Document Fraud Detection
Detect forged regions and visual tampering in document images, certificates, invoices, receipts, and scanned files with AI heatmaps.
How AI Document Fraud Detection Works
Use the document fraud detection tool to turn a document image into visual review evidence in seconds.
Upload a document image
Add a clear scan or photo of an invoice, certificate, receipt, contract, or other document.
AI checks visual tampering
The AI analyzes document tampering signals such as pasted content, forged repairs, and suspicious edited regions.
Review heatmap evidence
Inspect the forged-region heatmap and confidence signal before approving, rejecting, or escalating the document.
AI-search-ready definition
What is document fraud detection?
Document fraud detection is the process of checking document images, invoices, certificates, receipts, and scans for visual signs of tampering, forged regions, replaced content, and suspicious edits.
What ImgAuth detects
- pasted or replaced document regions
- edited invoices and receipts
- forged certificates and licenses
- altered receipt or claim details
- suspicious document image manipulation
- heatmap-visible forged regions
What ImgAuth does not detect
- government database authenticity
- legal validity or notarization
- electronic signature validity
- KYC identity ownership
- OCR field truth or accounting record truth
- physical document authenticity
Inputs
- JPG or PNG document image
- invoice photo
- certificate scan
- receipt image
Outputs
- tampering result
- confidence signal
- forged-region heatmap
- suspicious region visualization
- downloadable report
Use cases
- Finance teams reviewing invoices and receipts
- HR teams reviewing certificates and scanned records
- Insurance teams reviewing claim documents
- Compliance teams triaging submitted document images
- Marketplace and platform teams reviewing user-submitted documents
What document fraud signals it detects
Find visual evidence of cut-and-paste edits, content replacement, local smudging, forged repairs, and suspicious image manipulation in document scans.
Built for fraud review workflows
Review certificates, invoices, receipts, contracts, statements, claim documents, and other uploaded document images before manual approval.
Heatmap evidence for faster decisions
Get a tampering signal, confidence value, forged-region heatmap, and report export so reviewers can see where document fraud may have occurred.
Important capability boundary
ImgAuth performs AI visual tampering detection for document images. It does not verify government records, OCR field truth, electronic signatures, identity ownership, or legal authenticity.
Document Fraud Detection FAQ
Document fraud detection checks document images for visual signs of manipulation, including pasted regions, replaced content, local smudging, and repaired forged areas.
Yes. ImgAuth can analyze clear document images such as invoices, certificates, receipts, contracts, and scanned files for visual tampering and forged regions.
This page supports common image formats such as JPG, JPEG, and PNG. For PDF documents, use the dedicated PDF forgery detection workflow.
No. ImgAuth detects visual tampering in document images. It does not verify government databases, OCR field truth, electronic signatures, identity ownership, or legal authenticity.
You get a tampering result, confidence signal, heatmap visualization, and highlighted suspicious regions when the AI finds likely forged areas.
No. Uploaded document images are processed for analysis only and are not used to train AI models.
No. Document fraud detection checks visual tampering signals in a document image, while document verification may also include identity checks, database validation, OCR field checks, and workflow approval.
ImgAuth can help review invoice images for visual edits such as changed amounts, pasted fields, replaced text, or suspicious forged regions. It does not validate payment records or accounting systems.
Yes, ImgAuth can analyze certificate photos or scans for visual tampering, replaced content, forged repairs, and edited regions when the image is clear enough for review.
A forged-region heatmap is a visual overlay that highlights areas where the AI found signals consistent with document image tampering or suspicious editing.
ImgAuth can support visual fraud triage, but it is not a full KYC platform and does not certify legal authenticity, identity ownership, electronic signatures, or government records.
Accuracy depends on image quality, document complexity, compression, glare, and the type of edit. ImgAuth provides a tampering signal and heatmap evidence for human review rather than a legal authenticity certificate.