A Startup Processed 1B Transactions To Give 8M Africans A Credit Score Banks Wouldn’t

In Harare, a man buys bricks with cash and pays the builder the same way. Over months, he pours concrete for the foundation, raises the walls to window level, and carefully budgets to get the timber for the roof. Then, abruptly, he stops.

For five or six years, the house sits there—open to the sky, half-finished—while he saves up again. When he finally puts the roof on, it only covers half the structure. He moves in without tiles or paint, spending another decade completing what should have taken six months.

Dalumuzi Mhlanga grew up watching this pattern. It had nothing to do with poverty but the absence of a financial instrument that could stretch a repayment over years. They had the income, the land, and the discipline. What they did not have was a bank willing to look past their account balance.

Mhlanga is now the founder and CEO of Notto, which calls itself Africa’s first licensed alternative credit bureau. The company has analysed over a billion transaction records and generated more than eight million credit scores across the continent. But the origin story of Notto is less about big data and more about a deeply personal paradox he observed long before he wrote a line of code.

“It started with members of my own family who had been paying rent in full and on time for years,” he tells WT. “They were consistently meeting this very significant financial obligation, but they still could not access home loans.”

That contradiction became the intellectual and emotional anchor for his work. If credit is fundamentally about determining whether a person is willing and able to meet obligations consistently, then why does paying rent—often the largest monthly expense a person has—count for nothing?

The contrast crystallised during his freshman year at Harvard. Almost weekly, his mailbox contained another unsolicited credit card offer from Capital One. He had virtually no income at the time, yet the American financial system was already prepared to begin a relationship with him.

“On one side, you had people in Africa who had demonstrated for years that they could meet significant obligations, but the system could not see them. On the other side, you had a system that was willing to look beyond somebody’s account balance today.”

When the Zimbabwean founder and his team initially built Notto, they thought they were solving a product problem. They designed a specialised credit score for home loans. After two years, they realised they had started at the wrong end of the chain. The issue was not a missing product, they discovered, but absent infrastructure. The plumbing required to identify rent payments, utility bills, and mobile money behaviour simply did not exist in a standardised form.

The internal enemy

What makes this problem particularly stubborn, Mhlanga argues, is not a lack of lender interest. Banks know the opportunity is massive. The real friction sits inside the banks themselves.

“Large enterprises have governance structures and processes,” he explains. “The idea may need to go through a product committee, a risk committee, a credit committee, technology, compliance and then the people who actually release the balance sheet.”

By the time an initiative reaches the finish line, the quarterly targets that drive staff bonuses have rolled over several times.

“Infrastructure does not always produce results inside one quarter,” he adds. “Somebody is sitting there thinking: this may take too long to yield results, and may even wonder if they may still be in the organisation by that time.”

So the obstacle is less a misconception about creditworthiness and more an architecture of institutional inertia, Mhlanga reckons. Banks are designed to manage risk and hit short-term metrics. Alternative data, he points out, does not fit neatly into that machine, yet.

The loan shark paradox

After processing over a billion transaction records, Notto’s data revealed something that contradicts the industry’s cautious posture. Some of the most creditworthy Africans are already paying exorbitant rates to informal lenders and still repaying faithfully.

“You see people taking loans at 20 or 30 percent interest month on month, and they pay them back,” Mhlanga says. “The market is still a bit of a wild, wild west, and many lenders have not figured out how to price risk properly. They price for the risk of the entire portfolio, so they charge that same very high rate to some of the most creditworthy people.”

This is the hidden tax on financial invisibility. People who could easily service a low-interest mortgage are instead borrowing from loan sharks at predatory rates simply because the formal system cannot verify them.

Notto’s infrastructure tries to separate that population from the high-risk pool using non-traditional signals, such as digital payment receipts, mobile money inflows, and regular bill settlements.

The pivot that saved the company

There was a moment when Mhlanga genuinely questioned whether the model would survive. The original plan was B2C, that is, to collect alternative data directly from tenants and landlords to generate specialised scores. “The data collection was slow, expensive and difficult to scale,” he admits.

The pivot was painful but decisive. Instead of gathering raw data themselves, they decided to work with enterprises—telcos, payment gateways, and fintechs—that already had it.

They would build the infrastructure to turn that existing data into credit intelligence at scale. The shift transformed the company, but integration became the new challenge. Mhlanga notes that banks do not discard their legacy risk frameworks overnight, and alternative data must live alongside existing credit policies before it can replace them.

Who guards the guardians?

The use of non-traditional data inevitably raises questions about privacy and fairness. Mhlanga’s response is to lean heavily into regulation. Notto operates as a licensed credit bureau, he emphasises, subject to data protection, consent, and residency laws in each market.

“I do not see regulators as constraints to innovation,” he says. “Regulators are protecting consumers, and consumers need to be protected. A company should not simply say, ‘Trust us,’ especially when it is dealing with people’s financial information.”

It is a prudent stance, but it does not resolve the deeper tension in that the same data that unlocks a mortgage could also be used to exclude, price-gouge, or surveil. For now, Mhlanga trusts the oversight frameworks to draw that line.

The long bet

Looking ahead, Mhlanga measures success not by the number of microloans disbursed but by the length of the credit. He wants a young couple in Lagos, Conakry, or Mali to walk into a bank and leave with a twenty-year mortgage. Not only does that require a leap of faith about economic stability, but it also demands a cultural shift.

“Your credit score should matter more than your account balance,” he insists. “An account balance is only a picture of where you are today. Creditworthiness tells us something about your future.”

When asked if he would pass his own test using only digital transaction data, Mhlanga does not hesitate. He applies the same three filters he uses for every customer: consistent income, bills paid in full and on time, and enough residual capacity to save. He believes he passes all three.

The real question is whether Africa’s financial system will ever learn to ask the same questions. For now, millions are still building their homes one brick at a time, not because they cannot pay, but because the system refuses to believe them until they already have.