What does the fourth industrial revolution, Industry 4.0, have to do with banks? In our latest NOYM, Shirin Haddad talks to Ville Sointu and Marina Repo, who lead Nordea's project to develop a pay-per-use platform for manufacturing.
As part of our latest Nordea On Your Mind report about Industry 4.0, we explore why manufacturing industry business models need to evolve and how banks can help facilitate this.
To delve deeper, Shirin Haddad from Nordea Thematics interviewed Ville Sointu and Marina Repo, who spearhead the Nordea Runway 2019 project, which focuses on ideas for financing Industry 4.0 and developing a pay-per-use platform for manufacturing as well as potential new revenue streams for the bank.
We suspect you are currently involved in one of the most exciting areas across the whole Nordea Group – Could you tell us about your roles, the story behind your team, and what you are currently working on?
Marina: Indeed yes, this initiative is breaking new ground and we are exploring the ways Nordea can become even more relevant to our corporate customers going forward through exploring what Industry 4.0 would mean for banks in collaboration with manufacturing companies in terms of new business models and benefits from instant payment flows. I am responsible for the business dimension of the team, which ties in well with my education and 15 years at Nordea spent in cash management, cards, client coverage, mobile payments and e-commerce. I have been involved in launching the Apple Pay, Samsung Pay and Google Pay applications in Nordea, and I am now working with Nordea Connect, our PSP solution for e-commerce.
The story behind our team is that we came together in Nordea’s Runway project in the summer of 2019, in which we focused on ‘engine as a service’ and explored the pay-as-you-go approach used by, for example, aero engine manufacturer Rolls-Royce. Our focus has since evolved into relevant development areas for our large corporate customers, looking for solutions to enable payment in real time and optimisation of cash flows from equipment with sensors sending data that triggers the payments. At the core, there is a legally binding contract facilitated by the bank. Initial customer feedback on our ideas and initiatives is encouraging, and in a hopefully more normal post-corona environment we would like to build an MVP together with some of them.
What makes the Industry 4.0 area so interesting for a bank like Nordea is the fact that it touches so many parts of our core business: trust, identity, real-time payments, working capital, supply chain, finance and potentially even capital markets.
Ville Sointu at Nordea Runway 2019 project
Ville: In a very similar way as on the business side, this area aggregates a long list of emerging technologies: IoT, cloud, edge computing, distributed ledger technology, digital contracts, artificial intelligence, machine learning, predictive analytics, PKI, secure elements, 5G and even augmented/virtual reality technology. It is probably due to this wide spectrum of business impacts and diverse technology landscape that I became fascinated by this opportunity in early 2019. My day job in Nordea is Head of Emerging Technology and my role in the Industry 4.0 team is to lead the initiative and make sure we seize this opportunity together with our customers. I am a technologist by background and have been working in the financial technology space for close to 18 years around the world, and it is a lot of fun to see so many technologies and solution areas from my past converge in this project.
Our current focus in the Industry 4.0 initiative is to initiate meaningful dialogues with customers, OEMs, technology vendors, integrators and other financial institutions. We’re keen to build a common understanding of what we want this future data-driven economy to look like.
How do you see the concept of Industry 4.0? Is it about technology or business models, or both?
Marina: Coming from the business side, the way I see it, the technology is already to some extent out there. Manufacturing equipment already has connected sensors. What corporates now need to realise improvements is business models that make the continuous payments actually work. We can look at subscription-based models in e-commerce as the first step in this direction and then move forward to machine-to-machine payments between two companies as the ultimate example. As an illustration, imagine a robot on a manufacturing floor that picks up screws from another robot which is owned by another company. Payments for the screws are made instantly between the two machines and settled to virtual accounts with pre-defined thresholds which are then being reflected to the companies’ real bank accounts. The banks act as trusted partners and provide the legally binding contract between the companies. Or imagine instead the simple example of a consumer product, such as a vacuum cleaner, with a dynamic pay-per-use model. You could pay based on how many square meters you clean and how intense the cleaning is.
Ville: One of the key things we have learned throughout our journey is that this is not just another technology bubble, but in fact a paradigm shift in our customers’ business models. The move to pay-as-you-go models is happening across the entire value chain, and technology that makes it feasible (eg IoT, AI, 5G) has now reached a point where it also makes economic sense to deploy it. Once our customers start operating accurate digital representations of their entire business value chain by using sensory data, we as a bank need to ask ourselves: are we with our customers in this transformation, or do we expect them to build on or circumvent a transaction banking model that has not seen radical evolution for decades?
