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What is Automated Document Verification?
Raapyd’s automated document validates submitted documents through controlled extraction, logical checks, and name matching to support onboarding, verification, and compliance decisions across regulated processes.
API-Based Validation
A REST API receives documents and metadata, applies predefined validation rules, and returns structured results for downstream onboarding or verification systems.
Rule-Driven Decisions
Each submission is evaluated based on document type, field availability, data quality, and validation logic to determine approval, review routing, or rejection.
Name Matching Logic
Fuzzy and NLP-based matching compares form data, document content, and master records to assess consistency and generate confidence scores.
How the Document Verification Works
The software processes uploaded documents through validation, extraction, matching, and verdict generation stages before returning structured outputs.
Document Verification with Measurable Outcomes
65%
Faster onboarding turnaround by reducing rework from incomplete or invalid bank documents.
97%
Of standard documents processed automatically through predefined validation and matching rules.
100%
Of decisions logged with timestamps to support audit and compliance requirements.
65%
Faster onboarding turnaround by reducing rework from incomplete or invalid bank documents.
97%
Of standard documents processed automatically through predefined validation and matching rules.
100%
Of decisions logged with timestamps to support audit and compliance requirements.
Streamline document validation with Raapyd’s rules-driven engine that delivers clear verdicts, traceable decisions, and system-ready outputs.
Key Benefits of Raapyd Document Verification Automation
Automated validation and decision logic reduce manual checks while maintaining consistency across regulated workflows.
Deterministic Decisions
Predefined rules ensure consistent approval, routing, or rejection outcomes across all submitted documents.
Reduced Operational Load
Only documents with partial matches, quality issues, or rule conflicts are routed for operational review.
Improved Data Integrity
Mandatory field checks and logical validations reduce incomplete or inconsistent records.
Faster Verification Cycles
Early-stage validation prevents delays caused by rework, clarification requests, or repeated submissions.
Audit-Ready Outputs
All decisions, match scores, and validation results are logged with timestamps and transaction identifiers.
System-Friendly Integration
Structured engine responses integrate cleanly with onboarding, compliance, and case management platforms.
Frequently asked questions
What document types are supported? +
The engine supports identity documents, employment records, registration forms, and official statements based on configured document rules. Unsupported types are rejected automatically.
How are name mismatches handled? +
Name comparisons generate match percentages and classifications. Partial matches or special cases are routed for operational review.
Does the engine perform AML or background checks? +
No. The engine focuses on document validation, extraction, and matching. Screening and background checks are handled by downstream systems.
How are low-quality documents treated? +
Documents with low clarity, suspected screenshots, or layout anomalies are rejected or routed based on rule outcomes.
Is audit logging supported? +
Yes. The engine logs extraction results, validation outcomes, routing reasons, timestamps, and transaction identifiers.
AI-Driven Document Verification
Standardize document validation and name matching through Raapyd’s rule-based engine built for onboarding and verification workflows.