Your claims management platform has no native anonymize-and-export feature. Your offshore BPO team needs complete claim details to process. Your reinsurer needs the full accident narrative to assess risk. Black boxes make both impossible. Text anonymization gives every recipient a readable, complete claim file with synthetic claimant identities.
Vehicle collision on I-10 westbound, injuries to left shoulder.
Document anonymization sits at the intersection of every claims sharing workflow. These are the four failure modes that block reinsurance submissions, break RPA bots, and prevent offshore BPO teams from doing their jobs.
Guidewire ClaimCenter, Duck Creek Claims, CCC Intelligent Solutions, Insurity ClaimsXPress, Majesco Claims: none have a built-in anonymize-and-export feature. Adjusters download the PDF, open their PDF tool, draw boxes one at a time, re-upload. Every claim. Every time. Claims platform marketplaces offer many integrations, but purpose-built batch anonymization with synthetic replacement remains a gap that leaves insurers relying on manual processes or custom-built pipelines.
Insurance companies built RPA bots to process claims. The bots read document text. When documents arrive with black boxes, the bot cannot read redacted fields and throws an exception. Black-box redactions cause a material increase in RPA automation failures. Some analyses indicate up to 1 in 5 documents requires costly manual intervention. You redact for compliance and break your own automation. The black box that satisfied the privacy requirement is the same black box that crashes the workflow that was supposed to replace manual review.
Database masking tools mask SQL columns. They cannot open a 30-page PDF claim file with embedded police reports, medical records, and adjuster notes. Completely different problem. The enterprise data governance stack was built for structured data. Unstructured claims documents are outside its scope entirely. These are the ones that actually move between insurers, reinsurers, and BPO vendors.
Insurers outsource claims processing to BPO teams in India, the Philippines, and Eastern Europe. Those teams need to read the documents. Send them claim files full of black rectangles and they cannot process them. The claim narrative is broken, key fields are missing, and the processor has to escalate for manual review. Text anonymization gives them complete, readable documents with claimant PII already replaced.
Re-Doc sits between your claims management system and every downstream recipient. One API call returns a complete, readable claim file with claimant PII replaced.
Export from any claims management system. PDF, DOCX, or scanned attachments. Any format your claims workflows produce.
Every identifier found: claimant name, policy number, SSN, address, phone, medical provider, date of birth. Visual processing handles scanned police reports and accident photos.
Claimant PII replaced with consistent synthetic data. Claim narrative preserved. "Vehicle collision on I-10 westbound" stays. Policy numbers, SSNs, addresses get plausible replacements.
Send to reinsurer, offshore BPO team, state DOI regulator, or feed into the RPA bot. Everyone gets a complete, readable document. No black boxes.
A single claim packet can include a native PDF from your claims system, a scanned police report, a handwritten medical bill, and a DOCX adjuster narrative. Re-Doc handles all of them.
Black boxes over PII. Source pixel data permanently destroyed.
For scanned attachments where the source document cannot be edited. Visual processing reads images at pixel level. A context-aware model identifies every claimant identifier in context. Black boxes drawn precisely over the detected regions. The original pixel data is destroyed, not covered.
Synthetic data swap. Document stays complete and readable.
For native digital claim files exported from your claims management system. Claimant PII replaced with consistent, realistic synthetic identifiers. David Alan Martinez becomes James Robert Anderson on every page of every document in the batch. Reinsurers, BPO teams, and regulators receive a complete, readable file.
The claim narrative is preserved. The claimant is gone. The reinsurer can underwrite it. The BPO team can process it. The RPA bot can parse it.
Claimant: David Alan Martinez
Policy: POL-8843-2024
SSN: 489-22-7731
Address: 5612 Elm St Phoenix AZ 85004
Provider: Banner Health Phoenix
Vehicle collision on I-10 westbound, injuries to left shoulder. Claim filed 11/04/2024.
Claimant: James Robert Anderson
Policy: POL-3317-2024
SSN: 621-45-8894
Address: 2249 Maple Ave Tucson AZ 85701
Provider: Tucson Medical Center
Vehicle collision on I-10 westbound, injuries to left shoulder. Claim filed 11/04/2024.
Claim facts preserved: incident description, date, claim type. All claimant PII replaced with consistent synthetic data.
Each of these workflows is currently handled by manual review, custom-built pipelines, or simply left unsolved. These are the actual bottlenecks in large carriers and reinsurers right now.
Reinsurers need full claim details to price treaties: the facts of the incident, the injuries or damages, the amount paid. They do not need the claimant's name, address, and SSN. Text anonymization lets you send the complete claim narrative. Every material fact intact. Claimant PII replaced. For carriers with high-volume auto and property programs running 500+ submissions a month, the API processes the entire batch overnight.
State departments of insurance conduct market conduct examinations requiring carriers to produce claim samples. The NAIC Insurance Data Security Model Law (MDL-668) has been enacted in 28 jurisdictions as of 2025. Regulators reviewing claim samples need to verify the claims-handling process, not identify the claimants. Text anonymization removes claimant PII before the files leave your systems, while preserving the claim facts the examiner actually needs to review. Note: regulators retain authority to demand original, unredacted files under formal legal process.
Cross-border transfer of personal data under GDPR Article 9 requires appropriate safeguards. India's DPDP Act imposes similar restrictions on data transfers. When US insurers send claim files to BPO teams in Bangalore or Manila, every file is a potential compliance consideration. When effective anonymization is applied before transfer, the data may fall outside the scope of personal data regulations, significantly reducing compliance risk. The BPO team receives a complete, readable document with plausible synthetic identifiers. No black boxes that prevent processing.
Most tools in insurance process documents manually or apply cosmetic redaction that leaves underlying data intact. Re-Doc was built specifically for unstructured claim file workflows.
Typical tools
in the market
Re-Doc
Purpose-built for claims
Cosmetic redaction. Text layer survives copy-paste and downstream extraction.
True text removal. PII gone from the file, not just visually covered.
Manual, per-file process. Unusable for high-volume claims operations.
Batch API processes thousands of claim files in a single submission.
Cannot handle scanned claim documents and fax-originated records.
Visual processing pipeline handles scanned PDFs, fax images, and image-based attachments.
Text anonymization unavailable. Shared files must be redacted, not replaced.
Text anonymization preserves document structure for reinsurer and BPO sharing.
No API access. Every file must be processed manually one at a time.
REST API and batch upload for automated, high-volume processing workflows.
of medical claim attachments processed electronically when this gap began
71% of medical claim attachments are still processed manually (CAQH 2023). Black-box redactions cause a material increase in RPA exceptions. Up to 1 in 5 documents may require costly manual intervention when bots hit redacted fields. Text anonymization breaks this cycle. Every field is readable. The bot processes normally.
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