Financial Services / Security7 weeks
Behavioral Biometrics for Continuous Authentication
Client: Global Trust Bank
Continuous, invisible security layer based on user interaction patterns to prevent account takeover.
The Challenge
Global Trust Bank needed to combat account takeover fraud by moving beyond single-point authentication to create a continuous, invisible security layer based on user behavior. The challenge was to detect fraudulent activity without adding friction for legitimate users.
Key Challenges:
- Combat account takeover fraud effectively
- Move beyond single-point authentication limitations
- Create continuous security monitoring without user friction
- Detect anomalous behavior patterns in real-time
Without continuous authentication, the bank faced high risk of account takeover fraud, financial losses, and potential regulatory compliance issues.
Our Solution
- Deep learning models analyzing micro-patterns in user interaction
- Behavioral fingerprint creation based on typing rhythm, mouse movements, and swipe gestures
- Real-time anomaly detection flagging suspicious sessions
- Continuous authentication without interrupting user experience
- Machine learning models learning from user behavior patterns
- Integration with existing banking systems for seamless security
Technology Stack
PyTorchTensorFlowIsolation ForestAutoencodersKafkaReal-time APIs
Client Testimonial
"Dropped account takeover fraud by over 90% with zero additional friction."
— CISO, Global Trust Bank