Enable financial AI workflows—without exposing customer data

Financial services teams are already using AI for compliance documentation, customer communications, and analysis. GPT-Shield adds a local, real-time protection layer that detects and redacts sensitive financial information before it reaches AI tools—maintaining regulatory compliance across browsers and supported desktop applications.

Regulatory-aligned protection
Real-time redaction
Local-first processing
Financial data protection
Before GPT-Shield

"Customer John Doe (SSN 123-45-6789, Acct #847392) wire transfer $285K..."

GPT-Shield Protection Layer

Detects PII & financial data • Redacts identifiers • Enforces compliance

After GPT-Shield

"Customer [REDACTED] (SSN [REDACTED], Acct #[REDACTED]) wire transfer [REDACTED]..."

Financial services AI risk is happening at every level

Financial institutions didn't deploy AI through controlled IT initiatives. It arrived the same way consumer technology arrived: individuals discovering tools that make complex work faster and easier.

Under regulatory and competitive pressure, teams use AI to:

None of these activities are inherently risky. The exposure occurs in a single moment: when customer data or sensitive financial information is pasted into a prompt.

This is the practical reality of Shadow AI in financial services: productivity-driven usage, outside compliance frameworks, where one prompt can expose regulated customer data.

If your institution relies on policy and training alone, you're betting on perfect compliance from hundreds or thousands of employees under constant pressure.

This is happening now:

Draft compliance reports and regulatory filings

Regulatory efficiency

Generate customer communications and updates

Relationship management

Summarize credit analysis and underwriting

Lending operations

Analyze fraud patterns and investigation details

Risk management

Why traditional controls fail for financial AI

Most data protection was built for core systems and structured databases. AI introduces a different exposure surface: the unstructured prompt.

Legacy Controls

  • Policies don't scale

    Cannot enforce compliance at the individual prompt level

  • Blocking creates Shadow AI

    Users move to personal accounts and unmanaged devices

  • Network DLP misses prompts

    Cannot reliably see unstructured AI interactions

  • Incident response is reactive

    Discovers exposure after regulatory damage occurs

Prompt-Level Control

  • Prevention before submission

    Detects and redacts customer data in real time

  • Enable compliant AI adoption

    Support productivity without regulatory risk

  • Financial data-aware detection

    Understands banking workflows and regulated information

  • Automatic enforcement

    Policy applied without relying on individual judgment

Financial services needs prevention at the moment of entry.

What GPT-Shield does (and why it's different)

GPT-Shield is built for the point of failure: when customer financial data is about to leave the device.

Local-first, real-time protection

GPT-Shield uses hybrid ML + NLP detection to identify financial data and redact it in real time before submission.

Works across platforms

Protects AI usage across browsers and supported desktop applications with consistent regulatory-aligned enforcement.

Compliance-driven enforcement

Instead of relying on individual compliance, GPT-Shield automatically enforces policies at the prompt level.

Financial workflow coaching

Provides contextual guidance for financial professionals and includes compliance training modules.

How it works

1

User begins typing or pastes content into an AI prompt

2

GPT-Shield detects customer PII, account numbers, and financial data

3

GPT-Shield redacts in real time before the prompt can be submitted

4

Coaching guidance appears when needed, reinforcing compliant AI usage

5

Analytics and training support institution-wide compliance improvement

This is not surveillance. It's preventive compliance control.

Common financial workflows

Real examples of how GPT-Shield protects financial AI workflows

Financial data at risk in AI prompts

Financial AI exposure goes beyond account numbers—it includes customer PII, proprietary analysis, and regulatory data.

Customer financial information

Account numbers and balances, transaction histories and patterns, credit scores and reports, investment holdings and performance, loan amounts and terms.

Personal identifying information

Customer names and contact details, Social Security numbers and tax IDs, dates of birth and addresses, employment and income information, family relationships and beneficiaries.

Proprietary analysis and strategy

Internal risk ratings and models, credit decision rationales, pricing and margin analysis, market intelligence and forecasts, merger or partnership discussions.

Regulatory and compliance data

SAR filings and AML investigations, audit findings and remediation plans, regulatory examination details, control frameworks and testing results.

Training & live coaching

Build compliance maturity with contextual guidance for financial teams

Live coaching for financial teams

When GPT-Shield detects customer data, it provides guidance:

⚠️

GPT-Shield detected customer information

Account details and PII were automatically redacted

💡 Compliant alternative:

"Draft a client update summarizing portfolio performance for the quarter, focusing on asset allocation changes and market impact without including specific account details."

Compliance training modules

GPT-Shield includes role-based training:

  • Regulatory fundamentals and AI risk
  • Safe prompting for financial workflows
  • Customer data protection best practices
  • Compliance requirements by role
  • Building AI-aware culture

Security & privacy by design

GPT-Shield's architecture ensures customer data never leaves your institution's control

Local-first processing

All detection and redaction happens on-device. Customer data is never sent to GPT-Shield servers.

Zero data retention

GPT-Shield does not log, store, or transmit prompt content. Financial information stays on the device.

Encrypted policy sync

Policy configurations sync securely. No customer data or prompt content is included.

Privacy-preserving analytics

Aggregate metrics support compliance improvement without exposing individual prompts or customer information.

Frequently asked questions

Financial Data Protection

Ready to Secure Financial AI While Maintaining Compliance?

Join financial institutions protecting customer PII, account data, and transaction details while leveraging AI for analysis, reporting, and customer service. Meet regulatory requirements while gaining competitive advantage.

View Pricing Plans

Scalable plans for banks, credit unions, wealth management, and fintech. Start protected risk-free.

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Protect your privacy while using AI chatbots. Real-time detection, smart coaching, and browser-based security. Supporting your organization's compliance efforts across HIPAA, GDPR, GLBA, and other regulatory frameworks.

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