AI-Credit Card Parser for Zapier

PDF4me AI-Credit Card Parser in Zapier uses AI-powered machine learning to extract structured data from credit cards and card documents. Process credit card PDFs or images from your Zap triggers and actions—such as email attachments, cloud storage uploads, or form submissions—to automatically capture card numbers, expiry dates, cardholder names, CVV codes, card types, issuing banks, card brands, account numbers, valid dates, and other credit card fields. This action is ideal for credit card processing automation, payment card digitization, expense tracking, financial data extraction, automated card verification, PCI DSS compliance workflows, and credit card information processing that require AI-powered extraction with structured output inside your Zapier automations.

Authenticating Your API Request

To access the PDF4me Web API through Zapier, every request must include proper authentication credentials. Authentication ensures secure communication and validates your identity as an authorized user, enabling seamless integration between your Zaps and PDF4me's AI-powered credit card processing services.

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Key Features

• AI-Powered Extraction: Advanced machine learning technology for accurate credit card data extraction
• Multi-Format Support: Process credit cards in PDF, PNG, JPG, and JPEG formats from Zapier triggers and file actions
• Comprehensive Card Information: Extract card numbers, expiry dates, CVV codes, cardholder names, and card types
• Bank Details Extraction: Extract bank names, issuing banks, card brands, and account numbers
• Date Recognition: Automatic extraction of valid-from and valid-through dates
• Custom Field Support: Extract additional custom fields beyond standard credit card data
• Flexible Data Structure: Dictionary-based field extraction for dynamic and extensible data access
• Warning System: Receive warnings for potential data quality issues or extraction challenges
• Fallback Mechanism: Automatic fallback processing ensures reliable extraction
• Zapier Integration: Send extracted data to spreadsheets, CRMs, expense tools, and compliance systems via Zapier

Credit Card Extraction Capabilities

Field Recognition

• Card and Bank: Extract card numbers, expiry, CVV, cardholder name, card type, bank name, issuing bank, card brand
• Dates: Automatic extraction of valid-from and valid-through dates
• Warning System: Receive warnings for potential data quality issues or extraction challenges

Document Support

• Multi-Format: Process credit card documents in PDF, PNG, JPG, and JPEG from Zapier triggers and file actions
• Custom Fields: Extract domain-specific or custom credit card fields via optional Custom Field Keys; dictionary-based field access

Zapier Integration

• Downstream Steps: Map extracted data to spreadsheets, CRMs, expense tools, and compliance systems in subsequent Zap steps
• Triggers: Use files from Gmail, Google Drive, OneDrive, Dropbox, or form uploads as input

Parameters

Important: Parameters marked with an asterisk (*) are required and must be provided for the action to function correctly.

Required Parameters

Configure how credit card documents are passed into the AI-Credit Card Parser action within your Zap.

Parameter	Type	Description	Example
Credit Card File*	File	Source Credit Card File • Map the credit card file from a previous Zap step (for example, Gmail attachment, Google Drive/OneDrive/Dropbox file, form upload) • Supports PDF, PNG, JPG, and JPEG formats • Use the file output from your trigger or file-based action	credit_card_statement.pdf
Credit Card Name*	String	Credit Card File Name with Extension • Name of the input credit card file including the correct file extension • Used for format detection and AI processing optimization • Can be mapped dynamically from trigger or previous step data • Must include file extension (.pdf, .png, .jpg, .jpeg)	credit_card_statement.pdf

Optional Parameters

Parameter	Type	Description	Example
Custom Field Keys	Array	Optional Custom Field Keys List • Optional list of custom field keys to extract from the credit card • Use to capture domain-specific or custom credit card fields beyond standard data • Each item represents a custom field key you want the AI to look for • Pass as a JSON array string or mapped list depending on the Zapier field UI	["customField1", "customField2"]

Output

The PDF4me AI-Credit Card Parser action returns structured credit card data that can be used in subsequent Zapier steps.

Table

Table View

Response data in a structured table format:

Parameter	Type	Description
fields	Object	Dictionary object containing extracted credit card fields; each key is a field name and each value is a FieldData object with a Value property
warnings	Array	Array of warning messages indicating potential data quality issues or extraction challenges encountered during processing
fallbackUsed	Boolean	Indicates whether fallback extraction methods were used during processing
jobId	String	Unique identifier for the AI processing job, useful for tracking and debugging
jobIdExt	String	External job identifier for integration with third-party systems, if applicable
success	Boolean	Indicates whether the AI-powered credit card data extraction completed successfully
message	String	Descriptive message indicating the result of the credit card data extraction process

Common Credit Card Fields in Fields Dictionary:

The fields dictionary can contain the following common credit card related fields, among others:

