal credits), they don’t create the commercial demand signal that tells investors a product has a market.

Pre-purchases do: By committing to buying carbon removal (or methane abatement credits, or other tradable forms of climate impact) at a set price and volume, an early buyer takes on a share of the commercial risk that would otherwise fall entirely on the company. That risk-sharing helps the startup invest in infrastructure, hire staff and demonstrate delivery. It bridges the gap between traditional philanthropic support like grants, and the kind of track record that development finance institutions (DFIs), impact investors and eventually commercial capital require before they’ll commit.

At Terraset, we built a revolving fund specifically designed to channel funding to make upfront pre-purchases from early-stage companies, paying today for tons of greenhouse gas removal that will be delivered in the future as credits. Then, we sell the credits to corporate buyers and recycle the returns into new purchases, creating a flywheel for ongoing impact. The model is built on the notion that the most catalytic thing philanthropic capital can do at this stage of the climate market is to create demand. 

How pre-purchases work across technologies and business models

The pre-purchase model works across a range of technologies and contexts, but the dynamics are especially visible in emerging markets, where the path to institutional finance is longer and the need for early demand signals is more acute. The approach can also be applied across a variety of different business models.

For instance, we have also purchased from Pyrogen, another Kenyan company taking an entirely different approach to greenhouse gas removal. Pyrogen is transforming invasive tree biomass into biochar, which is then incorporated into high-performance, carbon-negative concrete blocks used in affordable housing construction. At full production, the company is targeting the construction of 5,000 affordable homes per year and the removal of over 17,000 tons of CO₂ equivalent annually.

Terraset made a $100,000 pre-purchase from Pyrogen in June 2025. Pyrogen is currently working with Habitat for Humanity via the World Bank’s CGAP-sponsored affordable housing finance program to build Africa’s first low-cost housing using concrete infused with biochar. 

Highlighting this larger institutional partnership is not intended to infer causation but to illustrate the pattern we see across Terraset’s portfolio: Even small contributions of philanthropic capital can unlock much larger institutional capital. In Pyrogen’s case, our pre-purchase allowed their team to purchase a block manufacturing kit, put their concrete mixes to the test outside the lab, and build a fully digitized monitoring system to track each concrete block from harvested biomass to installation. This early support builds the proof of concept, the verified delivery record and the first commercial milestone, all of which helps DFIs and impact investors enter with confidence.

Why DAFs fit the pre-purchase capital model

The pre-purchase model requires a specific kind of capital: patient, risk tolerant, with no market-rate return requirement and no pressure to deploy into proven assets. It is a perfect fit for funds that have already been donated to charity (i.e., DAFs) but have yet to be put to use.

DAFs are a well-established structure, and donors who use them certainly aren’t doing anything wrong. The logic is sound: Accumulate capital, grow it, deploy it thoughtfully. But for climate specifically, timing is essential. Urgency is key.

The leverage available to an early buyer of a company like Octavia Carbon or Pyrogen today is distinct from the leverage available in five years when these businesses have either reached commercial scale or failed to get there. A dollar deployed now — as a pre-purchase from an early-stage climate company in an emerging market — makes an impact that the same dollar cannot match later.

What donors can do

For philanthropic advisors supporting donors who have put their money into DAFs and are interested in climate impact, two things would help move that capital to where it’s most needed.

• Shift the conversation with donors from “what they can do one day” to “what they can do now.” Most climate-focused DAF donors already intend to deploy their capital to the types of projects we’ve discussed here. The question worth raising is whether the planned timing of these deployments is calibrated to the unique impact this capital can make in the short-term for businesses at the commercialization stage, particularly in emerging markets where early buyers make a decisive difference.
• Recognize that the knowledge barrier for donors is real but surmountable. Carbon removal is a technical field, and most donors are not interested in becoming carbon removal experts before making a decision. Intermediaries like Terraset can play a role here, by vetting companies, structuring purchases, verifying delivery and reporting back on outcomes. A DAF holder does not need to evaluate the permanence standards for direct air capture or the MRV protocols for biochar to make a meaningful, verified contribution to a company building climate infrastructure in markets like Kenya. They need a trusted allocator and a reason to act now rather than later.

