The Comptroller and Auditor General (CAG) of India has expressed concerns over the reliability of the Goods and Services Tax (GST) data maintained by the GST Network (GSTN).

The apex auditor’s Compliance Audit Report on Indirect Taxes — Goods and Services Tax, Union Government Department of Revenue (Indirect Taxes – Goods and Services Tax), tabled in the Parliament on August 8 says that an analysis of pan-India data provided by GSTN revealed significant data inconsistencies between the taxable value and declared tax liability. “Inconsistencies were also noticed between the CGST and SGST components of GST, and between ITC (indirect tax credit) figures captured in GSTR-3B and GSTR-9 returns”, the report said.

The audit looked into GST returns data in February 2021, pertaining to the period from FY 2017-18 to FY 2019-20, as filed by taxpayers up to August 2021. The report states that due to significant inconsistencies in the GST data, audit could not establish the reliability of data, for the purpose of finding audit insights and trends in GST revenue, and assessing high risk areas such as tax liability and ITC mismatch at the pan-India level.

The CAG report wants the finance ministry to consider introducing “appropriate validation controls (controls which prevent unreasonable data entries or alert the taxpayer to unreasonable data or both) supplemented by post-facto data analytics in respect of important data elements, where in data (such as tax amounts; taxable values; tax components, like CGST and SGST; validation of ITC and tax amounts, between the annual and monthly returns) is entered by the taxpayer.”

It also recommends the development of an effective review and follow up system within GSTN to review and address cases of data inconsistencies. “In case of significant deviations, tax officers may be alerted to the inaccuracies and directed to take necessary action”, the report said.

The report also pointed out that while there exists a mechanism to match ITC availed by a taxpayer with the GSTR-1 returns filed by the suppliers and to identify fraudulent cases through data analytics after the amount has been paid, adequate systems are not in place to prevent and mitigate refund related frauds by using real-time or near real-time data analytics so as to alert the tax officials before sanction of refunds.

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