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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64860
Volume:
10 |
6 |
Jun 2026
Pages:
1-11
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Kerala GST Department
GST Department
The Goods and Services Tax (GST) is one of the primary sources of revenue for the State of Kerala. However, challenges such as revenue leakage, unregistered businesses, fake registrations, under-reporting of turnover, and fragmented government databases continue to affect revenue mobilization. At the same time, emerging opportunities such as Vizhinjam International Seaport, digital commerce, and data-driven governance offer significant potential for expanding the GST base and improving compliance. This study proposes a data-driven framework for enhancing future GST revenue growth in Kerala through Geospatial Business Intelligence, Government Data Integration, and Vizhinjam Port-led Economic Development. The research integrates multiple data sources, including GST registration records, KSMART Trade License data, Income Tax data, E-Way Bills, E-Invoices, electricity consumption records, property tax databases, and geo-mapped business establishment data to identify revenue leakages and compliance gaps. The study examines the role of Vizhinjam Port in creating new economic opportunities through logistics, warehousing, e-commerce, maritime services, and export-oriented activities. By integrating GIS, Big Data Analytics, Artificial Intelligence, and government databases, the proposed framework aims to enhance GST compliance, identify revenue leakages, detect unregistered businesses, and support data-driven policy decisions. The study is expected to contribute to sustainable GST revenue growth and the development of an intelligent revenue management system for Kerala
KEYWORDS
This study recommends the establishment of a Kerala GST Revenue Intelligence Platform integrating GST, KSMART, Income Tax, Property Tax, Electricity Consumption, E-Way Bill, E-Invoice, Customs, and Geospatial Business Intelligence data to strengthen taxpayer monitoring, compliance management, and revenue forecasting. The Government may adopt GIS-based business mapping, AI-driven risk profiling, and inter-departmental data sharing to identify unregistered businesses, detect revenue leakages, and improve taxpayer compliance. Effective utilization of CGST Act provisions relating to registration, scrutiny, enforcement, penalties, and prosecution can further strengthen GST administration. The study also recommends leveraging Vizhinjam Port as a catalyst for logistics, warehousing, maritime services, e-commerce distribution, industrial development, and cruise tourism, thereby creating new taxable economic activities and expanding the GST base. In conclusion, the integration of Geospatial Business Intelligence, Government Data Integration, Artificial Intelligence, and Vizhinjam Port-led Economic Development can support sustainable GST revenue growth, reduce revenue leakages, improve compliance, and enhance data-driven tax governance in Kerala.
1. Goods and Services Tax Network (GSTN) (2024). GST Statistics, Return Filing and Taxpayer Reports. GSTN. 2. Central Board of Indirect Taxes and Customs (2024). Annual Report and GST Administration Reports. Government of India. 3. Ministry of Finance (2024). GST Revenue Collection Reports and Economic Analysis. Government of India. 4. Government of Kerala (2024). Kerala GST Annual Administration Report. Thiruvananthapuram. 5. National Informatics Centre (2023). Digital Governance and Data Integration Frameworks for Public Administration. 6. United Nations (2022). Geospatial Information Management and Data-Driven Governance Frameworks. 7. Adani Ports and Special Economic Zone Ltd. (2024). Vizhinjam Port Development Reports and Economic Impact Assessments. 8. Kerala State Industrial Development Corporation (2024). Logistics Parks, Industrial Growth and Investment Promotion Reports. 9. Survey of India (2023). Geospatial Data Standards and GIS Applications in Governance. 10. NITI Aayog (2023). Artificial Intelligence for Governance and Public Sector Analytics.
Publication Date
6/12/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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