Duplicate Prevention System - IBR-016

IBR must use the Identity Verification Service to prevent duplicate beneficiary records

Essential for maintaining data integrity and preventing benefit duplication

Use the Identity Verification Service to prevent duplicate beneficiary records.

Beneficiary ID, Identity Verification Data, Duplicate Prevention Metrics

• The system must prevent the creation of duplicate beneficiary records based on configurable unique identifiers (e.g., a system-generated ID, National ID, or a combination of fields)."

• "The system must check for potential duplicates during data entry and updates."

• "The system must provide a mechanism for administrators to review and resolve potential duplicate records."

• Database Indexing: Implement unique indexing on key beneficiary identifiers within the database to enforce uniqueness and prevent the creation of exact duplicate records on those identifiers.

• Logging: Implement basic logging of duplicate detection activities, including when potential duplicates are flagged and the actions taken (e.g., flagging for review, preventing record creation).

• Identity Verification: Integrate with an external Identity Verification Service (or open-source ID matching tool) via interfaces to enhance identity verification accuracy and reliability beyond basic internal checks. Implement fuzzy matching algorithms to detect potential duplicates even with minor data variations.

• Database Indexing: Utilize UUIDs (Universally Unique Identifiers) for primary keys and implement unique constraints across a combination of key identifying fields (e.g., name, date of birth, address) to ensure data consistency and prevent duplicates based on multiple criteria.

• Logging: Implement integration with SIEM (Security Information and Event Management) systems for enhanced anomaly detection related to duplicate records and more comprehensive audit trails of deduplication processes.

• Identity Verification: Implement multi-modal biometric verification (e.g., face, fingerprint) integrated with a sophisticated Identity Verification Service to achieve highly accurate and reliable deduplication, especially in contexts with limited text-based identity data availability.

• Database Indexing: Utilize graph-based indexing and relationship detection within the database to identify potential duplicates based on complex relationships and network analysis, beyond simple attribute matching.

• Logging: Implement AI-driven duplicate detection and proactive resolution, with the system automatically identifying, flagging, and potentially resolving duplicate entries based on machine learning models and anomaly detection, with comprehensive and auditable logging on a distributed ledger (blockchain) for tamper-proof records.

Implement appropriate security measures for identity verification processes and biometric data handling (if applicable), and ensure secure logging of deduplication activities.

Utilize UUIDs and unique constraints for managing duplicates at scale. Consider distributed database solutions and optimized matching algorithms for handling large beneficiary populations.

For "Standard" and "Advanced" levels, ensure REST API integration as an example interface for interacting with external Identity Verification Services and exchanging deduplication status information with other DSPDS components.

Compliance with GDPR and ISO 27001 for identity verification and data handling, particularly when using biometric data.

N/A (While not explicitly UI-focused, a user interface for manual review and resolution of potential duplicates flagged by the system would be a highly desirable feature in a real-world implementation, even if not explicitly stated as a core functional requirement here).