A global financial institution offering a wide range of banking and investment services. The client needed a more accurate and scalable fraud detection system to protect customer accounts while maintaining operational efficiency.
Traditional fraud detection systems were generating too many false positives, leading to disrupted transactions, strained customer relationships, and inefficient manual reviews. Core challenges included:
- High rate of false positives causing unnecessary alerts and customer dissatisfaction
- Delayed fraud detection with limited real-time capabilities
- Difficulty meeting compliance requirements due to manual monitoring processes
Codvo.ai collaborated with the client to design a next-gen fraud detection and risk management system using AWS AI-powered models. The solution focused on improving accuracy, speed, and compliance through automation.
Implemented Solutions:
Real-Time Fraud Detection
- Anomaly Detection Models: Identified suspicious transactions using behavior-based ML models.
- Risk Scoring System: Assigned dynamic risk scores to transactions based on real-time data patterns.
- Real-Time Alerting: Enabled rapid fraud response with live notifications to security teams.
Compliance & Security Automation
- Regulatory Alignment: Integrated fraud detection workflows with compliance monitoring systems.
- Scalable Cloud Architecture: Deployed on AWS for seamless scalability, security, and performance.
The tech stack includes AWS AI/ML Services, Real-Time Anomaly Detection Models, Risk Scoring Algorithms, Cloud-Native Architecture
-40% Reduction in False Positives: Increased precision in fraud detection models.
-Faster Fraud Response: Real-time alerts accelerated fraud resolution.
-Improved Compliance Readiness: Automated tracking and anomaly logging supported audits.
-Smarter Risk Management: ML-powered scoring adapted to new fraud patterns.
-Reduced Manual Review Effort: Fewer false alerts meant streamlined investigation workflows.
