4. Fraud Detection and Prevention

Real-time Monitoring:

• AI-Powered Analytics: Employs AI and machine learning models for real-time monitoring and anomaly detection.
• Behavioral Biometrics: Analyzes user behavior patterns for additional layers of security, detecting deviations from normal behavior.

Rules and Alerts:

• Rule-Based Engine: Utilizes a rule-based engine to define customizable fraud detection rules.
• Alert Management: Implements alert management systems to send notifications via SMS, email, or push notifications upon detecting suspicious activity.

Authentication:

• EMV 3-D Secure: Incorporates EMV 3-D Secure (3DS) for secure online transactions, adding an extra layer of authentication.
• Tokenization: Replaces sensitive card data with unique tokens during transactions to minimize exposure.