The next wave of climate-committed philanthropic capital should be driving impact now: the hundreds of billions of dollars that have already been earmarked for the public good, but have not yet been put to work. For climate businesses, the ongoing wait for this funding has a cost that compounds every year. The companies building carbon removal infrastructure are doing it now, and they’ve reached the stage where early buyers can make the difference between survival and scale. The capital to support them already exists: It’s up to DAFs and other funders to deploy it, now.

Adam Fraser is CEO of Terraset, a nonprofit that pools and deploys philanthropic capital to early-stage climate solutions.

Photo credit: Nataliia Kravchuk 

Laying the groundwork for these pilots was a slow, iterative process involving one site visit after another, conversations with power distribution companies (DISCOMs) to understand their concerns, and discussions with farmers who were interested in the additional income but understandably cautious about the risks. DISCOMS are one of the key stakeholders in such projects, as they are the entity that buys the energy generated by the Agri-PV plant.

Somewhere along the way, during this process of testing, questioning and recalibrating our approach, we met Kajod Mal, a farmer in Kundanpura, Rajasthan who already owned a 600-kW ground-mounted PV. He is the farmer with whom we partnered to launch Rajasthan’s first farmer-owned Agri-PV plant under the Indian government’s PM-KUSUM programme. But before he agreed to engage in this programme, he asked us a question that revealed a fundamental concern — one with important implications for the uptake of solar energy projects among Indian farmers.

“After you implement this project, will I still be able to farm and reclaim my fertile agriculture land?” It was one of the first questions he asked us, even before we could finish explaining the fundamentals of an Agri-PV plant.

The question exposed a contradiction we had been grappling with ourselves. India is now the world’s third-largest producer of solar power, and government programmes such as PM-KUSUM have played an important role in expanding renewable energy installation while creating new income opportunities for farming communities. As part of PM-KUSUM, farmers can install grid-connected solar plants on their land and sell electricity to the grid — a significant policy innovation that aligns India’s clean energy ambitions with rural livelihoods. But while the programme originally envisioned the installation of these ground-mounted power plants on barren land, some farmers, like Kajod Mal, decided to install them on fertile agriculture land. Their reasoning was that it made sense to prioritise energy generation, a steady source of higher income, over the more volatile and lower returns they could generate from farming this land.

Before installing his ground-mounted solar plant under PM-KUSUM, Kajod used to cultivate wheat and millet and earned roughly INR 40,000 per acre annually. After installing a ground-mounted plant and just selling energy to the local distribution company at Rs 3.14/kWh, his net annual income per acre jumped five to seven times. On paper, the programme worked exactly as intended. Yet standing in his field, we saw something it did not capture: The solar panels stretched across the land from edge to edge. The soil that had sustained Kajod’s family for generations could no longer support a single crop. As someone who had farmed all his life, he told us that he missed farming: We saw that the solar plant that was boosting his income was also impacting his sense of identity, and his connection to the land.

This farmer’s experience pointed to a larger question about how India can expand renewable energy without compromising its agricultural land. Conventional ground-mounted solar can generate substantial energy income, but when installed on productive farmland, it can displace cultivation for decades. Agri-PV offers a way to avoid this trade-off. By elevating solar panels up to 10 feet and designing the system around agricultural operations, the same parcel of land can continue to produce both electricity and crops. The objective is therefore not to force farmers to choose between food and energy, but to enable them to produce both, creating an integrated model in which the expansion of clean energy does not come at the expense of food production and agricultural livelihoods. In fact, Agri-PV offers an opportunity to rethink not only how solar infrastructure is designed, but also how policy adjustments could better support farmers’ livelihoods.

