Nitin K Patil, Pramod M Dumre


With the launch of the “One Nation, One Tax” approach in the sphere of indirect taxes in the form of GST since July 1, 2017, for enhanced tax compliance and increased economic growth in a federal country like India, the whole process has ushered in new challenges for which transformational governance has become imperative. On one hand, the ease of doing business has improved due to quick registration and refund mechanisms being incorporated through the use of digital solutions; on the other hand, the tendency to use this mechanism to defraud the government has also risen. To mitigate the risks involved, there is a need to significantly increase the focus on increased risk mitigation and systemic investment. It is within this broad framework that we intend to examine e-Governance1 as adopted in the state of Maharashtra.

Sales Tax Department’s efforts to computerise its tax system in Maharashtra

The Sales Tax Department’s efforts to computerise its tax system in Maharashtra began in 2007 with electronic compliances for filing returns, registration, payments, refunds, etc., when the Electronics Corporation of India (ECIL) was awarded the contract to establish IT infrastructure, Data Centre, and comprehensive maintenance. The transactional system was developed by Mastek, with back-end modules for Registration, Returns, Refunds, etc., and corresponding back-end workflows2 were also developed. This marked the VAT era. Later, in the GST era, the Department realised the need to separate the whole process into two major parts: System integration for a total solution for e-Governance (handled by NIIT Technologies) and the implementation of IT facility management services for LAN and WAN (handled by (n)code Solutions). (n)code Solutions was later replaced by Orient Technologies Ltd., while the application was developed by NIIT (Coforge) in 2016. All of this was a learning experience that proved to be an asset when the GST system was rolled out in 2017.

The GSTN Common portal and BIFA

The GSTN system was set up primarily to provide IT infrastructure and services to the Central and State Governments, taxpayers, and other stakeholders for the implementation of GST. The GSTN has pan-India coverage. All taxpayers have to visit the GSTN common portal for all compliances such as registration, filing of returns, making payments, etc. Two models were made available, namely Model 1 and Model 2. The Business Intelligence3 and Fraud Analytics (BIFA) system was developed to analyse the data available from taxpayer compliances across India. In Model 1, the front-end taxpayer service was provided by GSTN, while the officer’s services were from the respective state, with user charges being less compared to Model 2. In Model 2, both the dealer side and the back officer side services were developed by GSTN for the states. Earlier, Maharashtra opted for Model 1, feeling that its system would be able to integrate with the GSTN system. However, after some experience, it transitioned to Model 2 from September 7, 2019. The connectivity of GSTN to the officers of Maharashtra was to happen through the already developed system maintained by Coforge (NIIT earlier) and the existing IT system maintained by (n)code and later by Orient Technologies Ltd.

Data Analytics in the Maharashtra State Tax Department

As soon as computerised return filing and compliance began in Maharashtra in 2009, a significant amount of data became available for analysis and risk assessment. When the department started receiving validated electronic data, systematic risk analysis was conducted using SAS (Statistical Analysis System) after awarding the contract to Capgemini.

A “Compliance Risk Management”4 system was established, leading to a significant shift in the approach towards taxpayers due to the availability of data analytics. The concept of Issue-Based Assessment (IBA) was introduced for the first time to take action on risk parameters generated through Computerised Desk Audit (CDA). The front-end direct compliance system for dealers was also made accessible on the MAHAVAT website, promoting transparent compliance and closure of IBA/CDA parameters without officer intervention. Later, with the advent of electronic filing of returns in the GST era, the process of GST data analytics gained momentum, allowing for intelligent solutions. The selection of cases for scrutiny and audit began to occur based on risk-based5 selection.

In cases where taxpayers are provided with accurate information and filing is made easier, compliance is generally achieved. Hence, the approach was to encourage voluntary tax compliance through effective IT-based solutions. However, for those taxpayers inclined to evade taxes, the approach was to identify such cases early through vigilant measures and take corrective steps. In instances of deliberate misuse of the system, an investigative approach was adopted. The integrated risk analytics system successfully considered all taxpayers based on their risk profile6 and facilitated the risk-based selection of cases for scrutiny, audit, and investigation, achieving deterrence at the earliest.

Also Read | One Nation, One Tax: Inside Maharashtra’s High-Tech Strategy for GST Compliance

To ensure effective implementation, the Department established the Economic Intelligence Unit (EIU), responsible for risk profiling of all taxpayers and defining its parameters. The Department invested in its infrastructure, including hardware and SAS licences, and trained its officers to conduct analytics using the software, as the department lacked separate technical resources. The Department employs its own SAS Enterprise Guide solution and utilises Business Intelligence and Data Warehouse systems (BIDW), with CapGemini serving as the system integrator for the VAT period and PWC taking on the role for GST.

