Learn how to comprehensively redact all bank account information including routing numbers, SWIFT/BIC codes, sort codes, and bank names. Protect complete banking data in payment instructions, wire transfers, and financial documents.
Complete bank account information encompasses multiple data elements that, when combined, enable financial transactions. This includes account numbers, routing numbers (ABA/ACH), SWIFT/BIC codes, sort codes, bank names, and branch identifiers.
Anonymization API provides unified detection and redaction for all banking identifiers with 99.4% accuracy. Our system understands the relationships between banking data elements and can detect complete wire transfer instructions, ACH payment details, and international banking information in various formats and languages.
Whether you're processing payment documents, vendor setup forms, direct deposit authorizations, or international wire instructions, our API ensures that all banking information is consistently identified and redacted.
Protecting this information comprehensively is essential, as even partial banking data can facilitate fraud when combined with other pieces.
We support both US domestic banking formats and international standards including IBAN, SWIFT, and regional identifiers from 80+ countries.
All banking data types in one pass
80+ countries and banking systems
Understands linked banking elements
Complete banking information represents the keys to financial accounts. Unlike credit cards with robust fraud protections, direct access to bank account details can enable immediate, unauthorized ACH debits, wire transfers, and other irreversible financial transactions.
High Risk: Routing number + account number = complete ACH access. Wire transfer fraud using compromised banking details is difficult to reverse and can result in total loss of funds. Comprehensive redaction of ALL banking elements is essential. The combination of routing and account numbers is particularly dangerous.
Banking information protection is mandated by numerous regulations:
Complete banking data includes multiple interconnected elements:
The unique identifier for the specific account (checking, savings, etc.)
9-digit codes identifying the financial institution for US domestic transfers
8-11 character codes for international bank identification
International Bank Account Numbers combining country, check digits, and account info
UK bank branch identifiers (6 digits)
Australian Bank-State-Branch numbers
Institution names when combined with other banking data
Branch addresses and identifiers
Important: Individual banking elements may seem harmless alone, but become highly sensitive when combined. Our API understands these relationships and can redact banking information comprehensively based on context.
Get started with comprehensive bank information redaction in just a few lines of code. This example shows how to detect and redact all banking elements from text.
from anonymization import Client client = Client(api_key="your_api_key") result = client.anonymize( text="Bank: Wells Fargo, Routing: 121000248, Account: 7890123456", entity_types=["BANK_INFO"] # Detects all banking elements ) print(result.anonymized_text) # Output: Bank: [BANK_NAME], Routing: [ROUTING_NUMBER], Account: [BANK_ACCOUNT]
const { AnonymizationClient } = require('@anonymization/api'); const client = new AnonymizationClient('your_api_key'); const result = await client.anonymize({ text: "Bank: Wells Fargo, Routing: 121000248, Account: 7890123456", entityTypes: ["BANK_INFO"] }); console.log(result.anonymizedText); // Output: Bank: [BANK_NAME], Routing: [ROUTING_NUMBER], Account: [BANK_ACCOUNT]
curl -X POST https://api.anonymizationapi.com/v2/anonymize \ -H "Authorization: Bearer your_api_key" \ -H "Content-Type: application/json" \ -d '{ "text": "Bank: Wells Fargo, Routing: 121000248, Account: 7890123456", "entity_types": ["BANK_INFO"] }'
The API response includes all detected banking elements with their types:
{
"anonymized_text": "Bank: [BANK_NAME], Routing: [ROUTING_NUMBER], Account: [BANK_ACCOUNT]",
"entities": [
{
"type": "BANK_NAME",
"text": "Wells Fargo",
"start": 6,
"end": 17,
"confidence": 0.98
},
{
"type": "ROUTING_NUMBER",
"text": "121000248",
"start": 28,
"end": 37,
"confidence": 0.99,
"metadata": {
"checksum_valid": true,
"bank_name": "Wells Fargo Bank, NA"
}
},
{
"type": "BANK_ACCOUNT",
"text": "7890123456",
"start": 48,
"end": 58,
"confidence": 0.97
}
]
}
Our API recognizes and categorizes different types of banking information for precise redaction.
US routing numbers are 9 digits with a built-in checksum:
International bank identifiers are 8 or 11 characters:
UK bank/branch identifiers are 6 digits, often formatted with dashes:
The API detects complete wire transfer instruction blocks:
# Detect all banking data types at once result = client.anonymize(text, entity_types=["BANK_INFO"]) # Or specify individual types for granular control result = client.anonymize(text, entity_types=[ "BANK_ACCOUNT", # Account numbers "ROUTING_NUMBER", # ABA routing numbers "SWIFT_BIC", # SWIFT/BIC codes "IBAN", # International IBANs "SORT_CODE", # UK sort codes "BSB", # Australian BSB "BANK_NAME" # Bank institution names ]) # Enable routing number validation result = client.anonymize( text=text, entity_types=["ROUTING_NUMBER"], options={"routing_validate": True} )
Choose the appropriate technique based on your security requirements and downstream data needs.
Completely replaces all banking elements with type-specific placeholders. Maximum security.
Replaces all banking elements with a single placeholder. Useful when you don't need to preserve structure.
Shows last few digits for verification while hiding sensitive parts.
Redacts account-specific data while keeping general bank identification.
Replaces with fake but valid-format banking data. Useful for testing systems.