To help make the case for this shift in focus, with support from Kotak Mahindra Bank’s CSR initiative, our team decided to retrofit Kajod Mal’s existing ground-mounted solar plant into Agri-PV. We knew the engineering design would be challenging, particularly in ensuring structural integrity. What we underestimated was the complexity of implementation on the ground. We initially assumed that once the technical design was finalised, retrofitting the plant would be largely an engineering exercise. In practice, the bigger challenges lay in coordinating people, processes and institutions. These experiences shaped the lessons we share below.

Designing the Solar Farm Around the Farmer

Going into this pilot program, it was tempting to view the retrofitting of Kajod’s existing PV plant as a series of engineering challenges: Raise the solar panels. Preserve the installed capacity. Complete the construction. Instead, we began with a much simpler question: “What do you want this land to grow?” His answer made his priority clear: He wanted the land to produce crops again, rather than using it solely to generate electricity. If the panels were elevated to approximately 10 feet, Kajod hoped to experiment with maize, tomatoes, cucumbers and chilies, going beyond the wheat and millet he had mainly grown prior to his original PV installation. The partial shade created by the elevated panels would offer different growing conditions and allow him to cultivate a wider range of crops. That answer reshaped our design plans. Row and column spacing, panel height, layout — we reworked all of this to allow these crops to be cultivated comfortably underneath the solar panels, and to allow agriculture machinery like tractors to operate smoothly in his field.

When the retrofit was complete, the same land that had once been completely occupied by solar panels now supported both electricity generation and agriculture. This enabled Kajod Mal to return to farming, and to once again make the key decisions every farmer must make about what to plant and where, based on his own preferences and understanding of the land and market. Seeing him make those choices for himself was an important reminder that the project was not just about adding agriculture beneath solar panels. It was about giving farmers the freedom to continue farming, while gaining a new source of income from the same land. When climate solutions complement livelihoods rather than compete with them, they become far more meaningful and more likely to be embraced by farmers.

Farmer trust in Agri-PV is built through dialogue

The challenges we faced in designing the Agri-PV plant around Kajod’s crop preferences were ultimately solvable. But asking him to dismantle a solar plant that was already generating a reliable income, on the promise that we would rebuild it into something better, was a different kind of challenge altogether. He did not agree immediately. Even though our project covered the retrofit costs, the decision still involved considerable uncertainty for him. It took us multiple rounds of discussions, negotiations and conversations about risk before we established enough trust for him to move forward.

The implementation phase tested that trust further. Kotak’s CSR initiative funded the pilot. The disbursement process took longer than planned because of the time required to complete the necessary documentation, finalise the engineering, procurement and construction (EPC) process, sign the memorandum of understanding, and process the payment through ICRIER’s finance department. The elevated PV structure took longer to manufacture than expected. A lack of coordination between the EPC contractor and the local installation team stalled progress on site. At one point, the plant remained partially dismantled while everyone waited for the next step in the process to move forward.

For Kajod Mal, these were not just administrative delays. Retrofitting requires part of the plant to be shut off, so every day of implementation delay cut further into his steady energy income. Since he had dedicated all his farmland to his existing solar PV plant, these delays were impacting his livelihood. This phase of the project was our stress test, and there were moments when Kajod’s frustration was palpable. We had honored our financial commitments, but the work on the ground remained stalled because the EPC supplier missed the agreed-upon timeline and delivered the required materials and equipment later than expected.

What helped us navigate that period was continuous engagement from our end, along with Kajod Mal’s now-strong determination to turn this idea into reality. We kept visiting the site, explaining what was happening, acknowledging the delays with integrity, and staying engaged with him throughout this difficult phase. That experience fundamentally changed how we think about the implementation of Agri-PV projects. We often perceive trust as something that must be built before a project begins, but our experience suggested something different. Mutual trust might not be fully established before implementation begins; it develops and strengthens throughout the project.

