The mainstream public commentary on GST revolves around the tax rates for various goods and services. This post will look at three other aspects of GST that do not get the attention it deserves. They cover the areas of GST administration (for both tax officials and taxpayers), investigations, and enforcement.
The GST system consists of four taxpayer-side processes - registrations, returns filings, e-way bills (EWB) generation, and refunds - and its administration by tax officials. These processes generate three distinct databases - GST registrations, GST returns filings, and e-way bills (EWB) generation. Once electronic invoicing picks up, the returns filings database becomes a trove of very granular business transactions. The administration consists of registration of taxpayers, scrutiny of returns, investigations to detect revenue loss and its adjudication (audit, inspection, and vehicle interception), and refunds.
On the administrative side, the GST Network (GSTN) operates a Back Office portal (BOWEB) that's accessed by tax officials for all administrative activities and taxpayers for all their transactions. This BOWEB provides a standardised process for all GST business processes. The GSTN also provides an MIS of the BOWEB processes and analytics of the transactions in the Business Intelligence and Fraud Analytics (BIFA) portal.
In the years since its adoption, the GST system has become more automated and access to data has increased. In the last couple of years, the fidelity and reliability of business processes like returns filings have improved with several workflows becoming fully automated. The returns filing and EWB generation processes are moving towards the ideal of a single source of truth. This will only be hastened with the advent of electronic invoicing.
Here are a few thoughts on the next stage of reforms to the GST systems.
1. Arguably the biggest institutional problem with any tax system is its revenue bias. This manifests in the form of excessive and unreasonable tax demands. This cannot be controlled without strong institutional restraints on such demands. Apart from the formal appellate processes, there should be institutionalised scrutiny and review mechanisms to validate demands before they are raised, especially those above a certain threshold. In a world gripped by the fear of oversight agencies like CBI and CVC, high-pitched demands can be restricted only by directly engaging with the problem.
I have blogged here about the issue and offered some suggestions to address it.
2. The statutory business processes of the GST system, on both the taxpayer's and the tax administrator's sides, are standardised and run on a single IT system, the BOWEB. This is an essential requirement for a national taxation system. However, this workflow standardisation should be viewed distinctly from value-added aspects like business intelligence generation and decision-support MIS reports.
In a large country with widely varying contexts and capabilities, there cannot be a one-size-fits-all BI or MIS. It's only natural that each tax unit figures out its unique BI and MIS. The GSTN could of course come up with some default version of data analytics and MIS that tax units could use as a starting point. However, the main objective should be to facilitate innovation in these areas by state units. This requires enabling access to data through web-APIs.
In this context, it's important to highlight two points. One, it should become part of the policy (in fact data transfer policy itself) to restrict all data access only through APIs and disallow downloads and sharing of information through the likes of file transfers. Only APIs-based access allows for the automation of data processing. Two, it's misplaced to believe that it's sufficient to enable access to loads of tax data that can be downloaded and analysed to generate actionable information. Instead, given weak capabilities and low motivation levels, data analytics must be workflow-automated so that they make available directly actionable information.
3. Given the extensive workflow automation and digitisation of tax processes, tax administration today is largely a knowledge-based activity. It's about identifying taxpayers whose transactions exhibit a high likelihood of evasion and then undertaking clinical investigations and enforcement of those cases. An essential requirement for this is the quality of data analytics and its interpretation as business intelligence. The objective is to identify taxpayers with a high likelihood of high-value evasion, while also minimising false positives (which can result in the harassment of genuine taxpayers).
This requires developing predictive models of various kinds of evasions that use multiple independent variables. Such models can be developed using the different GST databases, especially that of returns filings. These models will have to be periodically iterated to improve their accuracy in response to adaptive behaviours by taxpayers.
4. High-quality data analytics require access to data on taxpayer transactions as well as third-party data sources. However, state tax units currently have limited access to the transactional data of taxpayers of other states. Even if they can access case-by-case data on request, there's no way to conduct meaningful automated data analytics.
For example, a fake outward ITC claim (made on the GST revenue of a sale from another state) cannot be investigated without accessing the transactional data of the other state taxpayer. In such cases, while the purchaser's state loses revenue and has an incentive to investigate, it does not have access to the data required to do so. In contrast, the seller's state, which has the data, has no incentive to investigate.
For example, the investigations of fake ITC claims most of which involve crisscrossing inter-state transactions are hampered by the data access restrictions. Accessing third-party data sources like NHAI toll gates, Income Tax filings, PAN numbers, corporate registrations and filings (MCA21) etc even in a request mode is difficult, and is impossible in API-mode.
5. The GST system is currently administered by the tax units of the central and state governments. The taxpayers are more or less equally distributed between the state and central tax units, which exercise considerable concurrent jurisdiction over the taxpayers. This division creates a fundamental incentive mismatch problem that's at the heart of many of the challenges with GST systems reforms.
For one, with their very limited field presence (compared to the state units), the CBIC units have limited capabilities and incentives to focus systematically on tax evasion and revenue loss. Second, unlike the state tax units which are strongly incentivised to maximise revenues, the internal structure and geographical spread of CBIC units incentivise them to prioritise investigations and enforcement. All this means that the CBIC units tend to be focused on process compliance and raising demands, irrespective of whether they end up realising revenues or not. This also amplifies their revenue bias and results in unreasonable demands.
6. One of the biggest challenges in GST administration is the presence of fake and non-genuine taxpayers, who exist only to evade taxes through ITC claims. Instead of detecting shell companies after they have been registered through periodic one-off campaigns, the GST administration should shift to detecting likely shell companies at the time of registration application and also constant surveillance of new registrants for unusual activities (disproportionately high ITC claims, EWB generation, low cash-liability ratio etc.).
In this context, it's useful to keep in mind the trade-off between ease of doing business and economic inefficiencies. An excess of ease of doing business prioritisation, especially given the Indian context, can paradoxically end up lowering the ease of doing business. The pervasiveness of shell companies leads to GST administrators focusing on enforcement actions that also snare the honest taxpayers.
7. The GSTN provides an unmatched platform for mass flourishing and ecosystem development in two important ways. One, the GSTN's BOWEB can become a platform on which third-party applications can plug in through secure Application Programme Interfaces (APIs). These applications include those developed by state tax units to improve administrative efficiencies - automation of processes like scrutiny and refunds, screening and surveillance of registrations, faceless administration of registration and refunds etc - or by the National Informatics Centre's mobile App used for capturing vehicle interceptions. Or they could also include applications by fintech companies or the RBI's Trade Receivables Discounting System (TREDS) to enable lending to small and medium businesses, and e-commerce platforms to conduct their businesses. This has the potential to catalyse markets, improve economic productivity, and generate large economic multipliers.
8. The GSTN BOWEB is a source of some of the richest data on economic transactions. This data has immense value in granular macroeconomic surveillance and forecasting sources using trends of high-frequency indicators of consumption across even states and cities. It could plug a big gap in good economic data and spawn a vibrant research ecosystem. On the commercial side, the data could be used by businesses to assess creditworthiness, consumption trends, investment decisions etc. The data sharing can be made secure and with sufficient private protections.
One of the biggest obstacles to the use of GST data for macroeconomic data is the poor quality of HSN and SAC codes. For a variety of reasons ranging from the multiplicity of goods and services offered by any firm to tax evasion incentives, and the reluctance of the GST administration to be more firm with self-coding by the taxpayer, these codes are not a reliable unique identifier to categorise businesses. This must change if we are to make greater use of the GST data.
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