Nationwide UCC Filing Data Extraction

A financial services client approached iWeb Data Scraping to aggregate Uniform Commercial Code (UCC) filings from all 50 US states and territories. While UCC data is public, each state maintains its own online system—with different search interfaces, formats, and update frequencies. The client aimed to collect structured data from every state’s UCC search portal, standardize it into a unified CSV format, and ensure the resulting dataset was complete, deduplicated, and ready for analysis.By building a state-by-state scraping framework, handling diverse formats, and respecting each portal’s access rules, we delivered a nationwide, consolidated UCC dataset that accelerated the client’s research and compliance operations.

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objectives

Objectives & Deliverables

Primary Objectives

  • Identify and access each state’s UCC filings portal.
  • Extract the latest available filing data, including:
    • Debtor name(s)
    • Secured party name(s)
    • Filing date
    • Filing number
    • Filing type (original, amendment, continuation, termination)
    • State/jurisdiction
    • Collateral description (when available)
  • Standardize outputs into a single CSV schema.
  • Deduplicate records across states and date ranges.
  • Provide a data dictionary and a refresh plan.

Challenges

  • No standardization: Each state portal has a different interface, fields, and formats (HTML tables, PDF documents, CSV exports, XML feeds).
  • Varied access rules: Some states allow bulk downloads, others only search-by-criteria.
  • Pagination and search limits: Many portals restrict result size per query.
  • Update frequencies: Some update daily, others weekly or monthly.
  • Data completeness: Not all states publish collateral descriptions online.
the-challenges
/Approach

Approach

Step 1: State-by-State Inventory

  • We mapped all 50 states + DC, noting:
  • Portal URL
  • Access rules
  • Available search parameters (name, date, filing number)
  • Download/export formats

Step 2: Source-Specific Scraping

  • Direct CSV/XML exports where available
  • HTML parsing for table-based results
  • PDF parsing with OCR for scanned documents
  • Form automation for states requiring search-by-date
  • Rate-limiting compliance to avoid service disruption

Step 3: Data Normalization

  • Standardized date formats to ISO 8601
  • Unified naming conventions for debtor/secured party
  • Standardized filing type codes across states
  • Tagged each record with state code for traceability

Step 4: Deduplication

  • Matched by Filing Number + State as primary key
  • Applied fuzzy matching for debtor/secured party names to catch duplicates from multi-jurisdiction filings

Step 5: QA and Verification

  • Randomly sampled filings from each state and compared against live portal records
  • Verified counts matched daily/weekly totals published by states that provide them

Tech Stack

  • Python (Requests, BeautifulSoup, Pandas) for HTML/XML/CSV parsing
  • Playwright/Selenium for interactive form handling
  • Tabula + Tesseract OCR for PDF extraction
  • PostgreSQL for staging and deduplication
  • Docker for environment consistency
  • AWS S3 for secure CSV delivery
Tech-Stack

Sample Data (Illustrative)

UCC Filings CSV

Filing Number State Filing Date Filing Type Debtor Name Secured Party Name Collateral Description
2025-IL-0001 IL 2025-08-05 Original John Smith Construction LLC First Midwest Bank All inventory, equipment, A/R
2025-CA-0098 CA 2025-08-03 Continuation Green Energy Solutions Inc. Bank of America Solar panels, installation tools
2025-TX-0452 TX 2025-08-01 Termination Blue Sky Farms LLC AgriBank, FCB Livestock, feed, and tractors
/Results

Results

  • Records collected: 1.5M filings across all states
  • Completeness: 100% debtor and secured party fields populated
  • Accuracy rate: 99.2% after QA sampling
  • Deduplication success: <1.5% residual duplicates
  • Delivery: CSV with unified headers, state tag, and data dictionary

Compliance

  • Accessed only publicly available UCC records per each state’s terms
  • Did not bypass paywalls or restricted areas
  • Rate-limited to avoid overloading state servers
  • Provided audit trail of source URLs for each state
Compliance
Client-Impact

Client Impact

Key Benefits

  • Research efficiency: Reduced manual search time from hours per state to <10 minutes for nationwide queries
  • Compliance readiness: Instant access to lien status for any debtor nationwide
  • Business intelligence: Ability to analyze collateral trends and market activity by industry and region

Conclusion

By building a robust, state-by-state scraping framework and standardizing highly fragmented UCC filing data, iWeb Data Scraping — a leading web scraping service provider USA — transformed a complex, manual process into a scalable, automated solution. The consolidated nationwide dataset not only delivered accuracy and completeness across 50 states and territories but also enabled the client to run faster compliance checks, streamline research, and gain actionable insights into lending and collateral trends. This project demonstrates how thoughtful data engineering and compliance-conscious scraping can unlock the full potential of public records for financial services and beyond.

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