Partnership is the most integral component of an Agri-PV project

By the time construction began, we thought the hardest part was behind us. It wasn’t. We still needed to work with a variety of partners, who often needed to spearhead new designs and processes to bring the project to completion. For this Agri-PV pilot, there was no single organisation that deserves full credit for turning our concept into reality. Every stage depended on various institutions that had never before collaborated on an Agri-PV project.

Throughout the transition, JVVNL, the local electricity distribution company, continued purchasing the electricity generated by the project under the existing agreement and on the same terms. Because this was Rajasthan’s first farmer-centric Agri-PV project, the local EPC contractor was attempting its first retrofit of this kind, and had to fabricate a structure unlike any it had built before. Our funding partner backed the idea even though Rajasthan had no proven model for implementing a farmer-centric Agri-PV project. Our role at ICRIER, as the ideation and implementation team, was to ensure that all of these moving pieces continued moving together. Finally, after almost a year of this collaboration and coordination, our collective effort bore fruit. Kajod’s Agri-PV plant was officially inaugurated on June 24 of this year.

Looking Ahead: Clean Energy that Doesn’t Leave the Farmer Behind

We began this journey with a simple question: Should a farmer choose between agriculture and clean energy?

When we first met Kajod Mal, he had already become an energy producer, but he had stopped being a farmer. The land beneath his solar panels was no longer being cultivated. A year later, that has changed. Standing beneath the elevated panels, watching maize and chilies grow on land where he had once stopped farming, Kajod is once again cultivating his fields. The first harvest is still ahead, so his agricultural income remains a projection. But the potential is significant. The original ground-mounted solar plant had increased his income to around five to seven times what he had earned from conventional farming, but at the cost of giving up cultivation. With the Agri-PV retrofit, he can now combine both sources of income, potentially earning around INR 450,000 per acre, per year — nearly 10 times his former income from conventional farming.

Beyond the substantial increase in his income, something more important has changed. Kajod Mal is not only farming again. He owns the solar project, explains the model to visitors, and is already considering leasing additional land for a second Agri-PV project. In the process, he is moving from being simply a beneficiary of such a project to becoming an active participant in it, and potentially an Agri-PV entrepreneur in his own right.

That, ultimately, is what our pilot demonstrates. Agri-PV is not simply about growing crops beneath solar panels. It is about designing the energy transition around the farmer, so that producing electricity does not come at the cost of producing food. With the right technology, finance and institutional support, farmers like Kajod do not have to choose between the two. They can farm the land, harvest the sun — and earn income from both.

Laxmi Sharma is a Research Associate, and Subhodeep Basu is a Research Fellow at the Indian Council for Research on International Economic Relations.

Photo: Kajod Mal’s Agri-PV plant in Kundanpura, Jaipur. Photo credit: Indian Council for Research on International Economic Relations

Two then-small entities, one in the US and the other in the UK, were tasked with reshaping the globe. One was the World Bank, which opened in 1946 on a single office floor in Washington, D.C., with just 26 people. The other was the United Nations, which established its initial operational footing that same year in a temporary office in London with seconded diplomats and clerks.

From those modest beginnings, the development sector has grown over the subsequent decades into a sprawling ecosystem, including both powerful multilaterals and millions of community-level NGOs worldwide.

But this journey is not just a story of expanding budgets and staff headcounts. It is also the story of how the sector has repeatedly reinvented its tools and techniques to handle the growing scale, depth and relevance of development work.

Today, as traditional aid recedes and legacy tools strain under modern operational demands, the sector has reached another defining inflection point. While the emergence of advanced technologies like AI offers unprecedented processing power, leveraging them requires more than just another software update. It demands a complete reimagining of the digital architecture that underpins global development, impacting how projects are designed, how data is gathered and shared, and how NGOs engage with their field staff and funders. Understanding how the sector’s tools evolved — and where they currently fall short — reveals exactly why this radically new architecture is necessary.

From LogFrames to the World Wide Web

1983 was a watershed year for the use of innovative planning tools in the development sector. It marked the widespread civilian adoption of the Logical Framework Approach (LogFrame), an analog but highly structured algorithmic matrix rooted in 1960s US military planning. When UN agencies and Germany’s GTZ (now GIZ) integrated it into their manuals that year, it triggered the era of participatory workshops in global development.