Field Name	Type	Description
bankName	String	The name of the bank issuing the credit card
cardNumber	String	The primary account number (PAN) of the credit card, often masked for security
expiryDate	String	The expiration date of the credit card (typically in MM/YY format)
cardholderName	String	The name of the cardholder as it appears on the credit card
cvv	String	The Card Verification Value (CVV) or Card Security Code (CSC)
cardType	String	The type of credit card (for example, Visa, MasterCard, American Express)
issuingBank	String	The name of the bank that issued the credit card
cardBrand	String	The brand of the credit card (for example, Visa, MasterCard, Discover)
accountNumber	String	The associated bank account number, if available on the statement
validFrom	String	The valid-from date of the credit card (typically in MM/YY format)
validThru	String	The valid-through date of the credit card, often same as expiryDate

JSON

JSON Response Format

The raw JSON response from the action:

{
  "fields": {
    "bankName": {
      "value": "Chase Bank"
    },
    "cardNumber": {
      "value": "XXXX-XXXX-XXXX-1234"
    },
    "expiryDate": {
      "value": "12/25"
    },
    "cardholderName": {
      "value": "JOHN MICHAEL SMITH"
    },
    "cvv": {
      "value": "123"
    },
    "cardType": {
      "value": "Visa"
    },
    "issuingBank": {
      "value": "Chase Bank"
    },
    "cardBrand": {
      "value": "Visa"
    },
    "accountNumber": {
      "value": "1234567890"
    },
    "validFrom": {
      "value": "01/22"
    },
    "validThru": {
      "value": "12/25"
    },
    "customField1": {
      "value": "Value for Custom Field 1"
    }
  },
  "warnings": [],
  "fallbackUsed": false,
  "jobId": "87654321-4321-4321-4321-210987654321",
  "jobIdExt": "CC-2024-001",
  "success": true,
  "message": "Credit card data extracted successfully using AI technology"
}

Workflow Usage

Advanced Workflow Integration

The extracted credit card data can be seamlessly integrated with other Zapier apps:

• Expense Management: Store extracted credit card data in expense tools, Airtable, or Google Sheets for tracking
• Accounting Platforms: Create credit card records or expense entries in QuickBooks, Xero, or other accounting tools
• CRM & Databases: Store card metadata (masked) in CRMs or databases for card management and expiry tracking
• Approval Workflows: Route credit card data for verification using Zapier approval steps
• Expense Tracking: Categorize and track expenses using extracted credit card information
• Compliance Tracking: Maintain PCI DSS compliance records with masked or secured card data
• Document Storage: Link extracted credit card data with original statement documents in Google Drive, OneDrive, or Dropbox

Workflow Examples

The PDF4me AI-Credit Card Parser action in Zapier provides comprehensive workflow templates designed for real-world business scenarios. These proven automation patterns help you implement credit card data extraction seamlessly into your existing processes:

Expense Tracking Automation

Automated Expense Tracking Workflow

Streamline expense management with AI-powered credit card data extraction:

Complete Workflow Steps:

1. Trigger: Credit card statement uploaded to cloud storage or received via email
2. AI-Credit Card Parser: Extract card details, cardholder name, and account information using PDF4me AI
3. Card Verification: Verify extracted card number and expiry date with cardholder records
4. Create Expense Record: Insert credit card data into expense management system or accounting tool
5. Update Sheet/Database: Store extracted credit card data in Google Sheets or Airtable with metadata
6. Expense Categorization: Categorize expenses using extracted card information
7. Excel/Sheets Export: Export credit card data to Google Sheets or Excel for expense reporting
8. Approval Request: Send approval request for high-value expenses via Zapier
9. Email Notification: Notify finance team with expense summary
10. Archive: Move processed statement to archive folder with extracted metadata

Business Benefits:

• Automates expense data entry from credit cards
• Reduces manual data entry time and errors
• Accelerates expense approval cycles
• Maintains complete audit trail of expense data

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Credit Card Management Automation

Automated Credit Card Management Workflow

Centralize and organize credit card information with AI-powered extraction:

Complete Workflow Steps:

1. Trigger: Credit card statement received via email or uploaded to cloud storage
2. AI-Credit Card Parser: Extract card number, expiry date, cardholder name, and bank details
3. Card Lookup: Match extracted card number to card master list in Airtable or Google Sheets
4. Duplicate Check: Verify if card information already exists in your system
5. Create Card Record: Add credit card record to Airtable or database with all extracted fields
6. Expiry Date Alert: Calculate days until expiry date and set reminder
7. Update Card Portal: Update card management portal with extracted card information
8. Compliance Check: Verify extracted card data meets PCI DSS compliance requirements
9. Notification: Send card information summary to card management team
10. Archive: Store processed statement with extracted metadata in cloud storage

