"Machine learning models reduced fraudulent transactions by 92%, saving $3.2M annually."
Financial Services
6 months development
8 data scientists
The client, a major financial institution, faced increasing losses from sophisticated fraud schemes. Manual review processes were slow and often missed subtle patterns, resulting in significant financial and reputational damage.
We implemented a real-time fraud detection system using ensemble machine learning models, anomaly detection, and behavioral analytics. The system continuously learns from new data, adapting to emerging fraud patterns.
Random Forest, XGBoost, Neural Networks
Isolation Forest, Autoencoders
User profiling and risk scoring
Instant risk assessment for every transaction
Immediate notification of suspicious activity
Automated compliance documentation
Subscription model for banks and fintechs
Discover how our AI-powered fraud detection can safeguard your financial operations and boost profitability.