RECEIPT FRAUD PREVENTION

Fake Receipt Checker

Protect Your Business from Tampered Purchase Receipts

Arnotts tim tam loyalty campaign promotion poster.
Visual representation of accuracy in invoice ocr api technology.

Fake receipt detector for rewards and loyalty automation

Receipt fraud poses a growing challenge for organisations managing rewards programs and expense claims. Traditional verification approaches often rely on time-consuming manual reviews that strain resources and leave businesses vulnerable to sophisticated manipulation attempts.

Taggun addresses this challenge through AI-powered receipt verification that transforms how businesses validate proof-of-purchase submissions. Our platform combines receipt OCR technology with advanced fraud detection algorithms to automatically identify tampered receipts, detect duplicates, and flag suspicious patterns in real-time. This supports organisations with proactive receipt fraud prevention and time saving automation that enable real time experiences and the scalability to scan and process receipts at high volumes efficiently.

Online Fake Receipt Checker

Follow these steps to spot suspicious receipts with AI-powered fraud detection. Results typically return in a few seconds; processing time varies with the document and enabled checks.

1. Upload Your Receipt

Drag and drop your file - PDF, JPG, PNG, GIF, or HEIF - into our clean, intuitive interface.

2. AI-Powered Check

Taggun extracts receipt data and runs the enabled fraud checks. Results typically return in a few seconds.

3. View Your Results

Spot suspicious receipts with AI-powered fraud detection and review the reported findings.

Try the fake receipt checker online now

Try Taggun’s receipt OCR and fraud detection. Fraud detection is included on Advanced and Enterprise plans.

Understanding Receipt Fraud Detection

Receipt fraud detection uses the following fraud detection checks:

Spotting Altered Details

Modified purchase details such as dates or amounts.

Spotting Altered Details

  • Identifies identical or highly similar receipts to prevent multiple submissions of the same purchase.
  • Surfaces potential repeat submissions, including lightly modified receipts, for review.
  • Compares new submissions against historical data using advanced algorithms to spot patterns of repeat fraud.

Cashback Campaign

Duplicated or similar submissions aimed at exploiting reimbursement or reward programs.

Digital Tampering Detection


  • Recognizes digitally altered receipts, including changes to crucial fields like purchase date, amounts, or merchant details.
  • Analyse receipt images for manipulation using pixel and metadata checks.
  • Uses metadata checks to flag suspicious receipt images.

Flagging the Handwritten

Handwritten receipts that might be more prone to manipulation.

Handwritten Receipt Detection


  • Identifies handwritten receipts, which can carry a higher fraud risk due to difficulty in verifying authenticity.
  • Allows separate handling or extra verification when receipts are partially or fully handwritten, ensuring more targeted scrutiny.
Receipt Validation API Integration

The Evolution of Taggun’s Fraud Detection Tools

Smarter OCR Tech

Enhanced OCR receipt verification that accurately captures structured data from multiple file formats.

Receipt Scanning Tools, Your Way

Tailor receipt OCR and fraud detection to your workflow. Fraud detection is included on Advanced and Enterprise plans, with controls enabled in Feature Settings.

Whether you’re running a global rewards program or monitoring internal expense claims, Taggun’s tools integrate seamlessly with existing systems to flag suspicious receipts and fraud signals before they escalate.

Infographic of a receipt scanning based customer loyalty promotion.

Partner with us - Your Industry Leading Solution for Receipt OCR and Fraud Detection

Request a demo
Visual representation of accuracy in invoice ocr api technology.

How it works

  1. Submit Receipt:
    Submit a supported file to a verbose extraction or validation endpoint with the relevant fraud checks enabled.
  2. Receipt OCR and Fraud Analysis:
    Use enabled similarity checks and digital tampering detection. Handwriting detection is available on eligible verbose extraction requests.
  3. Fraud-check Results:
    Enabled checks return their own flags, scores or similarity matches when available.
  4. Results
    The API returns both the fraud detection results and the extracted receipt data. This data includes merchant information, transaction amounts, and other essential details.

Add Fraud Detection to Your Integration

Enhance your existing Taggun OCR implementation with fraud detection in minutes. Fraud detection is included on Advanced and Enterprise plans. Enable available fraud controls in Feature Settings.

Quick Setup

  1. Signup for one our AI OCR receipt scanning plans that include fraud detection
  2. Integrate the API and add the fraud detection and receipt OCR to your receipt scanning workflow.
  3. Use the available fraud-check results returned with each eligible request.

Available fraud-check results are conveniently included in the API response alongside your extracted receipt data.

Infographic of a receipt scanning based customer loyalty promotion.
Receipt OCR API with Fraud Detection

Sample API Response

Illustrative verbose extraction response excerpt. Fraud outputs appear within entities.

  • similarReceipts - Shows two existing receipts with high similarity scores, indicating potential duplicate submissions.
  • tamperDetection - Provides the documented tampering flag and score when available.
  • handwritingDetection - Includes the handwriting flag ("isHandwritten": false) and handwriting score for this sample.
{
  "entities": {
    "similarReceipts": [
      {
        "referenceId": "REC-20240105-ABC123",
        "userId": "USER-9876543",
        "trackingId": "T-20241005-9276439",
        "similarityScore": 0.9779201745986938
      },
      {
        "referenceId": "REC-20240106-XYZ789",
        "userId": "USER-1234567",
        "trackingId": "T-20241005-2921841",
        "similarityScore": 0.9779201745986938
      }
    ],
    "tamperDetection": {
      "data": {
        "isTampered": false,
        "tamperedScore": 0
      }
    },
    "handwritingDetection": {
      "data": {
        "isHandwritten": false,
        "handwrittenScore": 0.05660377358490566
      }
    }
  }
}
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