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InvoiceGuard: An Intelligent Invoice Analysis and Fraud Detection System Using OCR and Machine Learning

Author

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  • Bala Ragupathi R
  • Kumuthaveni R
  • Mohanapriya D

Abstract

Invoice manual checks are slow to complete due to errors while there may be an issue of fake billing documents by suppliers, wrong calculation rates for bills etc. InvoiceGuard is a smart hybrid solution to automate bill processing and detect fraudulent activity through it. EasyOCR is used for converting an invoice image to structured information; it also performs rules based validation and duplicate detection so as to identify deterministic risks while simultaneously applying random forest algorithm on both invoices and suppliers' attributes for estimating likelihood of frauds. Two are combined as a single risk score weighted 40% for rule based risk and 60% for machine learning probability. The model was trained and tested on 300,000 invoices with an accuracy rate of 98.03%, precision at 98.07%, recall at 92.92%, F1 score at 95.43%, and ROC AUC at 96.02%.

Suggested Citation

  • Bala Ragupathi R & Kumuthaveni R & Mohanapriya D, 2026. "InvoiceGuard: An Intelligent Invoice Analysis and Fraud Detection System Using OCR and Machine Learning," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 12(5), pages 546-553, September.
    • Handle: RePEc:jbh:ijsrcs:v12:y2026:i5:id:2200
    DOI: 10.5281/zenodo.23564744
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT2612548
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