GSTN to arm tax officers with tools to analyse data to check evasion

Almost a year into providing platform for tax collection, GST Network is now developing applications and tools for tax officers to help analyse data of their assessees and check possible evasion, a senior official said.

GST Network (GSTN), the company handling the technology backbone for Goods and Services Tax, has over the last 11 months provided a platform for businesses to file their returns and pay taxes every month.

GSTN Chief Executive Prakash Kumar said the next focus of the company will be on providing data analytics and improving user interface on the GSTN portal, besides developing backend system for assessment, audit, appeal and advance ruling for 27 states.

"'We are working on the analytics part. We have already started sharing with tax officers simple analytics on differences between GSTR-3B and GSTR-1, GSTR-3B and GSTR-2A. This is a broad state-wise data generated by GSTN, based on which the officers can look into the returns filed by taxpayers in his jurisdiction and spot mismatches," Kumar told PTI in an interview.

GSTN currently only provides support to tax officers (on data analysis). And gradually we are providing them tools so that they can do it themselves... We are in the process of developing an application for Commissioners to generate data without any external help, he added.

He said the tools would enable tax officers to do the analysis themselves. "We have started work on it, We had even showed the functionality to state officers. We will be slowly releasing the tools over the next few months," Kumar added.

GSTN is also working to improve its user interface by providing systematised error messages with 'error numbers'. Once a taxpayers sees a particular error number pop up on the screen, he can call the GSTN help desk for solutions.

"Now the error message also says what has gone wrong and what you need to do to correct that. It will show a particular error number, which helps the GSTN helpdesk person to quickly identify the error that the taxpayer is committing and can guide him accordingly," Kumar said.

Since the roll out of the GST from July 1, 2017, GSTN has handled 11.5 crore returns and processed 376 crore invoices.

Currently, over 1.11 crore businesses are registered under the GST regime, of which 63.76 lakh have migrated from the erstwhile service tax and VAT regime, and 47.72 lakh are new registrants. As many as 17.61 lakh businesses have opted for composition scheme under GST.

Kumar further said that GSTN has been sending Management Information System (MIS) reports to tax officers 27 states which are categorised as model 2 states for better understanding of taxpayers in their jurisdiction.

"We have provided 27 different MIS report for model 2 states. The tax officers get to see their own jurisdiction data, who their assessees are, return filed, taxes paid. The report has daily, monthly revenue collection list in the jurisdiction, ward-wise collection list, registration details, taxpayers with outstanding liability, disposal of cases, among other things," he said.

Based on the broad data mining by GSTN, tax officers have started analysing cases where there are instances of mismatch and have been sending scrutiny notices to taxpayers whose summary sales returns GSTR-3B did not match with final returns GSTR-1 or with system generated purchase returns GSTR-2A.

Besides, many tax payers have got notices for utilising input tax credit (ITC) for payment of most of the GST liability and have been asked to explain reasons within a stipulated time. Also, some notices have been sent for claiming less IGST input tax credit while filing sales returns as against the credit claims auto-generated by the GSTN.

On taxpayers getting notices for utilisation of ITC for GST payment, EY Partner Abhishek Jain said, "While these could be genuine cases for quite a number of businesses for reasons like low margins and large transitional credit pool, these notices could help check on utilisation of any ingenuine credits. Also, these could help detect fake credits claimed, if any".