Cross-Program Fraud Detection - IBR-033

IBR ideally should implement APIs and advanced analytics capabilities to identify potential fraud or errors across multiple social protection programs, using real-time data exchange to prevent duplicate or fraudulent claims.

Enhances program integrity and prevents improper benefit allocation by leveraging both API integration and analytical tools.

Implement APIs and advanced analytics capabilities to identify potential fraud or errors across multiple social protection programs.

Beneficiary ID, Fraud Detection Data, Program Participation Data

• API: REST API for fraud data exchange.

• Analytics: Rule-based detection using Python scripts.

• Data Sharing: Batch processing for fraud alerts across programs.

• API: GraphQL for real-time fraud detection data sharing.

• Analytics: Machine Learning-based anomaly detection to identify potential fraud.

• Data Sharing: Real-time alerts using Apache Kafka.

• API: Federated GraphQL with real-time AI-driven fraud detection.

• Analytics: Deep Learning for pattern recognition across programs.

• Data Sharing: Streaming analytics with Apache Pulsar and AI-driven proactive alerts.

Secure fraud detection API, encryption for fraud data sharing.

Machine learning-based fraud detection for scalability.

Integration with multiple program data sources for fraud detection.

Compliance with GDPR for fraud detection data sharing.

N/A