Distinguishing the BIFA and BIDW Models

The BIFA system developed by GSTN of the Centre should be distinguished from the BIDW system developed by Maharashtra. State officers use both systems. Currently, BIFA operates with a fixed set of parameters to generate various predefined reports periodically. State officers use these reports to identify potential defaults and mismatches. The parameters are not frequently changed and are based on all-India feedback. Additionally, individual states have the freedom to make inferences and use analytics to deter fraud. Using the BIFA system, it is not possible to select the top risky cases of the entire tax base, as State-level bulk transaction data is unavailable for download on BIFA. Access to BIFA is limited to a few officers, as GSTN has imposed restrictions. Nevertheless, BIFA has the advantage of obtaining details of related transactions from the all-India database.

The Maharashtra system proceeds with the revenue risk profiling of all its taxpayers and then establishes its parameters. The department has developed its own data warehouse by pulling GSTN data through APIs, initially seeking assistance from the Karnataka NIC team. However, the department has recently developed its own APIs.

The state has the liberty to change its parameters if they prove to be ineffective. Often, taxpayers learn which parameter is used and become vigilant about that specific parameter, but they resort to the misuse of the system for some other parameter. In such cases, Maharashtra’s flexibility to change its parameters helps it more effectively than the BIFA system. Additionally, Maharashtra has adopted a system of combining all risk parameters to generate a total annual risk, avoiding the multiplicity of proceedings—a feature not available in BIFA. The Maharashtra parameters are dynamic, and a team of senior officers sits every year to direct the EIU to define and change the criteria for selecting cases, introducing an element of surprise. Consequently, mischief-makers are kept guessing, prompting a more cautious approach by taxpayers to avoid major fraudulent acts. The Maharashtra system also includes PAN-linked analysis, supply chain analysis, circular trading analysis, and refund risk in its analysis.

Compared to BIFA, more officers have access to BIDW, and the analytics conducted by EIU are made available to all department officers through its internal network. However, complete access to the Data Lake of GSTN is not available on a real-time basis. Based on Maharashtra’s analytics system experience, GSTN is developing a Scrutiny Tool in BIFA for integrated risk analysis on a set of risk parameters suggested by the department.

Benefits

Some of the most tangible benefits resulting from the use of analytics in Maharashtra are that non-genuine taxpayers are easily identified and published on the website. This information is accessible not only to Maharashtra officers but also to officers of other states for further action. The list of major vendors and their products can be generated. The selection of audit and scrutiny cases is based on the total risk assessment of taxpayers and not on limited knowledge. Due to a low tax collection per unit staff deployed ratio (2.33 crore per staff, including class 3 and 4), Maharashtra continues to have a higher collection rate than many other states for a prolonged period. Despite having the highest registration base of 17 lakh active taxpayers, its GST collection is way ahead of all other states, with around Rs. 28000 crore monthly collection compared to other states having less than Rs. 12000 crore monthly collection.

Given this advantage, the tax authorities in Maharashtra have relied more on the trust-based system7 and voluntary compliance rather than having check posts or flying squads for surprise checks of e-way bills, vehicles, and taxpayers. Consequently, dealers consider Maharashtra more prone to facilitating ease of doing business, making it a preferred destination from this perspective. Despite this, Maharashtra’s revenue collection grows at a rate of around 18% per annum, much higher than many other states in India.

To achieve this success, the main factors listed are heavy IT-based investment over a prolonged period, training of officers to use the developed system, constant learning, and migration to a more comprehensive risk-based transformational governance. The department visits successful projects implemented by GST departments of other states and adopts them if found more useful.

Realising the bottlenecks and the way ahead

Maharashtra continues to be in the learning and consolidation phase, despite the listed successes. In the future, the department is looking to upgrade its analytics system by incorporating modern technologies of Artificial Intelligence and Machine Learning in the selection of audit and investigation cases. The department also plans to use an easy-to-use dashboard system for monitoring performance. Challenges for the department are related to the training of manpower to sustain the existing analytics system.

Also Read | Punjab receives ₹3,670.64 Crores in Pending GST Compensation

In this broad framework, Maharashtra’s indirect tax administration needs to be seen in terms of how it embraced e-initiatives and transformational governance to balance the twin objectives of ease of doing business and increasing its net tax revenue, tax base, and net tax collection to the exchequer through the voluntary compliance method.

Views expressed by: Nitin K Patil, Special Commissioner of State GST, Government of Maharashtra, Pramod M Dumre, Joint Commissioner of State GST, Economic Intelligence Unit, Government of Maharashtra

 

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