Both direct and indirect tax dept employ data analytics, big data and AI/Machine Learning in tax administration to make it more effective

Categories: Press Release

The Government is using data analytics, big data and Artificial Intelligence/Machine Learning in tax administration to make it more effective, free of official discretion, business and taxpayers friendly. This was stated by the Union Minister of State for Finance Shri Pankaj Chaudhary in a written reply to a question in Lok Sabha on March 27, 2023.

Data analytics is being used to identify fiscal risks, suspicious trends and patterns and risky entities in Customs and GST by leveraging big data, the Minister added.


The Project ADVAIT (Advanced Analytics in Indirect Taxes) has been rolled  out in 2021, as a flagship analytics project for Indirect Taxes, by Central Board for Indirect Taxes and Customs (CBIC). The project uses capabilities of big data and Artificial Intelligence as well. ADVAIT has been envisaged with a threefold objective of enhancing Indirect Tax revenue, increasing taxpayer base, and supporting data-driven tax policy, the Minister stated.

Further, the Minister stated, ADVAIT provides business outputs in three formats:

  • Reports,
  • Interactive Dashboards, and
  • Analytical Models

The Minister stated that the functionality of each output is specifically designed to aid and assist officers in their day-to-day operations that range 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, keeping in view the 3 I’s:

  • Information,
  • Insights, and
  • Intelligence


The Minister stated that the Central Board for Direct Taxes (CBDT) is using techniques as data analytics, big data and Artificial Intelligence/Machine Learning for:

  • Identifying cases with High Risk of tax evasion and high likelihood of income addition, for further scrutiny.
  • Identifying taxpayers to send reminders for advance tax payments.
  • Prompting specific taxpayers about apparent mismatches in ITRs and transactions made, so that taxpayers may revise their returns.
  • Using big data techniques for storage and effective search of information by income tax officers.
  • Using data analytics over networks of taxpayers visualize the taxpayers relationships and to flag potential high-risk transactions.
  • Using data analytics techniques for segmentation of taxpayers to focus campaign on high- risk cases from tax evasion perspective.

The Press Release can be accessed at: