Open Access Research Article

USING ARTIFICIAL INTELLIGENCE TO VERIFY GST INVOICE AUTHENTICITY: TACKLING QR CODE FRAUD IN E-INVOICING

Author(s):
ANKUL PRAJAPATI SHUBHAM SHARMA ARYAN PUNDIR
Journal IJLRA
ISSN 2582-6433
Access Open Access
Volume 3
Issue 7
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Abstract

India’s transition to a digitised tax ecosystem through GST and e-invoicing has strengthened tax administration and reduced reliance on manual verification. However, the existing e-invoicing framework contains a significant vulnerability while a digitally signed QR code authenticates the metadata embedded within it, it does not establish that the visual contents of the invoice correspond to that metadata. This “analog gap” enables manipulation of invoice amounts, GSTINs, and other fields while retaining a valid QR code, posing particular risks for Micro, Small and Medium Enterprises (MSMEs) that frequently rely on fragmented billing systems and digitally circulated invoices. This paper examines the legal and technological implications of this verification gap, particularly in light of AI-assisted invoice forgery and QR-based phishing (“quishing”). It argues that reliance on QR-code authentication alone may expose genuine recipients of manipulated invoices to tax, penalty, and prosecution consequences despite their reliance on officially available verification mechanisms. To address this problem, the paper proposes “GST Administration 3.0”, an AI-enabled layered verification framework that supplements cryptographic authentication with Optical Character Recognition (OCR), semantic comparison, visual forensic analysis, and deep-learning-based anomaly detection. The proposed system would compare invoice contents with QR-encoded metadata, identify potential manipulation, generate risk classifications, and provide explainable verification reports. These records could also assist taxpayers in demonstrating due diligence and enable authorities to distinguish fraudulent actors from bona fide recipients. The paper further examines the statutory and constitutional implications of AI-enabled GST verification and proposes targeted reforms to GSTN verification mechanisms, CBIC enforcement guidance, and the e-invoicing framework. It concludes that AI-assisted verification can bridge the gap between cryptographic authentication and document integrity while strengthening revenue protection and reducing disproportionate compliance risks for MSMEs.

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Author Details

Authors: ANKUL PRAJAPATI, SHUBHAM SHARMA & ARYAN PUNDIRRegistration ID: 1013330 | Published Paper ID: IJLRA13330, IJLRA13331 & IJLRA13332Year: Oct-2026 | Volume: 3 | Issue: 7Approved ISSN: 2582-6433 | Country: Delhi, IndiaPage No.: 812- 837

Article Information

USING ARTIFICIAL INTELLIGENCE TO VERIFY GST INVOICE AUTHENTICITY: TACKLING QR CODE FRAUD IN E-INVOICING

Authors: ANKUL PRAJAPATI, SHUBHAM SHARMA, ARYAN PUNDIR

  • Journal IJLRA
  • ISSN 2582-6433
  • Volume 3
  • Issue 7
Citation Download Paper Full Details Search on Google Search on Google Scholar

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International Journal for Legal Research and Analysis

  • AbbreviationIJLRA
  • ISSN2582-6433
  • AccessOpen Access
  • LicenseCC 4.0

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