Veryfi Blogpost: AI_Generated Receipts
AI-generated document detection is an integrated component of the Veryfi Fraud Suite that identifies documents created using artificial intelligence tools. The system employs advanced detection methods to flag potentially fraudulent AI-generated documents and returns a "Generated Document" decision in the Fraud Attribute when suspicious patterns are detected.
Detection Methods
Veryfi uses two complementary detection approaches that work together to provide comprehensive AI-generated content identification:
1. Image Artifact Analysis
The primary detection method uses sophisticated computer vision models that perform pixel-level analysis to identify patterns typically associated with AI-generated images. This approach:
Analyzes image artifacts and pixel patterns characteristic of AI generation
Employs multiple specialized models for enhanced accuracy
Functions independently of file metadata
Provides confidence scores for detection results
2. Metadata Analysis
AI-generated images can also contain distinctive metadata signatures that can indicate artificial creation. Veryfi system also examines file metadata and EXIF data embedded within documents, including:
EXIF data, Document metadata, Technical metadata
How Results Are Delivered
Fraud Integration
When Veryfi Fraud Suite is enabled, AI-generated documents are flagged through:
Fraud Attribute: Returns "Generated Document" as a fraud type
Fraud Color Coding: Red color indication when the detection threshold is exceeded
Screenshot Field
Results for vision model also appear in the meta.pages.screenshot field with possible values:
ai_generated- Document identified as AI-generatedother_screenshot- Different types of screenshots detectedmobile- Mobile screenshot identifiednull- No screenshot characteristics detected
A confidence score accompanies each detection result.
📚 Read more about Artifact Analyses
Limitations & Considerations
Metadata Vulnerabilities
Metadata can be easily removed or altered
File conversion, screenshots, or format changes often eliminate metadata evidence
The vision model serves as a backup detection when metadata is unavailable
Physical Document Challenges
Screen Photography: Taking photos of screens displaying AI-generated content significantly reduces detection accuracy
Print-and-Scan: AI-generated documents that are printed and then re-digitized present detection challenges
PDF Limitations
AI-generated PDFs created programmatically (rather than as image files) may not be detected by the vision model or Exif data checker, as these are rendered documents rather than generated images. To improve coverage of PDF documents, we are currently working on Layout Analysis.
Best Practices
Make sure your implementation combines both detection methods for optimal coverage
Adjust thresholds based on your risk tolerance and false positive acceptance, either via Business Rules or in your business validation logic, if you handle it on your side
Monitor detection patterns to identify potential fraud trends
Consider the limitations when evaluating edge cases
Report to us new undetected cases, and we will work together on their coverage
This detection system provides a robust foundation for identifying AI-generated fraudulent images while maintaining operational efficiency and minimizing false positives.
Please note that Fraud Suit ( that includes AI-generated detection) is not enabled by default. Please reach out to [email protected] if you would like to access this feature.
How can I test Veryfi's AI-generated receipt detection?
Try uploading a suspicious receipt here and Vee, our mascot, will let you know if it’s fake or not. If you already have an account with us, please contact us at [email protected] and request it on your account through our Customer Service team.