AI-Powered Fraud Detection for Global Fintech
Reducing false positives by 87% while increasing detection rates
The Challenge
Our client, a major fintech company processing millions of transactions daily, was struggling with their existing fraud detection system. It generated too many false positives, requiring expensive manual reviews and causing customer frustration. Meanwhile, sophisticated fraud attempts were still slipping through.
Our Solution
We developed a multi-layered AI fraud detection system that combines several advanced technologies:
- Machine Learning Models: We trained ensemble models on historical transaction data to identify subtle patterns indicative of fraud.
- Behavioral Biometrics: The system analyzes user behavior patterns to spot anomalies that might indicate account takeover.
- Network Analysis: Mapping relationships between accounts, devices, and transactions to identify coordinated fraud rings.
- Real-time Decisioning: All analysis happens in milliseconds, allowing for instant transaction approval or further verification.
The solution was designed to continuously learn and adapt to new fraud patterns through both supervised and unsupervised learning techniques. It integrates seamlessly with the client's existing transaction processing systems and provides an intuitive dashboard for their fraud analysts.
Results
- 87% reduction in false positive alerts
- 34% increase in fraud detection rate
- Estimated $15M in annual savings from prevented fraud
- 95% reduction in manual review time
- Improved customer experience with fewer legitimate transactions being flagged
The AI fraud detection system developed by Intelik has transformed our fraud prevention capabilities. We're catching more actual fraud while dramatically reducing false positives, which has both improved our bottom line and enhanced customer satisfaction.