The Real Big Data – sources and laundries of black money
Consider an economy in which 38% of the GDP evades income tax, and that only 1% of the people pay income tax. This is probably true in respect of India. I ask the following questions in this light.
Assume that serial numbers on high value currency notes can be read by currency counting machines in banks and that ATMs loaded with notes of known serial numbers report to a central server as to who is issued, and who deposits, which currency notes.
What techniques can we use to monitor currency flow using all this information? What insights can we get? Are there a set of economically significant applications that would justify the cost of this surveillance? Can we identify potential sources of “black money” and potential launderers of such money?
What risks to citizens’ privacy does such monitoring pose?
I present a more detailed note on this topic along with the questions raised in the following blog post.
http://newstudentresearch.blogspot.in/2016/11/the-real-big-data-sources-and-laundries.html
Dear Ramani,
This is an excellent idea I must say. First thing is to store this data in form of a graph wherein each node is a person and each link represents a transaction (debit or credit) details. Now, the net debit and credit should be almost equal if a person has all money white. You may also utilize centrality approaches (from Social Network Analysis) for such graph study to derive fruitful relations.
Although potential source of black money could only be found out only if money is traced throughout the market because hard cash transactions are difficult to track for instance if black money is used only for entertainment purpose such as movie, dramas, branded clothes, food courts, and others wherein the recorded amount is quite less to be ignored by the system. These cannot be traced by such systems.
For such applications, I guess the best is to have a passive RFID tag on currency notes and record each and every transaction and flow of money in the market.
Devang Swami has an interesting idea of comparing deposits and withdrawals in an account. I interpret what he says as follows: If an account A gets significant deposits regularly, but draws out most of it as cash, it is an "account of interest!" The serial numbers of notes issued from A are worth tracking.
Incidentally those who read the blog post related to the question above may be interested in the sequel:
http://newstudentresearch.blogspot.in/2016/11/using-atms-to-do-currency-tracking.html
An article in Economic Times has said that about 4% (5.1 crore) of Indians filed Income Tax returns in 2015-16, but only 1.3 crore individuals in 2014-14, paid income tax. This shows that only 1% of Indians pay income tax. Visit http://economictimes.indiatimes.com/wealth/tax/these-10-points-in-government-data-show-what-india-pays-in-taxes/articleshow/52053092.cms
1 crore = 10 million
This does not mean most Indians evade income tax! Most are employed in the informal sector and have fairly low incomes.
In conjunction to my previous answer may I also suggest to store such graph model data can be stored and visualized in Neo4j database which is used for big data management for graph modeled data such as social network, maps and others....
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