How AI Credit Risk Scoring in Kenya Is Changing Who Gets Loans and How Fast

As Kenyan lenders face record loan defaults, a quiet shift is underway—AI is increasingly being trusted to decide who gets credit and at what cost.


AI credit risk scoring in Kenya is fast becoming the leading application of artificial intelligence in the country’s banking sector, a new Central Bank of Kenya (CBK) survey has revealed. The findings show that while only half of Kenyan lenders have adopted AI so far, 65% of those using the technology apply it specifically to assess borrower risk.

Digital credit providers are spearheading the trend, with 80% relying on AI for credit risk scoring. Microfinance banks follow at 75%, while commercial banks trail at 45%. The shift marks a growing move toward data-driven lending, as institutions seek faster, more accurate tools to approve loans and manage risk.

Credit risk assessment involves estimating a borrower’s likelihood to repay and plays a critical role in setting interest rates under risk-based pricing models. Traditionally, this process is time-consuming and prone to human error. But with AI, systems trained on large datasets are helping banks automate risk analysis, making it quicker and more precise.

“AI adoption has brought about operational efficiencies, particularly in credit risk management, cybersecurity, and customer service,” the CBK report noted.

Beyond AI credit risk scoring in Kenya, banks are also applying the technology to cybersecurity (54%), customer support (43%), fraud detection (43%), and digital onboarding (41%). Yet credit scoring remains the most common and the most desired application — even among banks that haven’t yet adopted AI.

Among lenders still on the sidelines, 83% said they plan to use AI for credit assessment. This includes 92% of commercial banks, 86% of microfinance institutions, and 77% of digital lenders. The survey points to a strong national consensus around the potential of AI credit risk scoring in Kenya to drive future improvements in lending.

The rising adoption comes as banks grapple with record-high non-performing loans, which now stand at Sh717 billion. The default rate has reached 17.7%, prompting a renewed push for smarter, more proactive risk tools.

Globally, AI in banking is often focused on fraud prevention and anti-money laundering. But in Kenya, lenders are putting their chips on credit assessment first — hoping AI will not only boost efficiency but also help reduce exposure to risky lending.

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By George Kamau

I brunch on consumer tech. Send scoops to george@techtrendsmedia.co.ke

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