Nombank, a digital bank operating in Nigeria, is using the multi-billion naira transaction data flowing through its platform to underwrite loans for small and medium-sized enterprises, aiming to address a long-standing credit gap in the market. The bank, which launched in 2024, processes what it describes as a significant volume of monthly transactions, providing a real-time view of business cash flows that forms the basis for its lending decisions.
According to the company, this data-driven approach allows it to extend credit to SMEs that traditional banks often overlook due to a lack of formal collateral or extensive credit history. Nombank's chief executive, Olumide Olusanya, stated that the initiative is a direct response to the financing challenges faced by small businesses, which are frequently cited as a major constraint to economic growth across Africa. "By analysing the actual transaction behaviour of businesses on our platform, we can build a more accurate picture of their health and capacity to repay," Olusanya said.
The move taps into a critical need in Nigeria's economy, where SMEs contribute nearly half of the national GDP but consistently report access to finance as a primary obstacle. Conventional lending institutions typically require physical assets as security, a requirement that excludes many small businesses operating in the informal sector or those without substantial property. Nombank's model represents a growing trend in African fintech, where companies leverage alternative data—from mobile money transactions to utility payments—to create new credit scoring mechanisms.
Nombank's entry into SME lending comes amid increased activity in Nigeria's digital banking and fintech lending space, though the sector faces heightened regulatory scrutiny. The Central Bank of Nigeria has been implementing measures to ensure responsible lending and protect consumers from over-indebtedness. In this environment, Nombank asserts that its use of proprietary transaction data offers a more sustainable and risk-aware model than some earlier digital lenders that relied heavily on aggressive mobile marketing and less transparent scoring methods.
The success of the strategy will depend on the bank's ability to accurately interpret transaction data to predict defaults while scaling its loan book profitably. Other players in the market, including some neobanks and fintech firms, have explored similar models with varying degrees of success, highlighting the technical and market challenges involved. Nombank did not disclose specific figures for its current loan portfolio size or default rates, noting that the SME lending product is still in its early stages of rollout.
Industry observers note that while data-centric lending holds promise, its effectiveness over a full economic cycle remains to be proven in the Nigerian context. Economic volatility and external shocks can quickly alter a small business's cash flow, potentially challenging the algorithms built on historical transaction patterns. Nonetheless, Nombank's pivot to leverage its core banking data for credit represents a logical expansion for a digital bank seeking to deepen its relationship with business customers and build a more diversified revenue stream beyond transaction fees.