The Next Wave: The age of lending to strangers is ending

The first generation of African digital lenders believed it had found banking’s blind spot. Millions of people earned money, ran businesses and moved cash around every day, yet remained invisible to lenders because they lacked collateral, formal employment or a long relationship with a bank. Technology promised to close that gap. If banks lent against paperwork, fintech would lend against data.

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It was one of the easiest stories in African tech to believe because the numbers appeared to support it. Credit penetration remained low by global standards, large parts of the economy operated informally and traditional lenders had little appetite for small borrowers. The total addressable market looked enormous. If hundreds of millions of people lacked access to formal credit, then surely the opportunity for digital lenders was measured in the tens of billions of dollars.

What the industry may have confused was demand for credit with the ability to build a profitable lending business around it. Those are not the same thing.

A payments company benefits every time money moves through its network. A lender only wins if the money comes back. The distinction sounds easy, but much of the first generation of fintech lending was built as though software economics would eventually overpower lending economics. Acquiring customers cheaply, automating underwriting, disbursing instantly, and scaling would take care of the rest. Instead, lending behaved exactly as lending has behaved for centuries.

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This week, Tala announced another restructuring exercise affecting teams across all of its markets as it centralised more functions and reduced local operating complexity. In Kenya, seven employees were affected out of roughly eighty-five staff, following another round in April 2025 that affected twenty-eight employees locally. The headlines naturally focused on the layoffs, but the more interesting story sits underneath them.

Tala is not retreating from Kenya and it is not leaving lending behind. The company appears to be moving away from the old idea that large local teams and ever larger volumes of unsecured consumer loans create durable businesses. Embedded finance, partnerships and products attached to existing commercial relationships offer something consumer lending apps have struggled to find consistently over the last decade: visibility into repayment.

Branch Mfb has arrived at a similar destination through a different route. Earlier this year, the company cut staff in Kenya and Nigeria despite generating roughly $30 million in profit globally. During the years when capital was ‘cheap’, investors rewarded customer growth and loan book expansion above almost everything else. However, the mood has shifted. Investors now care more about margins, collections and capital discipline than they do about how quickly a lender can originate loans.

Then there is 4G Capital, which spent the better part of the last decade doing something that looked almost old-fashioned. While the rest of the industry tried to automate lending decisions and remove people from the process, 4G Capital built field teams, opened branches and focused heavily on merchants and small businesses whose inventory cycles and cash flows could actually be observed. Earlier this week, the company crossed $1 billion in cumulative disbursements across Kenya and Uganda.

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That milestone is important in this argument because it challenges one of fintech’s favourite assumptions. Technology did make lending faster and cheaper, but it never removed the need to understand the borrower. In many parts of Africa, relationship banking turned out not to be a relic of the past but an effective risk management tool.

Make no mistake, the market is not abandoning unsecured credit. Consumers still borrow for school fees, emergencies or entertainment because income volatility remains a feature of everyday life rather than an exception. The appetite for short-term loans remains enormous, and lenders are unlikely to run out of customers any time soon.

The most important question is whether there are enough customers who can support venture-scale returns from unsecured lending.

Central Bank data in Kenya points to this challenge. Two years ago, data from the regulator showed that loans below KES 1,000 ($8) recorded non-performing loan ratios above 80%, while loans below KES 5,000 ($39) have also struggled with repayment performance. Curiously, larger loans tend to perform better, which runs directly against the original digital lending thesis (that small loans were supposed to be safer because they were diversified, short-term and distributed at almost no cost).

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The industry has spent years treating this as an underwriting problem. Powerful algorithms, more behavioural data and larger transaction histories are supposed to produce better borrowers. After more than a decade of experimentation, another explanation looks more convincing: that the problem may have been income.

Better underwriting models can improve pricing at the margins and reduce fraud around the edges, but they cannot manufacture repayment capacity where disposable income is thin or unpredictable. Somewhere along the way, fintech convinced itself that lending was primarily a data problem waiting for a technical solution when, in reality, it remained what it has always been: a cash flow business.