Turn Your Claims Data Into a Competitive Advantage

Policyholder names, policy numbers, SSNs, driver's license numbers, addresses, payment information, and beneficiary details. Health claims contain medical diagnoses, treatment histories, and prescription details. Auto claims include accident details and police reports. Property claims contain homeowner details and contractor information. Beyond standard identifiers, claims contain contextual details—employment information, family relationships, specific incident locations—that could identify individuals even without explicit account numbers. Photos and scanned documents may contain license plates, faces, and GPS metadata.

Yes. Fraud detection relies on patterns across claims, not individual identities. Suspicious patterns include similar damage descriptions across multiple claims, provider relationships suggesting collusion, and claim timing that indicates staged accidents. Pseudonymization preserves these relationships without storing real identities—you track multiple claims from the same provider, identify clusters of related claims, and detect fraud rings while protecting legitimate policyholders.

Insurance AI needs training data from millions of historical claims to learn fraud patterns, assess damage accurately, and automate routing decisions. De-identified claims preserve the patterns, relationships, and context AI needs without exposing policyholder identities. Train fraud detection on claim sequences and damage patterns. Build damage assessment models on historical repair costs. Turn regulated claims archives into AI training data that was previously too sensitive to use.

Insurance companies have decades of claims in scanned paper forms, legacy system exports, microfilm conversions, and outdated database backups. Limina processes these formats at scale—OCR extracts text from scanned and image-based documents, then entity detection runs across everything it finds. A major insurance company used Limina to map PCI exposure across 12-14 million legacy documents proactively, before a breach forced the issue.

No. Limina deploys as a container in your on-premises environment or VPC. All processing happens inside your existing security perimeter—no third-party cloud processing, no external transmission. This matters especially for insurance: claims documents, medical records, and policyholder data never flow to external services before they're protected.

Yes. Limina works across 52 languages with region-specific detection for insurance identifiers across North America, Europe, Asia, and Latin America. US Social Security numbers, Canadian health card numbers, Japanese My Number IDs, UK National Insurance numbers, and dozens of other locale-specific formats are all detected from a single deployment—alongside standard PHI and PCI.