Safaricom's M-Pesa, Africa's most successful mobile money platform serving tens of millions of users in Kenya and beyond, faced growing fraud threats as transaction volumes and values increased. Fraudsters used increasingly sophisticated techniques including social engineering, SIM swaps, and account takeovers to steal from M-Pesa users. Traditional rule-based fraud detection created too many false positives, frustrating legitimate users, while missing evolving fraud patterns.
Safaricom deployed AI-powered fraud detection systems that analyzed transaction patterns, user behavior, device fingerprints, and network data in real-time to identify suspicious activity. Machine learning models adapted to new fraud techniques automatically, learning from both confirmed fraud cases and false positives to improve accuracy. The company also launched Fintech 2.0, integrating AI throughout its financial services platform to enable new products like AI-assessed micro-loans and personalized savings recommendations.
“AI allows us to protect our customers from fraud while enabling new financial services that were impossible with traditional technology.”— Peter Ndegwa, CEO, Safaricom
This case study is based on publicly available information about Safaricom / M-Pesa.
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