Business Benefits:

• Centralized credit card repository with searchable extracted data
• Automatic expiry date reminders prevent card expiration issues
• Proactive card management and tracking
• Comprehensive card analytics and reporting
• Improved compliance with PCI DSS requirements

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PCI DSS Compliance Tracking

Automated PCI DSS Compliance Tracking Workflow

Ensure PCI DSS compliance with automated credit card data extraction and tracking:

Complete Workflow Steps:

1. Trigger: Credit card statement uploaded to a compliance folder in cloud storage
2. AI-Credit Card Parser: Extract card numbers, CVV codes, and cardholder information
3. Data Masking: Apply PCI DSS compliant data masking to extracted card numbers
4. Secure Storage: Store masked card data in secure Airtable, database, or compliant storage
5. Access Control: Implement access controls for extracted credit card data via Zapier and connected apps
6. Audit Logging: Log all access to extracted credit card information
7. Compliance Check: Verify extracted data meets PCI DSS compliance requirements
8. Compliance Report: Generate PCI DSS compliance reports from extracted card data
9. Alert Management: Create alerts for non-compliant card data access
10. Documentation: Maintain compliance documentation with extracted card metadata

Business Benefits:

• Ensures PCI DSS compliance for credit card data handling
• Automated compliance tracking and reporting
• Secure credit card data storage and access
• Comprehensive audit trails for compliance inspections
• Reduced compliance risks and penalties

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Card Spend & Expense Categorization

Automated Card Spend and Expense Categorization Workflow

Categorize and track credit card spend using extracted statement data:

Complete Workflow Steps:

1. Trigger: Credit card statement uploaded to cloud storage or received via email
2. AI-Credit Card Parser: Extract card details, statement period, and transaction-related fields
3. Spend Categorization: Map extracted data to expense categories using Zapier logic or lookup tables
4. Budget Comparison: Compare categorized spend against budget or department limits
5. Sheet Update: Append categorized spend to Google Sheets or Airtable expense workbook
6. Approval Routing: Route high spend or out-of-policy transactions for approval
7. Report Generation: Generate spend and expense reports from extracted and categorized data
8. Notification: Send spend summary or alerts to finance or card program managers
9. Archive: Store statement and extracted metadata for audit and reconciliation

Business Benefits:

• Automated card spend visibility and categorization
• Better control over card program and expense policy
• Faster expense reporting and reconciliation
• Improved spend analytics and budgeting

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Industry Use Cases & Applications

Finance & Accounting

• Expense Processing: Automate expense data extraction from credit cards
• Financial Reconciliation: Reconcile credit card transactions with accounting records
• Expense Reporting: Generate expense reports from extracted credit card data
• Audit Compliance: Maintain structured credit card data for audit trails
• Budget Tracking: Track expenses using extracted credit card information

Banking & Financial Services

• Card Processing: Automate credit card processing and digitization
• Card Verification: Verify credit card information using extracted card details
• Account Management: Manage credit card accounts using extracted card data
• Fraud Detection: Detect fraudulent activities using extracted card patterns
• Customer Service: Provide faster customer service with automated card data extraction

Retail & E-commerce

• Payment Processing: Process payments using extracted credit card information
• Expense Tracking: Track business expenses using extracted credit card data
• Vendor Payments: Process vendor payments using extracted card information
• Financial Analysis: Analyze spending patterns from extracted credit card data
• Inventory Management: Link expense tracking with inventory management systems

Corporate Finance

• Corporate Card Management: Manage corporate credit cards using extracted card data
• Employee Expense Tracking: Track employee expenses using extracted credit card information
• Travel Expense Management: Manage travel expenses using extracted card details
• Expense Approval Workflows: Route expenses for approval using extracted card data
• Financial Reporting: Generate financial reports from extracted credit card transactions

Compliance & Security

• PCI DSS Compliance: Ensure PCI DSS compliance for credit card data handling
• Data Security: Secure credit card data extraction and storage
• Audit Trails: Maintain audit trails for credit card data access and processing
• Access Control: Implement access controls for extracted credit card information
• Compliance Reporting: Generate compliance reports from extracted card data

Credit Card Parser Best Practices

Document Quality

• Clear Documents: Use clear, readable credit card statement or document PDFs/images
• File Formats: Prefer PDF or high-resolution PNG/JPG; include file extension in the file name
• Single Document: Pass one document per action run for consistent field mapping in Zapier

Zapier Integration Tips

• Map Required Fields: Always map Credit Card File and Credit Card Name from the previous step
• Use Output in Filters: Use extracted expiry, card type, or other fields in Zapier filters or paths
• Custom Field Keys: Pass optional Custom Field Keys when you need extra fields; use dictionary-based fields for flexible access

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