New Delhi, March 29 (IANS): Tax evasion is likely to get more difficult if not impossible with the entry of Big Data Analytics into the Income Tax (I-T) Department's realm of tools to check tax evasion starting April 1.
The Rs 1,000 crore programme named "Project Insight" would track social networking profiles of people and keep a tab on the expenditure patterns through the photographs and videos uploaded on social media.
If the purchases and travel expenses are found to be disproportionate to the declared income of a person, the I-T officials would be informed of the mismatch and actions would follow.
According to informed sources, the I-T Department has given the tax officials access to the software from March 15.
"If you are travelling to a foreign country and posting pictures on social media, or buying a luxury car which is beyond your means as per your returns filed, the I-T Department can use Big Data to analyse them and check the mismatch between your earnings and spendings. The process can easily use the complete trail even for the new tax filer," said people in the know of things.
"The I-T Department can also prepare a master file containing all the details and key information about individuals and corporates," they said.
The main objective of the project is to catch the tax evaders and increase the number of people filing returns and paying taxes.
The Insight Project will feature an integrated information management system, which will harness machine learning to help take the right step at the right time.
The software would also collect web pages and documents that could be probed by the I-T Department.
With the usage of Big Data Analytics, India is set to join a league of countries such as Belgium, Canada and Australia which already use Big Data to keep a check on tax evasion.
Since the inception of the technology in Britain in 2010, the system has prevented the loss of around 4.1 billion pound (Rs 36,942 crore) in revenue.
The software would ensure the overall scrutiny of all the returns filed and selection based on numerous small parameters from which the probability of tax evasion is likely to be nil, according to analysts.