# Full redaction with type-specific placeholders (default) result = client.anonymize(text, entity_types=["BANK_INFO"], mode="redact") # Unified redaction - single placeholder for all banking data result = client.anonymize(text, entity_types=["BANK_INFO"], mode="redact", options={"unified_placeholder": "BANK_INFORMATION"}) # Partial masking - show last 4 characters result = client.anonymize(text, entity_types=["BANK_INFO"], mode="mask", options={"show_last": 4}) # Keep bank names, redact numbers result = client.anonymize(text, entity_types=["BANK_ACCOUNT", "ROUTING_NUMBER", "SWIFT_BIC"]) # Bank names will be preserved # Format-preserving pseudonymization result = client.anonymize(text, entity_types=["BANK_INFO"], mode="pseudonymize", options={"valid_format": True})
Redact complete wire instruction documents:
wire_instructions = """ DOMESTIC WIRE INSTRUCTIONS -------------------------- Bank Name: JPMorgan Chase Bank, N.A. Bank Address: 270 Park Avenue, New York, NY 10017 ABA/Routing Number: 021000021 Account Number: 123456789012 Account Name: ACME Corporation Reference: Contract #2025-100 INTERNATIONAL WIRE (USD) ------------------------ SWIFT Code: CHASUS33 Bank Name: JPMorgan Chase Bank, N.A. Account Number: 123456789012 """ result = client.anonymize( text=wire_instructions, entity_types=["BANK_INFO", "ADDRESS", "ORGANIZATION"] ) print(result.anonymized_text)
Process multiple vendor banking records:
vendor_records = [
"Vendor A: Bank of America, ABA 011401533, Acct 1234567890",
"Vendor B: Wells Fargo, Routing 121000248, Account 0987654321",
"Vendor C: HSBC UK, Sort 40-05-30, Acct 12345678",
"Vendor D: Deutsche Bank, IBAN DE89370400440532013000"
]
results = client.batch_anonymize(
items=[{"text": record} for record in vendor_records],
entity_types=["BANK_INFO"]
)
for r in results:
print(r.anonymized_text)
Process employee direct deposit information:
direct_deposit_form = """ DIRECT DEPOSIT AUTHORIZATION Employee Name: John Smith Employee ID: EMP-12345 Bank Information: Bank Name: US Bank Routing Number: 091000019 Account Number: 1234567890 Account Type: Checking I authorize my employer to deposit my pay directly to the above account. Signature: John Smith Date: January 15, 2025 """ result = client.anonymize( text=direct_deposit_form, entity_types=[ "PERSON", "BANK_INFO", "DATE" ] ) print(result.anonymized_text)
Scan documents for any banking information:
def audit_for_banking_data(document_text, document_id): """Scan document for any banking information""" result = client.detect( text=document_text, entity_types=["BANK_INFO"] ) if result.entities: print(f"ALERT: Document {document_id} contains banking data:") for entity in result.entities: print(f" - {entity.type}: '{entity.text[:20]}...' at position {entity.start}") # Return redacted version redacted = client.anonymize( text=document_text, entity_types=["BANK_INFO"] ) return redacted.anonymized_text return document_text # No banking data found
Always use the umbrella BANK_INFO type to catch all banking elements:
# Recommended: Use BANK_INFO for comprehensive coverage result = client.anonymize( text=text, entity_types=["BANK_INFO"] # Catches all banking data types ) # BANK_INFO includes: # - BANK_ACCOUNT # - ROUTING_NUMBER # - SWIFT_BIC # - IBAN # - SORT_CODE # - BSB # - BANK_NAME (in banking contexts)
Enable checksum validation to reduce false positives:
# Enable all available validations result = client.anonymize( text=text, entity_types=["BANK_INFO"], options={ "routing_validate": True, # ABA checksum "iban_validate": True, # IBAN checksum "swift_validate": True # SWIFT format } )
Specify expected countries for better detection of regional formats:
# For international documents, specify expected countries result = client.anonymize( text=international_doc, entity_types=["BANK_INFO"], options={ "bank_countries": ["US", "GB", "DE", "FR"] } )
Banking data often appears with names and addresses - redact together:
# Comprehensive financial document redaction result = client.anonymize( text=financial_doc, entity_types=[ "BANK_INFO", # All banking data "PERSON", # Account holder names "ORGANIZATION", # Company names "ADDRESS", # Bank/account holder addresses "SSN", # Tax IDs that may appear "PHONE" # Contact numbers ] )
Defense in depth for banking data protection:
Security Note: Banking information should never be displayed in full in any user interface, log file, or report. Always apply masking showing at most the last 4 characters for verification purposes.
BANK_INFO is an umbrella entity type that detects all banking-related information in one pass. Using individual types (BANK_ACCOUNT, ROUTING_NUMBER, etc.) gives you granular control over what to redact, but BANK_INFO is recommended for comprehensive protection.
Bank names are detected with 97% accuracy when they appear in banking contexts (near account numbers, routing numbers, or wire instructions). Standalone mentions of bank names may have lower confidence as they could be references rather than account information.
The API processes text. For checks, bank statements, or scanned documents, use OCR first to extract text. We can recommend OCR partners. The MICR line on checks has a specific format that our API recognizes after OCR extraction.
The API supports banking terminology in multiple languages. Common terms like "IBAN", "SWIFT", "compte bancaire" (French), "Kontonummer" (German) are recognized. Specify the language for better accuracy: options={"language": "de"}.
Cryptocurrency addresses (Bitcoin, Ethereum, etc.) are handled by a separate entity type: CRYPTO_ADDRESS. Add this to your entity_types array to detect and redact crypto wallets alongside traditional banking information.
Enable routing validation with options={"routing_validate": True}. The API validates the ABA checksum and can optionally verify against the Federal Reserve routing directory. Invalid routing numbers are flagged with lower confidence.
Yes, simply exclude BANK_NAME from your entity_types: entity_types=["BANK_ACCOUNT", "ROUTING_NUMBER", "SWIFT_BIC"]. Bank names will remain while other banking data is redacted.
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Read the guideProtect complete banking data with comprehensive detection. Support for routing numbers, SWIFT codes, and 80+ countries.