How we built a real-time fraud detection system that reduced fraudulent transactions by 95% while maintaining seamless customer experience.
Fraud Reduction
Transactions/Day
Months Build Time
Fraud Detection System was operating with outdated rule-based fraud detection systems that generated high false positives and missed sophisticated fraud patterns. Their legacy security infrastructure was struggling to keep pace with evolving cyber threats.
We developed an intelligent, adaptive AI security framework that learns from transaction patterns, behavioral analytics, and fraud indicators to provide real-time threat detection with minimal false positives.
From legacy rule-based systems to intelligent AI-powered fraud detection that adapts and learns
We analyzed customer behavioral data, usage patterns, service history, and demographic information to identify churn indicators and patterns across different customer segments.
We built advanced ML models using ensemble methods to predict customer churn probability, integrated with automated retention campaign triggers and personalized offer generation systems.
The churn prediction system achieved high accuracy and reduced monthly churn. The company now proactively retains high-value customers with personalized offers before they consider switching.
The AI transformation delivered significant security improvements and operational efficiency
Significant improvement in fraud detection accuracy
Dramatically reduced false alarms improving customer experience
Instant fraud identification and prevention
Prevented fraud losses and operational cost reduction
Let's discuss how custom AI solutions can transform your regulatory compliance and reduce operational risk.
