Across the Cash Cycle, banknote data can be gathered by central banks to provide insight into how cash performs and circulates around the world.
Data can be recorded by banknote printers, at central banks, commercial banks, cash in transit companies and, in some countries, data is gathered at every ATM.
Central banks have a great responsibility for the stability of a nation’s economic health, with an important element of this being the cash in circulation. Volume, quality, authenticity, distribution, removal, and destruction are all elements that central banks must be able to monitor and control.
But with so many different components to keep an eye on, just how do central banks oversee it all? The answer to that is data.
Here we explain how data can be used in the cash processing industry.
How can cash processing data benefit central banks?
After conversations with colleagues in central banks across the world, we learned that many of them are already collecting data about how cash performs, once it’s in circulation. But this is not true for all banks and the granularity of the data is certainly a limitation.
The data currently gathered on macro banknote trends in country can be combined with the individual per note data from cash processing machines to better shape future clean note policies, banknote designs, counterfeit reduction policies and improve operational performance.
One major difficulty that many central banks face is how to make use of this data in an efficient, meaningful way.
Here’s an example.
Central banks always want to know how long banknotes spend in circulation and what factors have the greatest impact on the degradation over time. Combining the banknote condition data with date on banknote information of banknote issuance would allow banks to the lifespan of a banknote with the reason for the fitness level prior to destruction.
Analysis of this data could influence small changes to the national fitness standards which could in turn extend the life of the note, saving product costs and the overall cost of cash.
So, if central banks could utilise this data to improve their banknote performance, what else would be possible with enhanced data analytics?
What’s possible with data analytics in the cash processing industry?
Looking at the current adoption of data analytics in the cash processing industry and the current difficulties faced by central banks, we’ve listed applications for data analytics within the cash cycle.
Currently, many banks are still using platforms like Excel to collect and store data. Data is only collected from direct sources, and no big data is collected from the commercial sectors.
This leads to an opportunity to introduce data feeds from commercial cash centres.
Performance of banknotes
As we discussed earlier, data utilisation in this sector is relatively limited compared to other industries.
At the moment, only a small number of central banks monitor banknote performance over time, especially at the per note level.
If banks had access to detailed feedback on banknote performance, they could deliver a reduction of production costs because of more accurate predictions about banknote lifespan.
Authenticity of banknotes
Anti-counterfeit banknote design is not currently data-driven, as most banks are still adopting a manual design process.
Additionally, the utilization of software capable of recording and tracking counterfeits is limited. The automation of this process would expedite response to counterfeiting and would generate data that can be used to build profiles and trends on counterfeits so that Banknote designers can focus on prevention at the design stage.
Central banks are seeing gaps in integration data and are unable to fully monitor their cash cycles. This is largely due to lack of 3rd party data integration.
At present, only a handful of central banks monitor the movement of cash in their region, and only a couple of banks can monitor their country wide cash cycle.
Data analytics will give central banks the ability to understand cash centre entry frequency, and the movement and use of cash in their region. This is great way to identify any trends in how different regions are using cash.
What are the benefits of applying data analytics in cash processing?
We’ve already looked at the difficulties we currently see in the cash processing sectors and discussed possible resolutions to these problems. But what would the benefit be of applying data analytics in cash processing?
By monitoring the average length of time banknotes spend in circulation between each cash centre re-entrance, central banks can set and monitor a more appropriate banknote lifetime range, which will save time, money and resources.
Following on from the point above, higher efficiency will have a direct financial impact. Less time and resources will be spent on monitoring banknotes in circulation, and we will therefore see lower production costs.
Improved note quality
Improved visibility on whether banknote life should be extended or can be shortened will, therefore, lead to improved note quality.
With higher efficiency and improved note quality progressing, it’s only natural that central banks will see an enhance reputation. Their ability to introduce innovative data analytics processes would be commended.
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