Is it safe to share {X} with {Y}?

Sharing SWIFT codes with ChatGPT is strongly discouraged. Inputs entered into ChatGPT may be retained for up to 30 days and reviewed by OpenAI staff for safety and training purposes. Even if a SWIFT code alone does not trigger an immediate breach, its exposure within a conversation creates an uncontrolled record outside your organization's security perimeter.

Why this matters

ChatGPT is not an end-to-end encrypted environment, meaning any SWIFT code entered exists as retrievable data within OpenAI's systems during the retention window.
OpenAI's default data handling does not classify SWIFT codes as sensitive, so no automatic redaction or access restriction applies to them.
If an account is compromised or data is accessed through a third-party integration, SWIFT codes entered in prior sessions could be exposed.

For enterprise

Employees who enter SWIFT codes into ChatGPT through personal or unapproved accounts bypass institutional data governance controls entirely. Most corporate compliance frameworks, including those aligned with ISO 27001 or internal treasury policies, treat SWIFT identifiers as operationally sensitive and restrict their use outside authorized systems. Using ChatGPT as a workaround introduces audit gaps that may violate internal policy and, depending on jurisdiction, applicable regulatory requirements.

Compliances at risk

What counts as SWIFT Codes?

SWIFT/BIC codes
Bank Identifier Codes (BIC)
International bank routing identifiers
Financial institution SWIFT codes
Cross-border payment identifiers

Why people share SWIFT Codes with ChatGPT

To prepare international wire transfers
To identify receiving banks
To verify banking information
To complete cross-border payments

What actually happens when you paste SWIFT Codes into ChatGPT

When you paste SWIFT Codes into ChatGPT, that data is transmitted from your device to external servers operated by the AI provider.

Depending on system configuration and policies, the data may be logged, temporarily stored, or reviewed for safety and quality purposes. Retention can last from days to weeks, and in some cases may extend beyond the immediate session.

Statements such as “we do not train on your data” do not eliminate risks related to retention, logging, or internal access. These controls vary by product and setting, and are not always visible to end users.

From a governance perspective, any non-zero retention window introduces exposure risk when sensitive data is shared without controls, auditability, or enforcement.

Risks of sharing SWIFT Codes with ChatGPT

Unauthorized transactions: Card or bank details can be used for fraudulent payments.
Fraud escalation: Transaction data can help bypass fraud detection systems.
Credential abuse: Payment credentials can be reused across platforms.

Real incidents

Redis bug exposing chat and payment data : A vulnerability exposed chat histories and partial payment information across users.
Credential theft via infostealer malware : Over 100,000 ChatGPT credentials were stolen from infected devices.
Training data extraction : Researchers extracted memorized financial and personal information.

Is this allowed under policy or law?

Context	Is it safe?
Personal experimentation	No
Business use	No
Regulated industry	Definitely not
With redaction	Rarely

Safer ways to handle SWIFT Codes

SWIFT Codes should not be shared with consumer AI tools without controls in place. If AI assistance is required, organizations should use systems that enforce data redaction, access controls, and policy enforcement before data leaves their environment.

Automatically redact sensitive fields before sending data to AI models
Prevent unauthorized data from being entered into external tools
Maintain audit logs and visibility into how data is used
Ensure compliance with frameworks like GDPR, CCPA, and SOC 2

Platforms like Wald are designed to enable safe AI usage by ensuring sensitive data never leaves your control unprotected.

How Wald.ai handles this safely

Wald adds a governance layer to AI usage, helping organizations monitor and control how sensitive data like SWIFT Codes is shared.

AI DLP

Identifies SWIFT Codes in context and enables teams to:

Observe AI usage
Detect sensitive data in prompts
Allow, warn, or block actions
Maintain audit logs

LLM Pack

Provides controlled access to multiple AI models (ChatGPT, Claude, Grok, and others) through a single governed environment.

Centralized model access
Policy enforcement
Usage visibility
Auditability

Frequently Asked Questions

Is it safe to share SWIFT Codes with ChatGPT?

In most cases, no. Sharing SWIFT Codes with ChatGPT introduces unnecessary exposure risk and is generally discouraged unless strong governance controls are in place.

What happens when SWIFT Codes is entered into ChatGPT?

The data is transmitted to the AI provider's infrastructure for processing. Depending on the service and configuration, it may be temporarily stored, logged, or retained for security and operational purposes.

Can ChatGPT retain SWIFT Codes after a conversation ends?

ChatGPT providers may temporarily retain prompts and responses for security, abuse monitoring, or operational purposes. Depending on the platform and settings, SWIFT Codes may remain stored beyond the immediate session. In some cases, submitted data may be retained for up to 30 days before deletion. Organizations should assume that any sensitive information shared with AI systems could persist beyond the active conversation.

Does ChatGPT train on SWIFT Codes?

Some AI providers allow organizations to disable training on submitted data, while others may use interactions to improve services. Even when training is disabled, SWIFT Codes may still be processed, logged, or retained according to provider policies.

What happens if SWIFT Codes is accidentally shared with ChatGPT?

Once submitted, organizations may have limited visibility into how the information is retained, processed, or accessed. The appropriate response depends on the sensitivity of the data, internal policies, and incident response procedures.

Why do traditional DLP solutions struggle to identify SWIFT Codes in AI prompts?

Traditional DLP tools rely heavily on pattern matching and predefined rules. AI prompts often contain fragmented, transformed, or contextual information that can be difficult to classify accurately. Context-aware AI DLP solutions can evaluate surrounding context to better distinguish between similar data types and reduce false positives and false negatives.

Secure Your Employee Conversations with AI Assistants

Book A Demo