Safeguards for Non-Public Personal Information across financial AI workflows.
KorGuard detects regulated financial data inside AI prompts, emails, and document uploads used by banks, credit unions, lenders, wealth managers, and fintech operations teams.
Generative AI accelerates work in financial services, but it also creates a new disclosure surface for NPPI. KorGuard enforces the GLBA Safeguards Rule at the point of input with local detection, contextual escalation, and configurable policy.
NPPI Coverage
Full
SSN, account, routing, card, loan, credit, KYC, and beneficial-ownership signals.
Processing
On-Device
Detection runs locally. No prompt content reaches KorGuard infrastructure.
Policy Model
Tiered
Per-business-unit thresholds, role-based exceptions, and segregated audit telemetry.
The NPPI Exposure Surface
Customer financial data is leaking into AI tools faster than Safeguards programs can adapt.
Industry telemetry · 2024–2026
$19M
Average finance AI breach
Financial services sits second only to healthcare in per-incident AI breach cost — and rising as generative tools spread across front and back office.
93%
Use unsanctioned AI
Analysts, advisors, and operations staff routinely paste customer data into consumer LLM accounts that fall entirely outside Safeguards scope.
48%
Submit NPPI to LLMs
Nearly half of financial-services employees admit to entering account numbers, balances, KYC fragments, or denial reasoning into AI assistants.
30 days
GLBA breach notice trigger
FTC Safeguards Rule amendments require notification of qualifying events — generative AI exfiltration is now squarely in scope.
0
Examiner tolerance
Regulators have signaled that uncontrolled generative AI use is an examination finding, not a future risk.
$2.3T
Compliance spend annually
Global financial services compliance budgets keep growing — yet the prompt-layer surface remains largely uninstrumented.
Capabilities
Detection, scoring, and enforcement at the point of input.
Financial Identifier Detection
Recognizes Social Security numbers, account and routing numbers, card PANs, loan and credit identifiers, and KYC document fragments.
Contextual Escalation
Escalates risk when financial identifiers appear alongside customer names, balances, denial reasons, or fraud-investigation language.
Policy Enforcement
Configurable blocking, warning, or redaction aligned to internal Safeguards Rule controls and business-unit risk appetite.
Document Intake Protection
Locally analyzes uploaded statements, applications, and disclosures, returning a de-identified version safe for AI processing.
Audit Without Exposure
Compliance teams receive risk metadata, severity, and destination, never the underlying NPPI.
Workforce Coaching
Real-time prompts that teach analysts what counts as NPPI in the moment, reducing repeat exposures.
99% NPPI detection accuracy. Zero data leaves your perimeter.
The KorGuard shield runs financial-classifier inference inside the browser. Account numbers, SSNs, KYC fragments, and contextual customer signals are detected and scored locally — nothing reaches KorGuard, nothing reaches a third-party model.
99%
NPPI Detection Accuracy
Benchmarked across SSN, account, routing, card PAN, loan, KYC, and contextual customer-relationship language.
0
NPPI Bytes Transmitted
All detection, scoring, and redaction occurs on-device. No prompt or attachment leaves the user's session.
<40ms
Decision Latency
The shield returns a verdict before the user can submit. Front-office workflow stays intact.
100%
Examiner-Ready Telemetry
Severity, identifier class, and destination are captured. Underlying customer content never is.
Workflow
What happens between keystroke and submit.
01 / Capture
Browser-resident intercept
KorGuard inspects the active input across AI platforms, web mail, and internal applications.
02 / Classify
Financial classifier
On-device model flags NPPI and contextual signals such as customer relationship language.
03 / Score
Severity model
Risk tiering accounts for identifier sensitivity and destination platform reputation.
04 / Enforce
Policy action
Block, warn, or substitute redacted content, aligned to your Safeguards program.
Outcomes
What changes for your team.
- Reduce GLBA Safeguards Rule exposure introduced by uncontrolled generative AI use.
- Prevent NPPI from entering consumer AI accounts, personal mailboxes, or unsanctioned tools.
- Maintain fiduciary trust by enforcing data minimization at the moment of risk.
- Equip second-line risk teams with usable telemetry without expanding sensitive-data surface.
- Demonstrate operational controls to examiners with concrete enforcement evidence.
Why KorGuard
Built differently from cloud DLP and prompt firewalls.
Safeguards-aligned, not generic DLP
Built around the FTC Safeguards Rule control set, with policy primitives that map cleanly to your written information security program.
Context-aware financial detection
Goes beyond pattern-matching SSNs. Catches identifiers correlated with customer names, balances, denial reasoning, and fraud-investigation language.
Local-first by architecture
Cloud DLP creates a new disclosure path for the very data it scans. KorGuard inspects on the device, so NPPI never leaves your perimeter to be 'protected'.
Bring GLBA controls into the prompt layer.
See how KorGuard enforces Safeguards Rule expectations across the AI tools your teams already use.
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