For many smallholder farmers, the problem is not the absence of economic activity. It is the difficulty of translating that activity into information that financial institutions can use. Farmers plant, invest in inputs, harvest, sell produce and, in some cases, repay loans, but much of that activity happens outside the conventional financial records used to assess creditworthiness.

Dennis Okpe, co-founder and CEO of Heabron Farm Limited (Heabron), wants to change that. Raised by rural farmers in Benue State and now building technology around agricultural data, he believes better information can help financial institutions understand the productive and financial behaviour of farmers who have historically been difficult to assess. Through CoopScore, Heabron is building what Okpe describes as a data infrastructure layer for African agriculture, capturing farmers' activities and turning them into credit intelligence for lenders, insurers and other agricultural institutions.

In this interview with AgroCentric, Okpe discusses the data gap in agricultural finance, how Heabron works with farmer groups and local agents, what transaction-level agricultural data can reveal, why institutional adoption remains a challenge, and his ambition to build agricultural financial identities for farmers across Nigeria and eventually the ECOWAS region.

For readers who may be meeting you for the first time, can you tell us a little about yourself and your journey into agriculture?

My name is Dennis Okpe, and I’m the co-founder and CEO of Heabron. I’m an engineer by profession, but agriculture has been part of my life for as long as I can remember. My parents were rural farmers in Benue State, while I grew up in Lagos with the help of my uncle. During the holidays, I would return home and help my mum on the farm, so I grew up seeing both the realities of farming and the people behind it.

Professionally, I moved into agriculture about eight years ago. My experience has taken me through different parts of the agricultural value chain, including processing and aggregation, and eventually into agricultural finance and technology.

How did that experience lead to Heabron?

Heabron was registered as a business in 2019 and we initially worked with rural rice farmers across processing and distribution. However, we soon realised how capital-intensive processing was, so we pivoted to aggregation.

We began working with farmers growing maize, rice, soybean, groundnut, sorghum and sesame, connecting them with ready markets for their produce. This brought us closer to farmers and exposed us to another major challenge: access to finance.

Farmers regularly approached us for loans, but I did not have the capital to provide them. I started exploring ways to connect them with banks and other financial institutions, but found that many were reluctant to lend to rural farmers because they considered them high-risk borrowers.

Was that when you began to see the data gap as part of the financing problem?

I began to realise that much of farmers’ economic activity happens on the farm and does not necessarily appear in a bank statement. Farmers plant, buy inputs, harvest, organise themselves into groups and sell their produce, but much of this activity was not captured in a form that financial institutions could use.

We began thinking that if we could capture these activities, assess the associated risks and turn the information into credit profiles, lenders would have better data to make financing decisions. That thinking eventually led to CoopScore, our data intelligence platform.

Is data the biggest challenge holding back African agriculture?

There are several challenges, but if I had to put one at the top, I would say data. Reliable data is essential for understanding the sector, making informed decisions and managing risk effectively.

Compared with other sectors, identifying, quantifying, pricing and managing risk is particularly challenging in smallholder agrifinance. Without reliable information on farmers, their production, repayment history and other relevant factors, it becomes difficult for financial institutions and other stakeholders to assess and price that risk.

But data alone will not solve the problem. Another major challenge is the lack of alignment across the agricultural value chain. We need what I call shared risk, where insurance companies, financial institutions, input providers and farmers operate within a framework in which each stakeholder takes on part of the risk.

This also requires the right policy, regulatory and public infrastructure to build and strengthen credit and insurance markets in complementary and mutually reinforcing ways.

When these pieces come together, reliable data can support better decisions, stakeholders can share risk more effectively, and the financial system around smallholder agriculture can become more sustainable. That is critical to building a more sustainable food system in Africa.

Was there a particular experience that made you realise how difficult it was for smallholder farmers to access formal finance?

I saw this while working with the local government after transitioning into agriculture. Many farmers needed money at the beginning of each season to buy inputs, but banks often turned them down because they lacked acceptable collateral. They had land, but without a certificate of occupancy, it could not easily serve as security.

Season after season, many returned frustrated and eventually turned to local lenders charging very high interest rates.

What stood out to me was that these farmers were producing, selling and organising themselves into associations, yet little of that activity was being captured in a way that could support their access to formal finance. That made me start thinking about how their economic activity could be documented and used to give financial institutions a better basis for assessing them.

What drives your commitment to improving access to finance for smallholder farmers and strengthening food security?

There is so much value in agriculture, smallholder farming and rural communities. When rural people have access to the right tools, knowledge and finance, they can improve their productivity and grow higher-yielding crops.

I want to see that potential properly supported and turned into better opportunities for the people who are already doing the work.

What did you see in the agricultural finance system that convinced you this was a problem worth building Heabron around?

I started Heabron because of the fundamental gaps I saw while working with farmers in how agriculture was being financed. The financial system did not have enough visibility into the economic activity taking place on their farms.

While the lending decisions of financial institutions often depend on information such as bank statements and collateral, farmers’ economic lives happen largely in the field. This creates a disconnect between the realities of how farmers earn and operate and how their creditworthiness is assessed. That realisation led us to build CoopScore by Heabron.

