Demonetisation: How banks can help trace black money using technology

By | 26th November 2016
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After the Rs 500 and Rs 2000 currency notes were banned by the government, it was common knowledge that such an exercise can never reach fruition, simply due to the logistics involved. That hunch was today vindicated when the government announced the stopping of all currency exchange at the banks. It was simply not possible. People who have not been able to exchange and had been tiding over waiting for the queues at the banks to get shorter are in for a nasty surprise. Their money is now only worth the paper that it was printed on.

Right from the outset, the exchange had seemed like a Herculean task—millions of people hold the banned currency notes, with as much as 85 percent of the financial value of the economy held in higher denominations. The drastic measures are apparently aimed at controlling the so-called black money and curbing transparency and ensuring accountability in the system.

However, there could have been other ways to tackle the problem. This is the age of disruption, with new models challenging and even replacing the old ones, for example, Uber. The taxi aggregator uses licensed drivers, car ownership, smart phones, geo location identifiers, maps, credit cards, and a model based on demand and supply to set up a shared-resource transport system, which is disrupting the world of cabs and ricks.

Technology aided with innovation can trace the cash trail
All Cash leaves a digital trail. It is either at point of supply or point of consumption. Let’s look at how banks could have helped in tracing unaccounted and untaxed money through leveraging modern technology. With a little innovation and much less pain to the population, it is possible to trace black money. In fact, banks can play a crucial important role in hunting down tax evaders and black marketers.

The steps are simple and can be implemented with the proper backing of technology. To start off let us take a simple example: a person goes to the bank and hands over a bundle of currency notes to the cashier or some other relevant authority. The cashier or the person collecting the cash must utilize the currency machine to process and count the cash before it leaves that point of entry.

After the transaction is over, the currency notes could be associated with the specific account holder. All the data thus collected could then be relayed to a data cluster. On similar lines, the bank’s cashier can also associate the serial numbers that are printed on a currency and link them to a person at the time of withdrawal of money. All the data thus collected can again be relayed to the data cluster.

A huge amount of data will be generated and collected. Such enormous data is not a constraint for modern tools of analytics. Additionally, despite its hugeness, the data would be structured and categorised as there are no other lines of intersection. Other information and details including the account holder’s name, the name of the bank, serial number, date, time, and denomination can be accurately recorded and processed and analysed.

After all this data is fed into the tools, trends could emerge of the route and direction of cash flow, inter-account transfers, money trail, etc. The analysis could lead investigators to locate cash stashes and more importantly determine the flow of cash and identify end users.

For all of this to happen, currency counting machines would have to be installed in banks and equipped with sensors. It will also have to be made mandatory that all cash inflow is routed through the machine while processing. The technology can indicate monetary malpractices in real time and can detect corruption through existing infrastructure (banks that already have cash counting machines).

“Technology can help in tracing black money, that is, money that is out of the system as well as financial fraud. The inputs provided by banks can help locate unusual activity in currency flow or at an end point,” said Shashank Dixit, CEO, Deskera, a leader in cloud business software, which has its own Analytics tool. Correlations can be made and hidden patterns discerned. Investigative agencies could use the trends and tips to examine suspicious transactions, improve detection and surveillance, and predict and prevent financial fraud.

With over 10 years of experience in the field of journalism, the author is a technology evangelist and avid blogger.

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