Because the LogFrame required mapping out a strict logic tree, teams used flipcharts, colored markers and movable note cards to visually build the project matrix together. By moving project design away from isolated bureaucratic deskwork and into collaborative group settings, this represented an intensely human, conversational breakthrough. Yet the moment discussions ended, that living community wisdom had to be rolled up and forced into a static, typed report. Because this final output was merely a text document, it lacked the computational muscle to calculate, scale or link human insight to financial forecasting.

The solution arrived in the late 1990s, when commercial personal computers first landed on NGO desks, triggering the spreadsheet revolution. Born in corporate banking, spreadsheets became an institutional fixture when the World Bank and IMF began deploying spreadsheet-based simulation tools to design structural adjustment programs and verify macroeconomic targets. Almost overnight, Microsoft Excel became the development sector’s primary data capturing tool. For the first time, a field officer could link an activity line to a financial column and project a multi-year budget instantly. It was an intoxicating leap in autonomy. Yet the spreadsheet remained a silent, intimidating void — a blank grid that offered no guidance, required training, and was highly prone to invisible data entry errors.

By the 2010s, the landscape shifted again with the rise of the networked collective. Defined by global programs like the International Aid Transparency Initiative — and coming at a time of genuine, if somewhat naive optimism about the power of open data sharing — this cloud-connected era promised a synchronized ecosystem where local NGOs could seamlessly share data and unlock capital through online portals. But in reality, cloud-based data sharing shifted the power balance backward, turning technology into a mechanism for top-down compliance. These web portals (and the size and complexity of the reporting matrices submitted to them) demand reliable internet access, which often forces local staff to travel great distances just to upload their field data and compliance reports into rigid algorithmic boxes dictated by donor guidelines, instead of using the system to genuinely plan, strategize or learn from their own work or that of their peers.

The historical arc of technology adoption across the sector, as exemplified by these three milestones, leaves us with a major operational paradox: We have moved from the human but unscalable boardroom wall, to the liberating but silent desktop spreadsheet, to the connected but often suffocating cloud portal. The question for the next era of development is simple: How do we build a tool that captures the intuitive logic of the flipchart and the independent freedom of the desktop, while leveraging the intelligent processing power of the modern digital age?

Unfortunately, existing software can’t simply be adapted to the sector’s current operational realities. The issue is not an absence of tools, but a fundamental design mismatch. Current software forces a false choice: At the frontline level, we either rely on isolated offline spreadsheets that cannot share global data, or heavy, centralized cloud portals that require reliable, high-bandwidth internet and function primarily as mechanisms for top-down donor oversight. This creates a cycle of structural dependence, where local NGOs are locked into either expensive proprietary tech vendors or the fragmented maze of custom-built reporting platforms mandated by their donors. Because these systems were built for top-down bureaucratic oversight rather than frontline execution, simply patching these existing platforms with new features is unlikely to solve their underlying misalignment with the sector’s evolving needs. We need a foundation built from the ground up for development realities.

It is time for a new digital architecture in global development

The solution I am proposing is not to build yet another heavy, donor-centric compliance portal. Nor is it about resigning ourselves to the isolated offline spreadsheets that frontline teams still fall back on today. Instead, it is about building a digital architecture that could move the development sector away from centralized, siloed compliance portals mandated and run by current donors, and toward a decentralized, interoperable ecosystem where an NGO holds its own operational data locally (even offline) and selectively grants access to specific funders via a secure network.

A decentralized architecture would reduce dependence on any single vendor, government or donor-controlled platform while preserving interoperability across the network. For a local NGO, this would mean they could enter their data once into their own local workspace, and the system could automatically translate and route it to an aid organization’s portal, a UN database or a private foundation — without the frontline worker having to log into three different websites and manually type the data out three separate times.