So, is the challenge really a shortage of capital, or is the bigger issue what prevents financial institutions from deploying the capital they already have?

In many cases, the capital is available, but financial institutions are concerned about the risk involved in lending to farmers and do not have enough information to assess that risk properly.

There is also the cost of reaching and serving these farmers. Banks are businesses, so they have to consider the cost of acquiring customers and whether the returns from lending to them justify that cost. They also have to account for loan origination and recovery.

These are some of the factors limiting the deployment of capital into rural agriculture. Data is one part of the problem, but so are loan origination, customer acquisition and recovery costs. All of these factors determine whether financial institutions can practically deploy capital to rural farmers.

Let’s talk about the solution Heabron is building. How are you approaching the challenge of making agricultural lending more practical at the community level?

At Heabron, we have seen that one way to make agricultural lending more practical is to work with farmer groups rather than individuals. When 10 or more farmers come together as a cluster, it becomes easier to coordinate financing, monitor activities, and manage repayment.

Financing also doesn't have to be given as cash. We first identify what farmers need for the season and provide inputs such as fertiliser or herbicide. That helps reduce some of the risk.

We have also realised that local relationships matter. In many rural communities, people know each other, so our agent network is built around people who understand the community and its associations. If an agent can vouch for a farmer or association, that local knowledge creates a level of trust that an outsider may not have.

So, for us, the solution is about combining data with farmer groups and trusted local networks to make it easier to deploy and recover capital.

You describe Heabron as Africa’s agricultural credit infrastructure. For someone hearing about the company for the first time, what does that actually mean?

Heabron is building the data infrastructure for African agriculture, creating an intelligence layer between farmers and providers of capital and other agricultural services.

We turn farmers’ activities into credit profiles that financial institutions and insurance companies can use for lending and underwriting decisions. Other agricultural businesses can also use the information to better understand the markets and communities they serve.

A good comparison is a credit bureau. It does not provide loans; it provides information that financial institutions use to make lending decisions. We are applying that principle to agriculture through CoopScore, where much of farmers’ economic activity is still not captured in a form institutions can easily use.

We are not trying to become every provider in the agricultural ecosystem. We are building the underlying infrastructure that helps different players make better decisions.

You capture details about farmers’ planting, harvesting, delivery, payments and other activities. What can this transaction-level history reveal about a farmer that conventional credit assessments may not capture?

We aim to capture the full picture of a farmer’s economic activity, not just what appears in a bank statement.

It starts with the farmer’s profile, including name, phone number, gender, age, location and KYC verification. We then look at the farm itself, including its location, size, crop type and plots, as well as acreage, expected and actual yield, planting and harvest dates.

We also record the inputs used, such as the type and quantity of seed and fertiliser and how much the farmer spends. This helps us understand the relationship between what goes into the farm and what comes out of it. Expected yield is also assessed based on the local context because the same crop can perform differently across regions. Someone planting soybeans in Ogun State, for example, may have a different expected yield from a farmer in the North-Central region.

On the financial side, we track financing requested, approved and disbursed, as well as payment and repayment behaviour. Even where a farmer has not taken external financing, we can see what they have invested themselves.

We also record production and transaction activity, including what was planted and harvested, where it was sold, the buyer and the volume involved. Association, market and buying activity provide further context.

Another important component is field and extension data. When an agent visits a farm, observations are recorded, allowing us to monitor production throughout the season rather than waiting until harvest. For example, if a rice farmer’s crop takes roughly 90 or 91 days to mature, depending on the variety, field visits can identify issues such as flooding while they are happening.

We also track outcomes such as farmer income, productivity and jobs created. When these records are combined, they provide a clearer picture of a farmer’s productive capacity, transactions, financing behaviour and performance over time.

These are the core areas we currently cover, although we are still working to incorporate some additional external data points.

Could Heabron’s data become a new form of financial identity for farmers?

Yes, this is possible, and there are growing conversations around alternative credit data because smaller farmers operate differently from conventional borrowers.

The data we are building can provide an additional layer of credit intelligence alongside the information financial institutions already use. As farmers build records across multiple seasons, they develop a history of their production, transactions and financing behaviour that goes beyond a single loan application.

Once financial institutions begin using this information at scale, it can become an important part of how agricultural finance is assessed and potentially complement, or in some cases replace, some traditional methods.

Nine months into CoopScore, what has adoption looked like, and what have you learned from the market?

With financial institutions, we have had a lot of conversations and meetings. They understand the need, but adoption has been difficult because they already have established credit assessment criteria. One challenge is that some want to lend to us and have us take on the risk of lending to farmers.

Our position is different. We believe financial institutions should be able to use agricultural data, just as they use available information to assess SMEs, rather than simply passing the risk to us. Alternative credit intelligence is gaining more attention, particularly among development finance institutions and organisations working with rural farmers.

We are also building for the future. Every farming season gives us another layer of credit intelligence. We currently have more than 2,000 rural farmers on the platform, with financial identities built across two planting seasons.

We have also used our own balance sheet to provide more than ₦50 million in input financing to test repayment, before selling inputs to farmers at discounted rates and connecting them to ready markets. We are also in discussions with several development organisations around potential partnerships.

