GST rate: GST evasion: More than 200 companies under the lens after data mining



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The Department of Indirect Taxation sent notices to about 200 companies after the data revealed that they were perhaps guilty of defrauding the Goods and Services Tax (GST). The results showed that these companies can under-invoice or sell their goods in cash to customers. Data mining has triggered alarm signals in situations where details in GSTR3B and GSTR1 did not match.

GSTR1 is an online form in which details such as the value of the product, the tax rate and the amount of the tax are mentioned. GSTR3B is an online form that records details of sales and purchases. "It is obvious that the GST authorities have begun to review the returns using data from the system and the information requested from taxpayers on specific aspects, which must be answered with specific details," said MS Mani, partner , Deloitte India.

"It is imperative that statements be doubly verified before the day before on the information sought by the authorities in order to avoid litigation."

Data mining showed that companies were buying products at high prices, but that there was a lag with sales. "You deducted your tax debts (GST) by means of an input tax credit payment of more than 95% of the total tax obligations … In other words, the payment of the tax was less than 5% "sent to a company that ET has seen.

The tax authorities have stated that many of the companies have recorded significant purchases of raw materials but few sales, suggesting that they might under-invoice or sell products at officially lower prices and agree to money in However, experts said that there could be another explanation. "The Tax Department has issued opinions, but many companies may have used the transition credit from the previous tax system for tax due and badume that they have unpaid tax on the actual value-added can not be fair, "said Sachin Menon, National Chief of Indirect Taxation, KPMG.

"This mismatch may also be due to the fact that suppliers do not download all the invoices while the company was able to take these credits since it received tax invoices and paid them." Last year's transition to GST allowed to use unused and unused tax credits in their books as transitional credits to offset future liabilities related to the GST.

Assuming that tax credits for all companies only cover a month may not be accurate, according to tax experts.

Legal experts have stated that such notices could give rise to litigation and that some companies might consider going to court. "Although there may be failures in some cases, the entire business community can not be looked at through the lens of fraud," said Abhishek A Rastogi, partner at Khaitan & Co.. be published after a thorough review.Many reasons for less cash payment.

In the event that we find that notices are arbitrary, we may choose to file subpoenas for such action. The tax officials also pointed out that many companies were undervaluing sales and overstating purchases. "In the previous tax regime, such transactions would generally not be detected because there was no mechanism to compare vendor inputs with sales," said one of the them. "Under-invoicing and over-billing are the main method by which most businesses escape tax and generate black money." The government has established sectoral "risk factors" that companies could operate to avoid paying the GST. According to the Tax Officer quoted above, the categorization or risk badessment for these audits was created using the badysis of voluminous data.

The government used statistics from the last two fiscal years to create the checklist. The big data badysis is used by the tax services since 2016. The tool is deployed to detect outliers in all sectors and the gap with the sector average taxes is used to determine the objectives. to deepen. "The government would have comparable," said a person with knowledge of the issue. "Say, if 10 consumer goods companies of a particular size are paying Rs 50 crore in taxes, it's unlikely that a business of the same size of income would pay Rs 1crore." data could easily report such anomalies and the goal would then be on such companies. "

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