For the sake of this discussion, let’s give this proposed new digital architecture a name: Modus.

Modus would serve as both a framework for standardizing frontline data and an offline-first workspace for managing and sharing it. It would be a global, license-free ecosystem created to bring next-generation project design and execution within easy reach of countless development professionals. If the previous era belonged to the top-down cloud portal, the next era will belong to this sort of decentralized, global data architecture, pairing the independent flexibility of the spreadsheet with an open, secure repository hosted across distributed data networks.

While this system would work on individual devices in low-bandwidth or unconnected areas, when connected to the internet, it would act as a secure gateway: allowing the user to access advanced analytics, simulation tools and comparative insights drawn from the wider network, while maintaining strict control over sensitive operational data. Thus, Modus would allow NGOs to choose exactly which metrics to keep private, and which to selectively share with specific funders.

Frontline digital architecture for NGOs: A walkthrough

The nuts and bolts of this new architecture would best be left to multilateral leaders and Big Tech, who would ideally fund it not as a proprietary product, but as an open-source Digital Public Infrastructure that prepares emerging markets for their own advanced analytics. And once established, other entities  — especially in the public sector in countries around the world  — could easily adapt the architecture to decentralize and customize their project planning and implementation. But the blueprint for building it must be rooted in a deep understanding of the local NGOs and practitioners who face the realities of working at the field level where projects are actually implemented.

We can visualize some of this ecosystem’s core features by looking at how it would translate into quiet, practical value for a single, frontline NGO linked to this global network.

At the user level, the Modus software would need to be a lightweight, easily downloadable freeware developed to work on Windows and Macs, and able to operate seamlessly with or without regular internet access. Crucially, this software should be designed to be a widely used project worktool — built with the universal simplicity of Microsoft Excel rather than the intimidating, specialized complexity of heavy project management software like MS Project.

Let’s walk through the feature set of this proposed platform with Maya, a hypothetical program coordinator at a local NGO who represents millions of frontline practitioners managing multi-sectoral realities in communities that have limited access to the internet.

Phase 1: Strategic positioning and niche design: When Maya opens the Modus interface, an adaptive workspace prompts her to declare a clear operational focus for her NGO — a stark departure from current donor portals that inadvertently encourage scattered, multi-sectoral mission creep. As Maya inputs localized field realities, the tool’s analytical layer cross-references them against her organization’s core competencies to identify unfulfilled societal demands. Instead of traditional, box-ticking aid proposals that rely on broad, catch-all mission statements, the framework guides her to design highly targeted milestones that isolate the NGO’s exact mechanism of impact. This locks the organization into a distinct institutional niche before a single dollar is allocated, helping it differentiate itself from other NGOs across the broader network.

Phase 2: Financial sustainability and tapering models: Maya then switches to the financial workspace within Modus, where built-in calculators operating within the familiar, grid-like simplicity of a spreadsheet automatically project a multi-year budget directed toward an operational breakeven point. Crucially, the interface operationalizes the Diminishing Grant Framework approach I proposed in a recent NextBillion article, by embedding a tapering logic directly into the budget line items. As the system models a progressive reduction of donor funds, in accordance with this proposed framework, it requires her to structurally build local cost-sharing mechanisms, community fee-for-service models, or shared-value partnerships directly into the financial model to replace the receding grant money. By prioritizing the project’s local self-reliance as external aid recedes, the platform ensures that the intervention can survive on its own economic momentum.

Phase 3: Risk simulation and dynamic reporting: Before implementation, Maya connects briefly to the web to activate the platform’s analytical simulation layers. She introduces a hypothetical six-month supply-chain delay and an inflationary spike. The system utilizes AI-driven predictive analytics to instantly model these macro-disruptions across her entire plan — showing where the budget will break and how community outcomes will shift — allowing her to build a risk-adjusted blueprint in minutes.