So, institutional adoption is still developing, but we are building the data, testing the model and demonstrating what alternative agricultural credit intelligence can offer.

One thing that would encourage adoption is regulation: if the CBN provides a regulatory framework, or development finance institutions support the model once they understand its value, PFIs, merchant banks and commercial banks can also begin to adopt it.

There also needs to be some form of risk protection. Organisations like NIRSAL - De-risking Agriculture Facilitating Agribusiness could potentially provide a level of security for loans provided by banks. If an organisation like NIRSAL partners with us and gives financial institutions greater confidence to lend directly to farmers, that could encourage adoption.

Insurance companies also have an important role to play, particularly in protecting input credit. When financial institutions know that some of the risks are covered, they are more likely to consider lending through these models.

Beyond the challenges of building the business, what has entrepreneurship taught you about leadership and working with people that your earlier experience in agribusiness did not?

Building Heabron has taught me a lot about resilience. You have to be dogged and present.

I have also learned the difference between networking and building relationships. You cannot meet someone for the first time and immediately expect them to invest ₦100 million in your business. Relationships take time. You meet, continue the conversation, build trust and, eventually, that can lead to a partnership or collaboration. I call it the four levels of relationship building: connection, continuous discussion, trust, and partnership or collaboration.

I have also learned a lot about hiring and building a team. Your employees are not your friends or family, so you have to maintain professional boundaries. In a lean team, it is easy for those boundaries to disappear, but everyone needs to understand their responsibilities and what is expected of them.

What is one assumption about agriculture, finance or technology that you had to unlearn after becoming a founder?

One assumption I have had to unlearn is that there is simply a lot of money in agriculture. People talk about the sector’s potential without always explaining the risks involved. There may be opportunities in agriculture, but you cannot focus on potential returns without doing proper due diligence and understanding the risks.

Another assumption is that technology alone will solve Africa’s agricultural challenges. Technology is important, but it is only part of the solution. We still need the right infrastructure, inputs, information and support systems around farmers.

Technology is not just an app or a platform; it can mean climate-smart inputs, timely weather information, or simply improving how farmers do their work.

What has building Heabron taught you about dealing with uncertainty, disappointment and partnerships as a founder?

If I would say anything, it is that nothing has really surprised me. As a founder, I have learnt to expect disappointment. I have learned to lower my expectations and remain open to whatever happens.

Someone might promise to provide funding and then stop answering your calls. A partnership can also fail after months of meetings, planning and work. You may invest a lot of time in something, only for it not to work out.

However, disappointment helps you refine what you are doing and, ultimately, it helps build you as a founder. I would not call it a surprise; I would simply say it is a part of the journey.

Looking ahead to 2030, what are the key steps Heabron needs to take to reach one million farmers and build the agricultural data infrastructure you envision?

Number one is capital. We are currently raising $300,000, which we believe will allow us to onboard about 20,000 rural farmers. Scaling farmer onboarding and having the working capital to support it requires funding.

Our greatest advantage is the data we are building. Reaching 20,000 farmers would also help unlock more partnerships and conversations with state and federal governments, which could accelerate our path towards one million farmers.

We are trying to capture, as one of my mantras goes, “one farmer, one state, one local government” at a time. That is why we started with Oyo State. We want to understand how things work within a state, capture farmers across its local governments and then expand into the North-Central region and other parts of Nigeria.

So, the key steps are raising the capital to scale, building the data and using that foundation to unlock partnerships and expand geographically. By 2030, we believe we can reach most of Nigeria’s five geopolitical zones.

Beyond the number of farmers on the platform, what would convince you that Heabron is genuinely succeeding? What changes would you want to see for farmers and the institutions working with them?

Success for us would mean farmers becoming more bankable. They should be able to use verified agricultural records to demonstrate their economic activity and access finance.

It would also mean financial institutions trusting our data enough to integrate it into their lending and portfolio-monitoring processes. We want to see better access to inputs, markets and risk protection, leading to better outcomes for farmers.

Ultimately, Heabron should become a trusted source of agricultural data that institutions can use to make decisions, with a model that can scale across Nigeria and eventually the ECOWAS region.

If we have this conversation again in 2030, what would you hope has fundamentally changed about how African farmers access finance and participate in formal markets?

What we hope will change by 2030 is that a farmer’s ability to access finance will no longer depend primarily on collateral or a traditional banking history.

Instead, farmers should be able to build a digital financial identity from their actual agricultural activity, including their production, input use, participation in organised groups, sales and repayment behaviour.

If you are working and earning a salary, your income and financial behaviour should contribute to building your credit profile. If you are a farmer, your agricultural activity should also be recognised as part of your financial identity.

Financial inclusion for rural smallholders will not happen through conventional bank statements or urban lending models. Dennis Okpe’s work at Heabron demonstrates that when alternative credit intelligence replaces rigid collateral requirements, rural farmers can build sustainable livelihoods while strengthening national food security. To follow Dennis’s work and learn more about Heabron, connect with him on LinkedIn and visit Heabron’s LinkedIn Page.

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