Data Analytics post Demonetization in India

The demonetisation of ₹500 and ₹1000 banknotes was a policy enacted by the Government of India on 8 November 2016.

The announcement was made by the Prime Minister  Narendra Modi .PM  Modi declared that use of all ₹500 and ₹1000 banknotes would be invalid from midnight  and announced the issuance of new ₹500 and ₹2000 banknotes in exchange for the old banknotes.

The government claimed that the demonetisation was an effort to stop counterfeiting of the current banknotes allegedly used for funding terrorism, as well as a crack down on black money in the country. The move was described as an effort to reduce corruption, the use of drugs, and smuggling.

(source – https://en.wikipedia.org/wiki/Indian_500_and_1000_rupee_note_demonetisation )

 

This led to huge lines of people  outside banks and ATMs to withdraw new notes for daily needs and depositing cash to exchange notes f older denominations.

This also leads to a huge data analytics opportunity for data science to serve treasury and tax departments of India. The following data points would be of particular scrutiny for Indian data scientists helping or om contract to Indian Govt.

  1. Fraud– This would examine data points where inactive and dormant bank accounts suddenly had a huge inflow of cash. This data would be further matched and merged with income tax records using PAN CARD as a matching and AADHAR CARD too. Additional matching keys would be Name, Date of Birth, Address
  2. Terrorism – Terrorism in India is specific to a few geographic areas like Jammu and Kashmir and Naxalite areas. These could be further analyzed for fine tume of unusual currency patterns
  3. Cashless modes for laundering money ( Anti Money Laundering)- Plastic Money and Mobile apps saw a huge upsurge for transactions. This could be further used for additional sources of information since KYC norms of Telecom need Identification and so do Bank Accounts.
  4. Specific sectors- Land (real estate), Jewelery and other high value, high ticket items can be scrutinized

 

Overall data will be huge, so choosing the right database combination as well as the analytic (including especialy Big Data Spatial Analytics) could be key to help the current PM ‘s ambitious vision to transform India’s economy.

Comments are welcome.

Author: Ajay Ohri

http://about.me/ajayohri

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