Bringing IoT to the Cash Center

Digitalization will leave no corner of the industry unaffected. This is particularly true for advances in big data analytics, artificial intelligence and the Internet of Things (IoT). The currency management sector is a perfect example – greater connectivity is already improving the way banknotes are processed and sorted.

The ever-increasing pace of commercial life means that cash centers are under greater pressure to process banknotes and banknote data more efficiently. The most common problems facing cash center managers working in central or commercial banks, cash-in-transit (CIT) companies and casinos is a lack of transparency. Process anomalies, counting or stacking errors, stoppages in banknote processing systems, time lost to unplanned maintenance, and a lack of visibility over the entire cash flow process, are all factors that slow processing. “A typical problem facing a cash center manager is whether it is the machine, the operator, the note quality, or the process that’s not working properly,” says Robert Rose, Senior Product Manager Digital Customer Solutions at G+D Currency Technology. He points out that managers, “not only want to see the performance of a single cash center, but also compare different site-, operator- and service-related data.”

Integrated end-to-end software solutions meet this challenge by turning data from machines, sites and resources – including the quantity of notes, throughput, counting and stacking performance, how many notes are rejected and, crucially, where the jams and stoppages are occurring and why – into operational excellence.  

Virtually identical – digital twins and the shape of things to come

To pave the way for Industry 4.0 and digital innovation, integrated software solutions are combining with a secure network to form the necessary infrastructure for new cloud-based software applications.
Within this highly secure and efficient advanced currency ecosystem, digital twin technology is proving to be a powerful driver of efficiency. By monitoring real data, in real time, a digital twin can deliver full visibility across the whole cash center. This means, for example, that a cash center manager can track where their operators are working at any given time. “You can see straight away where there are inefficiencies, right down to the component of each machine,” Rose explains.

Ultimately, integrated end-to-end software solutions will enable cash center managers to rethink and optimize processes.


Robert Rose, Senior Product Manager Digital Customer Solutions at G+D Currency Technology.

When viewed in the context of integrated end-to-end solutions, this form of application has a myriad of advantages. For one, it not only makes it easier to optimize operations and predict maintenance and personnel requirements but can also support test-case simulations and innovation without disrupting performance. “Ultimately, it will enable the cash center manager to rethink and optimize processes,” says Rose, adding that by providing a greater level of transparency across the whole supply chain, digital twins can also make the delivery of service level agreements easier.
For CITs this could include the ability to plan resources more effectively or form a better idea of how many vehicles or operatives they need to count and move money, thereby possibly reducing their exposure to penalties. Cash center backlogs and downtime can also be eased, and partners forewarned about expected delays, resulting in increased trust.

Integrated, intelligent, connected, secure

When a multitude of data is harvested, analyzed and utilized within integrated end-to-end solutions, everybody wins – owners and stakeholders are empowered with new insights. Anonymized technical data, such as the quality and fitness of banknotes and the number of rejects or anomalies, can be streamed onto partners without compromising security. This has the potential to enable banks to prepare for spikes in activity or anticipated deviations in quality, for example when dirty banknotes are taken during a festival. Likewise, retail customers could use the technology to see how their daily deposits are being processed. "This translates into big reductions in downtime for maintenance and servicing costs," says Rose.

"Furthermore, performance data can reveal patterns to inform process planning and benchmarking," Rose continues, sharing his predictions for how day-to-day cash center operations will change in line with the introduction of holistic digital solution propositions.
"First, we will see demand-driven ideas about how to feed money into the cash centers. At the moment the cash arrives in sacks and has to be unbagged. For banks it would be really good if there was more exchange of data – not the value of the banknotes but the volumes and fitness levels. For CITs, the future is really about workforce planning. Do they need to have armored vehicles travelling such long distances if it means compromising their service level agreements, or do they need another cash center in the area?” he explains.

Additionally, if artificial intelligence is used to enable self-learning machines to monitor the local operations and their own performance, and then adapt operations accordingly, it will further reduce the need for central control and enable automatic software updates and upgrades, driving even more efficiency.


For this reason, G+D Currency Technology’s Advanced Currency Management solutions, including integrated end-to-end software solutions such as the Performance Dashboard, are designed to support future innovation, including blockchain developments, data analytics and emerging technologies.

Case Study: National Bank of Belgium

A valuable source to perform data analytics at a later stage

G+D has been the National Bank of Belgium’s currency management partner for over 30 years. Their Cash Center sorting operations are located in Brussels and they operate six BPS® M7 and two BPS® 1000. One of the main challenges to optimize their cash center operations was a lack of information regarding the quality of the processed banknotes and the machine processing behaviour. Online and real-time information about the quality of the processed banknotes, combined with reject reasons, sensor data, jam information and throughput can lead to an overall higher productivity and performance.

The analysis of the data gave a new insight into banknote processing, helping to optimize performance and communication


Luc Certyn, Head of Banknote Sorting at the National Bank of Belgium (NBB)

The theoretical processing rate for the BPS® M7 is 33 banknotes per second but in practice this throughput fluctuated significantly.
What was the reason for this? Was it caused by non-optimal machine performance and settings or the banknote quality or was the operator the main reason for this variance in productivity?
With these questions in mind, G+D began a pilot in the summer of 2018 to introduce a new workspace dashboard. The primary objective was to increase throughput and net productivity and to have greater insight into banknote fitness and quality by denomination.

The pilot has been working well, according to Luc Certyn, Head of the banknote sorting division of the National Bank of Belgium (NBB). “There was a close collaboration between G+D and the NBB to establish the main KPIs (Key Performance Indicators). This has resulted in a successful, quick and smoothly installation of the first release on one BPS® M7 and a dedicated data server in Q1 2019. Five prioritized KPI’s were identified: the volume of the processed banknotes, the throughput, the reject reasons, the banknote quality and the jam rate. The collection of the data and the analysis of that data provides a new insight in the banknote process.This knowledge can help us to improve and optimize performance in general.  It also establishes  “figures-based” communication with the banks on the quality of the delivered banknotes. In future releases, more KPI’s can be expected and algorithms to determine these KPI’s will be fine-tuned based on experiences from the field. Moreover, this data is a valuable source to perform data analytics at a later stage” summarizes Certyn.

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