FINANCIAL SERVICES

Your Customer Data Is an Asset. Treat It Like One.

Remove PII and PCI from records, transcripts, and communications so your analytics, fraud, and AI teams can work with real customer data—compliantly, accurately, and entirely within your infrastructure.

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Built for

HOW IT WORKS

From Compliance Liability to Competitive Advantage

Three steps to compliant, usable financial data—whether you're building fraud models, responding to a breach, or sending call transcripts to analytics platforms.

Detect PII and PCI Wherever They Hide

Find credit cards, bank accounts, SSNs, tax IDs, and customer identifiers across loan files, call transcripts, emails, chat logs, claims documents, and legacy archives—structured and unstructured, in real time or batch.

Remove What Shouldn't Be There

Redact, pseudonymize, or tokenize sensitive data while keeping the context fraud detection, analytics, and AI actually need. Transcripts retain conversation flow. Emails keep complaint patterns. Loan files preserve detail.

Prove Your Compliance Holds Up

Audit trails document exactly what was detected and removed. Feed structured output into your data governance tools. Satisfy PCI DSS auditors, regulators, and breach notification requirements with documentation that shows comprehensive coverage.

Built for the Complexity of Real Financial Data

Decades of loan files, call transcripts mixing payment data with fraud indicators, multilingual customer communications, legacy archives never built for AI, and breach investigations where traditional DLP tools miss years of unclassified data.

Detect Payment Data the Way Customers Say It

Catch credit cards split across sentences, corrected mid-reading, or referencing on the last four digits. Detect PCI data in context, not just full card numbers. Banks that tested competitors found 15-30% of actual PCI data went undetected. Limina consistently hits compliance-grade accuracy on real banking data.

Real-Time Redaction for Contact Centers

Remove payment data from call transcripts as they stream from your speech-to-text engine. Redacted transcripts fall outside PCI DSS scope, so you can store calls for quality assurance, fraud pattern analysis, and agent training without bringing your entire contact center into compliance scope. Many of the major call center software providers run Limina in production today.

Handle Breaches and Legacy Archives at Scale

Traditional DLP tools can't read handwritten credit cards on scanned invoices or detect PII in image files. Limina processes scanned documents, images, PDFs with mixed content, and handwritten forms that regex-based tools miss entirely.

Enable AI on Communications and Claims Data

De-identify customer emails, chat logs, and claims documents so AI teams can build fraud detection models, train customer service AI, and run analytics on real data without exposing customer identities.

Enable Real-World Evidence Studies

De-identification preserves the statistical properties RWE research needs. Major CROs use Limina to prepare large-scale real-world patient data for ML analytics and comparative effectiveness research, with expert determination reports that prove de-identification meets HIPAA standards for research use.

CUSTOMER WIN

Major Financial Institution

$500M+

AI investment protected by an enterprise-wide privacy layer

Billions

Monthly API calls processing customer documents and communications

Millions

Legacy documents de-identified for PCI compliance

Data Scientists Needed the Data. Compliance Said No.

Data scientists needed transaction and account data to build better fraud models, but PII and PCI made sharing unsafe, forcing a choice between compliance and innovation. Every request required manual review. Every delay meant models running on stale data.

Limina Became the Firewall

Limina now sits between operations and data science, automatically de-identifying data before it's shared. Transcripts retain context, emails keep complaint patterns, and loan files preserve detail—while credit cards and personal identifiers are safely redacted within the institution's own infrastructure. Data scientists access real customer data safely. Compliance stays intact.

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Ready to Put Your Customer Data to Work?

Talk to our team about your use case. Most customers are up and running in days, not months.

Frequently Asked Questions

How does Limina handle PCI compliance differently than general tools?

General-purpose tools treat credit card numbers like any other digit string. Limina applies Luhn validation to distinguish real payment credentials from employee IDs, reference numbers, and random digits that happen to match card patterns. We also catch contextual PCI—"card ending in 4532" or "my Visa"—that generic tools miss. Banks testing competitors found 15-30% of actual PCI data went undetected. Limina consistently achieves compliance-grade accuracy on real banking data.

How does call transcript redaction affect PCI DSS scope?

PCI DSS applies to systems that store, process, or transmit cardholder data. Transcripts containing credit card numbers bring your call analytics platform, CRM, and data warehouse into PCI scope with extensive security requirements. Redacted transcripts containing no payment data fall outside scope entirely—you store calls for QA, fraud pattern analysis, and agent training without PCI audit obligations applying to those systems.

Can we use Limina for breach investigation and legacy data?

Yes. Traditional DLP solutions can't process scanned documents, handwritten forms, or image files—the unstructured formats where years of unclassified PII and PCI typically live. Limina handles these formats at scale, letting you map breach scope across compromised data, meet notification deadlines, and document comprehensive assessment to regulators. The same capability works proactively before incidents happen.

Can we use de-identified customer data to train AI models?

Yes. Banking communications, claims documents, and transaction records contain valuable training data for fraud detection, customer service AI, and analytics. De-identified outputs preserve the conversation flow, claim patterns, and behavioral signals AI needs without exposing customer identities. A major bank built an enterprise-wide AI initiative using Limina as the privacy layer across all data pipelines.

Does our data leave our environment?

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 financial services: customer account data, payment records, and communications never flow to external services before they're protected.

Does Limina support the languages and regions where we operate?

Yes. Limina works across 52 languages with region-specific detection for financial identifiers across North America, Europe, Asia, and Latin America. Canadian SINs, Japanese My Number IDs, UK National Insurance numbers, German tax IDs, European IBANs, and dozens of other locale-specific formats are all detected alongside standard PCI from a single deployment.