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Leading Mobile Money Provider
70%
Reduction in Fraud Losses
$50M
Annual Savings
50%
Fewer False Positives
15M+
Daily Transactions Processed
Mobile money has transformed financial services in Africa, but rapid growth has attracted sophisticated fraudsters. Our client, a leading mobile money provider, was losing millions annually to fraud while struggling to balance fraud prevention with customer experience. Traditional rule-based systems couldn't keep up with evolving fraud patterns and generated too many false positives.
We developed an AI-powered fraud detection system that analyzes transactions in real-time, identifies suspicious patterns using graph neural networks, and blocks fraudulent activity before funds are lost—all while maintaining sub-100ms latency.
Rising fraud losses threatened user trust and business sustainability.
Fraud losses exceeding $70M annually
Rule-based system generating 40% false positives
New fraud patterns emerging faster than rules could adapt
SIM swap fraud causing significant account takeovers
Organized fraud rings exploiting network vulnerabilities
Customer complaints about legitimate transactions being blocked
Real-time ML-based fraud detection system with graph neural networks and behavioral analysis.
Every transaction scored in under 100ms with ML models.
Network analysis detecting fraud rings and suspicious clusters.
Device and behavior patterns identifying account takeover attempts.
Models continuously retrain on new fraud patterns.
Investigation tools for fraud analysts with AI-assisted insights.
Automated verification for suspicious transactions.
Our phased approach ensured successful delivery and adoption.
Analyzed historical transactions and fraud cases to build training datasets.
Built graph neural network and behavioral analysis models.
Deployed low-latency scoring infrastructure handling 15M+ daily transactions.
Ran models in parallel with existing system to validate performance.
Full deployment with continuous model improvement.
Measurable outcomes that transformed the business.
70%
Reduction in Fraud Losses
AI detection dramatically reduced successful fraud attempts.
$50M
Annual Savings
Direct savings from prevented fraud and reduced false positives.
50%
Fewer False Positives
ML models much more accurate than rule-based system.
15M+
Daily Transactions Processed
System handles full transaction volume with sub-100ms latency.
< 100ms
Scoring Latency
Real-time scoring without impacting transaction speed.
85%
Fraud Ring Detection
Graph analysis identifies organized fraud networks.
“VE.KE's fraud detection system has been transformative. We've reduced losses by 70% while actually improving customer experience by blocking fewer legitimate transactions. The ROI was achieved in the first quarter.”
Head of Risk
Leading Mobile Money Provider
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