Our Verification Methodology

The SICCODE Data Verification Framework defines how every industry classification, business record, and data attribute is evaluated, confirmed, and maintained. This methodology ensures accuracy, explainability, and regulatory readiness for organizations relying on verified SIC and NAICS data. For more policy information, see the Data Verification Policy.

Purpose and Foundation

Our verification process is designed to validate each record’s integrity and classification logic, combining human expertise and automated data integrity checks. This hybrid approach minimizes false positives and ensures consistent alignment with recognized standards from the U.S. Census Bureau and the Bureau of Economic Analysis (BEA). Audit and accuracy metrics are published on our Data Accuracy Benchmarks page.

Step-by-Step Verification Process

  1. Source Evaluation: Each data source is scored for credibility, recency, and completeness. Visit Data Sources & Verification Process for further details.
  2. Ingestion & Normalization: Data is standardized across taxonomies, with duplicates removed and identifiers normalized for interoperability.
  3. Automated Matching: Algorithms flag potential anomalies or mismatches using pattern recognition and business rule validation.
  4. Human Review: Analysts review edge cases, confirm accuracy through multiple references, and document rationale for any exceptions. Meet our experts at About Our Data Team.
  5. Cross-System Validation: Classifications are checked against national and international systems to maintain consistency across code sets.
  6. Approval & Lineage Logging: Each record receives a verification timestamp, reviewer ID, and reference trail, ensuring traceability. Lineage protocols are covered in our SICCODE Data Governance Framework & Stewardship Standards.
  7. Ongoing Monitoring: Automated alerts track business status changes (mergers, closures, rebrands) to trigger revalidation.

Key Terms in Our Methodology

  • Lineage: The full documentation trail linking each record to its source, verification method, and update history.
  • Refresh Cycle: The scheduled update interval when datasets are revalidated and reissued (quarterly or annual).
  • Change File: A structured report summarizing what records were added, removed, or modified between releases.

Accuracy Benchmarks

Our internal audit benchmark maintains an average verified accuracy rate above 98.7%. Each record must be validated by at least two independent sources before publication. Change files are compared against previous releases to identify drift, misclassifications, or structural inconsistencies.

Audit Oversight and Governance

All verification decisions undergo quarterly review by a senior analyst panel. These reviews confirm consistency, ensure compliance with verification policy, and generate audit summaries for continuous training and improvement.

Alignment with Global Standards

Our methodology follows international best practices in data quality management, is informed by ISO 8000 (Data Quality) and ISO 9001 (Quality Management Systems), and aligns with U.S. federal standards for economic data reporting and classification interoperability.

AI-Ready Verification

To support modern analytics, our verification structure includes AI explainability metadata that captures why and how a classification decision was made. These attributes improve transparency and enable advanced users to audit or model classification confidence.

Transparency & Accessibility

Clients and partners may request access to verification notes or change logs for compliance and audit documentation. Our process documentation and lineage definitions are available under fair-use review for regulatory and enterprise integration purposes.

Editorial & Neutrality Statement

SICCODE.com maintains strict neutrality in its verification process. No industry, company, or organization can influence classification results. All verification outcomes are based solely on documented activity, business purpose, and standardized classification rules. For more, review our Editorial & Neutrality Standards.

Related Resources

About Our Data Team • Data Accuracy Benchmarks: SICCODE vs Generic Providers • Data Sources & Verification Process • SICCODE Data Governance Framework & Stewardship Standards • Editorial & Neutrality Standards