Sunday 22nd, July 2018
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Demo succeeded in unearthing black money, preventing corruption: FM

Published On : 23 Mar 2018


New Delhi, (PTI) Finance Minister Arun Jaitley has said that demonetisation of high value currency notes in November 2016 "succeeded" in unearthing black money and preventing corruption.

In a written reply to the Rajya Sabha on Tuesday, which was made available today, he said that at the time of demonetisation, on November 8, 2016, high denomination notes of Rs 500 and Rs 1,000 amounting to Rs 15.44 lakh crore were in circulation.

"At the rate, Specified Bank Notes (SBNs) were growing in previous years, SBNs would have become of the order of about Rs 18 lakh crore in December, 2017," he said, adding that the circulation of high value came down to 13.34 lakh crore last December.

Therefore, circulation of high value notes have been brought down effectively, Jaitley said in the reply.

The minister further said that as high denomination notes have been used for storing black money and in corruption, "it may be concluded" that demonetisation did control black money generation and corruption.

"Demonetisation, besides serving other objectives of eliminating fake currency, stopping terror financing, promoting formalisation of economy, promoting digital payments, also succeeded in unearthing black money and preventing corruption," he said.

After demonetisation, the Department of Revenue had launched Operation Clean Money' on January 31, 2017 with respect to about 17.92 lakh persons whose cash transactions did not appear in line with their tax profile.

Online verification of such cash transactions was enabled and the information in respect of identified cases was made available in the e-filing window of the PAN holder.

"Nearly 11 lakh persons submitted online response. High risk cases have been made available to the field formation for effective monitoring and follow up," Jaitley said.

He also informed the House that data analytics was being used to match information in IT returns with cash deposit data and identify high risk cases/ groups for necessary verification/investigation.







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