The Ministry of Finance has highlighted the use of data analytics, big data, and AI/ML in tax administration. Both direct and indirect tax departments employ these advanced technologies to make tax administration more effective, free of official discretion, business and taxpayers friendly.
Indirect Taxes
The flagship analytics project for Indirect Taxes is Project ADVAIT (Advanced Analytics in Indirect Taxes). ADVAIT has been rolled out by Central Board for Indirect Taxes and Customs (CBIC) in 2021, and it uses capabilities of big data and AI as well. The project has a threefold objective of enhancing Indirect Tax revenue, increasing taxpayer base, and supporting data-driven tax policy.
ADVAIT provides business outputs in reports, interactive dashboards, and analytical models. The functionality of each output is specifically designed to aid and assist officers in their day-to-day operations, ranging from reporting and ensuring tax compliance to detecting tax evasion. The portal has advanced analytical capabilities, including data matching, network analysis, pattern recognition, predictive analytics, text mining, forecasting, and policy studies. ADVAIT has been designed and developed in a knowledge-driven data ecosystem using some of the most advanced data warehousing business intelligence solutions.
Direct Taxes
The CBDT is utilizing data analytics, big data, and AI/ML methods to transform tax administration. These methods are being utilized to detect cases at a high risk for tax evasion, issue reminders for early tax payments, notify certain taxpayers about discrepancies in their tax returns and transactions, utilize big data methods for efficient storage and retrieval of information by tax officers, display taxpayer connections and highlight potentially risky transactions, and categorize taxpayers to target high-risk cases for evasion.
Benefits of Using Data Analytics, Big Data, and AI/ML in Tax Administration
Utilizing data analytics, big data, and AI/ML in tax administration offers numerous advantages. Utilizing big data, these technologies can assist in pinpointing financial risks, questionable patterns, and potentially risky entities within Customs and GST. They can also assist in boosting tax revenue, broadening the taxpayer base, and backing data-informed tax policy. Moreover, these technologies have the potential to decrease official discretion, boost transparency and accountability, and foster a more business and taxpayer-friendly atmosphere.
In addition, utilizing data analytics, big data, and AI/ML in tax administration can streamline tax collection and lessen the load on taxpayers. Taxpayers can take advantage of these technologies by getting timely reminders for advance tax payments and being informed about discrepancies in their tax returns and transactions.
Conclusion
Utilizing data analytics, big data, and AI/ML in tax administration is transforming tax departments globally. These technologies could transform tax administration by boosting income, broadening taxpayer numbers, backing data-centered tax policy, and lessening official judgment. The advantages of these technologies are plentiful and can create a business and taxpayer-friendly atmosphere which encourages transparency, accountability, and efficiency.