When Banking AI Meets Mobile Money: Safaricom, MPesa and Kenya’s Digital Finance Revolution

By Benadeta Mwaura - Reporter

Kenya, December 5 2025 - A 2025 survey by Central Bank of Kenya (CBK) found that among banks using AI, 65% apply it for credit risk scoring, making it the leading application of AI in Kenya’s lending sector.

According to CBK Governor Dr, Kamau Thugge,“The adoption of AI has brought about operational efficiencies, particularly in credit risk management, cybersecurity and customer service,”

Other common uses include fraud risk management, digital onboarding and eKYC. Still, many lenders remain in early stages: a more recent CBK backed report shows 67% of financial institutions assessed are “AI immature”, either at pilot stage or not yet beyond basic awareness.

That lag may reflect concerns over transparency, data governance and model explainability, all flagged by banks themselves when asked about AI adoption challenges. On the mobile money front, Safaricom is rolling out a sweeping upgrade to MPesa under a new “Fintech 2.0” platform, cloud native, AI embedded and built for scale.

At the 2025 Cybersecurity Summit, Safaricom’s CEO Peter Ndegwa said, “Cybercrime is a challenge no single institution can solve alone.” He revealed that MPesa now runs real time fraud detection and risk scoring, predictive monitoring and “self healing” systems, capable of handling up to 12,000 transactions per second.

Ndegwa said the AI upgrades are already paying off, “We have seen a huge reduction in fraud incidents thanks to AI … it’s helping us detect identity theft, prevent social engineering and deliver worry free digital services.”

Beyond security, MPesa’s upgrade also brings tap to pay, wallet sharing and split payment features, enhancing convenience and access for millions of users across Kenya. For consumers, especially those underserved by traditional banks, the convergence of banking. AI and mobile money upgrades could offer easier loan access, faster payments, improved fraud protection and more inclusive financial services.

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AI driven credit scoring may open up lending for those who previously lacked formal credit history; and when integrated with MPesa, these services may reach rural and informal sector users just as easily as urban ones.

For Kenya’s fintech savvy population, the blend of traditional banking and mobile money under AI governance promises a future where savings, loans, payments, and everyday transactions live on the same secure, responsive platform.

Yet the transformation is uneven. Many banks remain “AI immature,” and CBK has warned that rushing adoption without robust data governance, including transparency, explainability and bias safeguards, could erode public trust and undermine customer protection.

Moreover, as AI powered platforms become targets for cybercriminals, especially deep fake scams and phishing, the need for strong regulation, real time monitoring and user education grows ever more urgent.

Kenya seems to be building toward a digital first financial ecosystem, where banks, mobile money, chatbots, AI driven risk models and fintech converge, reshaping what “banking” and “money” mean in 2025/26.