In Kenya, digital lenders used borrowers’ behavioural data to extend credit to people who might otherwise have been excluded by traditional banks. But the same technology that opened the door to credit could also slam it shut, with borrowers reported to credit reference bureaus over relatively small debts.
By the time Bloomberg reported on the issues in 2020, about 2.5-million Kenyans had been reported to credit reference bureaus by digital lenders. The promise had been inclusion, but the result for many was exclusion triggered by relatively small debts. And yet, many of those borrowers were offered credit precisely because of their behavioural data. Without it, traditional banking channels would never have cleared them.
Interestingly, Kenya’s regulator responded — and quickly. In April 2020, the Central Bank of Kenya set a Ksh1,000 (about R125) floor for negative credit listings and delisted borrowers who had been blacklisted for sums below it. It also withdrew unregulated digital and credit-only lenders’ access to the credit information sharing system. A licensing regime followed in 2022. By May 2026, the bank had licensed more than 220 digital credit providers which, between them, had advanced about 8.4-million loans worth about KSh150bn (approximately R20bn).
Harnessing the benefits
So, Kenya didn’t write off the technology completely but found a way to harness the benefits — widening the net for access while blunting its harm, particularly permanent exclusion over relatively small defaults.
Imagine a world where your behaviour can open doors previously beyond your grasp — and where, with the same speed, one mistake can exclude you forever. Your behaviour tells The Machine what it needs to know about what you can access. Then The Machine lets you in and locks you out, using the signals you have (unwittingly) generated.
This is what makes technology so difficult to argue about; it can feel like a much more objective arbiter of access than the systems we have today. But technology is an amplifier — of how we think and of opportunity and risk. This amplification depends on how it is built and, ultimately, who is watching.
Technology holds the power to open access, provided the design is intentional. The challenge is that AI draws conclusions from data we never consciously chose to provide. Consent remains critical but has less reach in a world of inference. We can opt out of marketing, for example, while leaving a digital footprint from which conclusions can be drawn.
Digital autonomy shifts the focus from what you have consented to hand over to what is inferred about you and, importantly, how those inferences are used. In practice, that means three things: you can see what has been inferred about you, you can contest it, and an adverse inference has an expiry date rather than following you for life.
High stakes
In the retail example, the worst-case scenario is a poor advert or irrelevant product. For financial services, the stakes are much higher. Inference is already built into the industry, assessing suitability, risk appetite and behavioural assumptions. AI takes this from the cohort to the individual, at scale. Imagine your digital footprint being used to prove eligibility or personalise savings and lending rates.
The principle is simple: make it easy to use data to let someone in, and hard to use it to shut them out. The traditional finance analogy already exists — it is typically easier to open a bank account than to have one frozen.
These are not easy conversations. But the size of the prize is significant, particularly in a country like South Africa, where formal financial exclusion remains a reality for many.
New technologies could be gamechangers for financial inclusion, provided the design is right. The design determines whether these technologies become door openers or shackles for life. This is not a problem for Silicon Valley to solve on our behalf. It is squarely ours, and time is ticking.
Bassier is chief operating officer at Ninety One.