Once this software is installed across the field teams at Maya’s NGO, these teams begin to upload encrypted qualitative observations phonetically in their local language using standard mobile keyboards. Upon syncing, the integrated system automatically deciphers, translates and structures these localized narratives into professional English. This creates an instant multilingual data bridge that simultaneously updates evaluation models and generates draft donor reports for final human review in real time, greatly streamlining data consolidation.

In considering the efficiency gains that can be generated by this sort of AI-enabled system, it’s important to acknowledge that need for final human review, as human judgment would be essential to the system’s success. While this review would require time and resources, these would pale in comparison to what’s needed to sustain the sector’s current data and reporting practices, where field data is often written on paper in local dialects, manually translated, then typed up days later by someone in a regional office — a process that’s slow, painstaking, and incredibly prone to human error and subjective interpretation. The AI would eliminate much of the manual grunt work of data consolidation, while a program coordinator would review and verify the system’s output, reducing the total time investment for these processes from weeks to hours.

Co-piloting the project lifecycle

The true utility of this sort of platform would lie in its ability to provide real-time guidance at every stage of project design. It would not replace human judgment; instead, by eliminating the mechanical burden of data entry, it would free up the practitioner’s funded hours for high-level strategic oversight. It would use clean interface design and contextual prompts to draw out a practitioner’s deep field insights.

Returning to the example of Maya: As she refines her project, this guidance surfaces a layer of analytical support directly inside the workspace layout, using the following measures:

• Contextual prompts: Instead of leaving the user staring at a blank row in a spreadsheet, the interface utilizes dynamic menus tailored to specific development sectors. If Maya inputs a generic line like “Community Training,” the system prompts her with localized operational questions, like: “Which local groups will lead this? Have seasonal migration patterns been accounted for?” These prompts ensure that routine data entry is consistently paired with rigorous project design logic.
• Cross-linkage scans: The embedded system actively scans the workspace to break down traditional operational silos. For instance, if Maya schedules a climate-adaptation workshop in one component and a livelihood-diversification module in another, the platform flags the duplication: “Similar target groups detected. Can these activities be integrated to save travel costs?” It connects the dots across the framework, ensuring that separate activity streams reinforce one another.
• Integrity filters: To minimize human error in complex, multi-year plans, the system acts as an automated editor scanning the internal logic of the project. If an operational expense is accidentally duplicated across regional sheets, or if an activity line lacks an assigned monitoring metric, the tool applies a gentle visual flag — such as a subtle highlight rather than a disruptive error pop-up. Through these cues, it alerts Maya to structural gaps and redundant lines in real time, guaranteeing a tight, defensible proposal before it ever reaches a donor’s desk. And because Modus is a decentralized framework, the data users enter stays locally with the NGO. Funders cannot peek into the workspace while the NGO is drafting or simulating scenarios: The proposal and its data only become visible to a specific funder when the NGO explicitly chooses to route it to them.

An open invitation for digital CSR

However, as I alluded to above, a transformative technology of this nature cannot be built by the development sector alone. It requires the foundational expertise of the very entities that are at the helm of the modern digital world.

Therefore, if it hopes to implement such an approach, the critical next step is for the development sector to assemble a visioning team with the expertise, tenacity and networks to pitch this as a collective corporate social responsibility proposal directly to tech titans and high-potential startups alike.

By provisioning this sort of standardized platform, major technology providers would have an opportunity to build a shared development utility. This could provide the development sector with a chance to move beyond passive corporate philanthropy and create a shared operational foundation. Within this system, an NGO field officer navigating a remote work site and a director sitting at a multilateral headquarters could operate using the exact same cohesive logic.

The technology to build such a system already exists. The only remaining question is whether — and how quickly — the development and technology sectors would be willing to step forward to build it together.

DISCLAIMER: The views and recommendations expressed in this article are solely those of the author and do not necessarily reflect the official policy or position of any other organization or individual.

Rajat Ray is a Social Innovations Advisor with over 40 years of cross-sectoral experience spanning multilaterals, international civil society organizations and multinational advertising.

Photo credit: Nutthaseth Vanchaichana