The Opportunity for a Revolution in Currency Management

Chris Skinner, an independent commentator on the financial markets, blogger and author, has written an interesting piece about how technology is changing the way business is delivered ¹. He wrote it about how the digital bank model needs to change, but how might this apply to the world of cash?

The hypothesis is that once upon a time the structure of business was:

• Back office: manufacturing products focused on innovation and continuous improvement
• Middle office: processing transactions focused on quality (getting it right, on time)
• Front office: customer relationships based on deep understanding and co- operation.

Across all of these, data was key.

But times change. Depending on your business, for example banking, some tell a story about apps, APIs and analytics, probably using AI. Perhaps for cash the application of these is rather different than for those working in banking.

However, one thing that does apply is a change in the way we think about data. You cannot be intelligent with dumb data. Whether you call it smart data or not, we need data that is consistent, consolidated, co-ordinated and current. It has to be structured data, whether in the back, middle or front office. All of it needs to be holistic and robust.

If you can get to this ‘smart’ data, then you have the option to start feeding it into analytical tools, particularly those such as artificial intelligence (AI), machine learning (ML) etc ².

Within banking and payments, historically the infrastructure of the ‘middle office’ has been SWIFT, Visa, Mastercard, Vocalink, the EBA, STEP, TARGET, Fedwire, FedNow and such like ³. The ‘futurists’ dream of all this being replaced by smart contracts and blockchain-based systems, and SWIFT, Visa and Mastercard are already moving to tokenisation.

The future looks a long way from product, process, people, with the era of paper processed in buildings by humans being replaced by data processed by data with tokens. How could this carry over to currency management?

Smart data in currency management

We live in a digital age built on three interconnecting developments – digital transformation (moving from paper to no paper), the Industrial Internet of Things (IIOT) (allowing data collection to move from historic to real time) and what is often referred to as Industry 4.0, the fourth industrial revolution, where data is turned into information. These developments open up opportunities to collect cash related data and to turn it into usable information.

One obstacle is the need to standardise its format across every area of the cash cycle. The organisation that will gain most from the information will need to lead on this, almost certainly the central bank.

While currency is a physical product, we need to ensure it benefits from all that digital has to offer.

Back office: (production)

• Sources: Today’s production sites are built around measurement. From building management systems to end-to-end on machine measurement to automated finishing and vault management, the finished product, and its journey, is recorded in detail.
• Analytics: Already production data is used to avoid creating designs that are inefficient to produce. In addition, design data is being used to speed up the make-ready of machines. Digital twins are coming, but already advanced analytical tools and techniques are being used to optimise production.
• Opportunity: An opportunity lies in linking this data with the performance of currency in circulation through to end of life. This can feed back to the specification and design choices of the product.

Middle office: (issue and return)

• Sources: Vault data, reporting on cash centre issue and returns, sorting machine fitness and authentication data, destruction records.
• Analytics: Forecasting, stock management and cash performance in circulation uses advance analytical models. The use of AI and ML tools is possible.
• Opportunity: Electronic Data Interchange (EDI) standards such as GS1 and CashSSP allow for standardised data flows between organisations. It should allow real time information, enabling anomaly identification and more granular data to be made available to central banks and other stakeholders. The identification of problems could help a move to automated reporting. Digital twins in cash centres allow for better predictions and understanding of cash flows and performance.

Front office: (circulation)

• Sources: A large number of modern devices now fitness check and authenticate currency – Smartsafes, teller cash receivers/dispensers, deposit ATMs, modern counting machines. Most are connected to the internet. Local recycling is increasing, whether by banks, retailers, cash in transit (CIT) or cash management companies. Apps, such as Koenig & Bauer Banknote Solutions’ ValiCash™, can capture fitness data as well as authenticate notes.
• Analytics: While CIT and cash management companies use sophisticated tools to forecast and manage their cash, little of this is shared with central banks. Analysis of fitness and the performance and flow of cash is seldom a prime concern.
• Opportunity: Access cash cycle data to understand the flow, stock levels, quality levels and the performance of cash in circulation to allow cash cycle stakeholders, including central banks, to minimise cash movement and optimise cash quality in circulation. Some organisations already use digital twins, AI and ML, but these offer major opportunities across the cash cycle.

The privacy of payments is a valued attribute of currency. Concepts such as tokenisation may be useful in preserving confidence in this attribute.

Final word

We live in a digital age. Digital is perceived as ‘easy’ while ‘analogue’ is seen by some as complex, difficult and ‘messy’, old fashioned even.

While currency is a physical product, we need to ensure it benefits from all that digital has to offer, particularly around data.

1 - How the digital bank model needs to change – Chris Skinner’s blog

2 - The latest buzz word is agentic AI, a type of artificial intelligence (AI) that behaves like an autonomous agent by perform- ing repetitive tasks, making predictions, and interacting with other systems without direct human oversight.

3 - EBA – European Banking Authority, STEP – ECB Short-Term European Paper, TARGET – euro real time gross settle- ment system, Fedwire – US real time gross settlement system, FedNow – US instant payment system