AI is becoming part of a bigger attempt by Nigerian banks to solve one of agriculture’s oldest problems: how to finance farmers who have little formal financial history, limited collateral, and unpredictable incomes.
First City Monument Bank is now pushing further into that problem, using agricultural technology, artificial intelligence, local language tools, climate data, and insurance as part of a strategy aimed at making smallholder farming easier to assess, support, and finance.
The shift is significant because the problem is not simply that farmers need more loans. Banks also need better ways to understand the farmers they are lending to.
The problem starts with data
Smallholder farmers make up a large part of Nigeria’s agricultural economy, but many operate outside the formal financial system. For banks, this creates a difficult lending equation. A farmer may have productive farmland and a viable business but still lack the conventional records, collateral, and credit history used to assess borrowers.
FCMB’s Agritech Alumni Impact Report, covering the period from 2018 to 2026, points to this financing gap as one of the reasons the bank is expanding its use of agricultural technology.
The bank has identified tools such as weather information, soil intelligence, and USSD-enabled platforms as ways to generate more useful information around agricultural activity.
That changes the role technology can play. Instead of simply putting a banking app in a farmer’s hands, agricultural technology can help create a digital trail around what is happening on the farm, from production conditions to weather risks and farmer activity.
For a financial institution, that information could eventually make agricultural risk easier to understand.
FCMB’s agritech bet started years ago
FCMB’s current strategy is not a sudden move into agritech. The bank began its Agritech Incubation Programme in 2018 with Wennovation Hub, targeting startups working on areas including agricultural finance, insurance, procurement, supply chain management, and other technology-driven agricultural solutions.
That first programme attracted 198 applications from across Nigeria, with 10 teams eventually selected for the final stage. Crop2Cash emerged as the winner, while Dilivas Box took the runner-up position. The following year, the programme attracted 320 applications. Ten startups pitched at the 2019 demo day, with AgroBarn winning the top prize and Agrico finishing as first runner-up. FCMB awarded N2 million and N1 million respectively in grants.
What began as a way of finding and supporting promising startups has since become a broader ecosystem involving technology companies, investors, and development organisations. FCMB now describes its agritech offering as including incubation support, hackathons, and grants for startups developing solutions across agriculture and food systems.
That history matters because it shows that the bank is not treating technology as a side project. It has spent years trying to identify where startups can solve problems that conventional banking products cannot.
AI is moving closer to the farmer
The next phase is more ambitious. FCMB plans to support AI-powered agricultural advisory platforms that can provide farmers with real-time information in Hausa, Yoruba, and Igbo. This is more than a language feature. A significant barrier to digital agricultural services is that many tools are designed around English-speaking and digitally sophisticated users. Local language support could make agricultural information more accessible to farmers who have previously been excluded from those platforms.
It could also allow technology to deliver practical information around farming decisions without requiring farmers to navigate complex English language interfaces. For FCMB, the larger opportunity is connecting that advisory layer to financial services. If a technology platform can collect useful information about agricultural activity, provide farmers with relevant advice, and create a clearer picture of their operations, it potentially gives financial institutions more information with which to assess agricultural businesses.
In other words, AI may not just be helping farmers farm. It could help banks understand who they can lend to.
Climate risk is becoming a banking problem
There is another reason this technology matters: farming is becoming harder to predict. Weather changes, extreme conditions, and other climate-related shocks can affect harvests and farmer incomes, creating risks for both farmers and lenders.
FCMB’s next phase includes climate-resilient agricultural financing and bundled insurance products, alongside animal healthcare solutions. The idea is important because a loan on its own does not protect a farmer when a major agricultural shock destroys the income expected to repay it. Combining financing with insurance and climate information could instead create a more resilient financial product.
This is part of a broader movement in agricultural finance. Climate information is increasingly being combined with credit, insurance, and agricultural inputs to help smallholder farmers manage risk and continue investing in production. A 2026 agricultural resilience project in Uganda, for example, is testing a bundled model involving climate advisories, credit, insurance, and inputs for 7,000 coffee and tea farmers.
For Nigerian banks, the implication is clear: understanding agricultural risk may increasingly require more than looking at a farmer’s bank statement.
Nigerian agritech is also looking beyond Nigeria
FCMB’s ambitions extend beyond financing farmers in Nigeria. The bank plans to support the expansion of Nigerian agritech startups into other African markets, including Uganda, Ghana, Côte d’Ivoire, Ethiopia, and Kenya. That could give Nigerian agritech companies a route into markets facing similar problems around financial exclusion, agricultural productivity, and climate risk.
It also represents a different kind of opportunity for the Nigerian technology ecosystem. Rather than building agricultural startups only for Nigeria’s domestic market, companies could develop products that solve problems shared across African farming economies.
The challenge, however, will be execution. Agricultural technology does not automatically translate into adoption. Farmers still need reliable connectivity, affordable services, trust, digital literacy, and solutions that work within the realities of rural communities. Banks also have to prove that the data generated through these platforms can actually improve lending decisions rather than simply create another layer of technology.
The bigger bet is not AI
FCMB’s agritech strategy ultimately points to a bigger change in how financial institutions think about agriculture. The opportunity is not simply to give farmers another digital tool or another loan, it is to build enough information around agricultural activity that farmers become easier to support, insure, and finance. That means combining AI with local language services, agricultural data, climate intelligence, insurance, and financial products, and if that model works at scale, the biggest change may happen quietly.
A farmer who was previously considered too difficult to assess could become a customer with a measurable business, a digital record, access to tailored advice, and financial protection against agricultural shocks. That is the real technology story behind FCMB’s latest agritech push.
The bank is not just trying to finance agriculture. It is trying to make agriculture more visible to the financial system.