One of the related macro trends that has appeared in many of our industry dialogues is the changing landscape of original equipment manufacturer (OEM) businesses, where capital-intensive equipment sales have been slowing down and increasingly replaced by significant growth in services businesses. Pioneers like Rolls-Royce, with its “power by the hour” model developed in the 1960s, have already shown that there is high optimisation potential from integrating equipment sales and services directly at the OEM. This model typically guarantees the best performance and output from any production system, and increasing measurement accuracy with real time IoT data and ubiquitous broadband connectivity makes it possible to create extremely granular pay-as-you-go service packages. These can also incentivise sustainable and responsible day-to-day usage of the production system itself.
How would you describe the benefits of usage-based business models compared with traditional produce-and-sell models? Would there be benefits only for OEMs, or across supply chains, including for customers?
Marina: The benefit is to get a continuous payment stream from your product, determined by the data displaying how it is being used. The manufacturer will be able to get an overview of how the product is being used, and can increase uptime by predicting when repairs are needed. And increased uptime improves the users’ cash flow. There is a difference between waiting 60 days to get a single original sales invoice fully paid, and getting continuous payments related to the usage. Another difference is which balance sheet the product resides in. This new model is not for all companies. Some will want to invoice and get paid the full amount after 60 days. But for others that already work with leasing models, a usage-based model can be an updated form of doing business. In this new model you can also add predictive maintenance and repairs to the offering, and you can get close to your customer over a long period of time. For supply chains, we are just starting to look into if there can be new forms of supply chain financing, which could unlock opportunities also for the suppliers to obtain some of the premium that the manufacturer obtains from pay-per-use or even pay-per-outcome models. For consumers, the benefits are easy to understand. With pay-per-use models, more people can afford to use the goods they want to use, and pay only according to their actual usage. This new affordable way also makes it possible for the manufacturer to get more customers!
Ville: Usage-based business models combined with sensory data could offer distinct benefits to all three parts of the value chain: the supply chain (raw materials and parts), manufacturing (factories) and operations (pay-as-you-go). The key theme across all these categories is working capital optimisation.
- Raw material and part suppliers can get paid in real time, as their products are used by the manufacturer (eg a robot picking up electronics components from a tower and paying for each component in real time)
- Factories could be filled with production robots that are operating under pay-per-use digital contracts; This could potentially free up incredible amounts of capital as OEMs could become value adding factory operators owning IPR to produce something rather than being burdened with the need to own vast amounts of commodity manufacturing equipment
- Equipment users/customers could benefit from lower upfront capital requirements and be incentivised towards more sustainable equipment usage.
The obvious question here is: On what balance sheet does all this capital sit if everyone operates under pay-per-use contracts? This is the exact question that led us to develop the digital contract model. We still have a lot of work to do and technical questions to answer, but in a situation where we can have secure and trusted metering of physical assets linked to legally binding contracts that trigger pre-authorised payment flows over a fixed time period, we can predict the risk of that pay-per-use contract very accurately and monitor its actual performance in real time. Predictable risk is two words that investors and other finance entities tend to like. A lot.
Beyond more traditional financing like loans, the technical approach of digital contracting makes it possible to create highly granular fractional shares of any individual contract. Theoretically, this could lead to interesting crowdfunding or chain financing opportunities, but these are potentially quite complex from a regulatory and compliance standpoint as of today.
Ville Sointu at Nordea Runway 2019 project
What will be needed to establish usage-based business models? Technology? Capital? Mindset change? Other things? Can you point to any examples of successes?
Marina: The simplest form of usage-based business models are subscription models in e-commerce, and more advanced models include virtual accounts structures and most importantly, the legally binding virtual contract between the parties in the collaboration. There will be investments needed to build this, usage of relevant technology, and of course a mindset change. One successful Europe-wide collaboration around Industry 4.0 is the Productive 4.0, where over 100 partners from 19 countries comprising universities, corporates and institutions collaborate.
Ville: Usage-based models are not entirely new, even in the industrial OEM space. Rolls-Royce did this in the 1960s with jet engines when they launched the “power by the hour” concept for airlines to pay for hours flown by engines, instead of owning and maintaining engines themselves. For institutions other than Rolls-Royce, it might not have been appealing to invest in jet engines on their balance sheets back then, but now, sixty years later, we have the opportunity to really scale up these models with digital trust models. And by doing so, we include more parties in the value chain.
There is still a lot of work to do before we can reach scale with these new business models. Industrial IoT investments, for instance, have been scaling up fast over the past few years. But it is clear that certain OEMs are more advanced in this space than others. On the bank side, we still have a ways to go in terms of developing our lending and risk assessment processes to incorporate real time data and digital contracts, let alone making these practices standard in financial services.
Currently, many companies are experimenting with prototypes to see how these models would work in real life. We have already seen experiments with pay-per-use lawnmowers and vacuum cleaners, and in the transport sector we have seen delivery trucks capable of paying and getting paid for transportation services for instance. Customer demand for usage models with lower capital requirements is set to grow fast as first real products reach the market. The most commonly talked about example of this is of course the pay-as-you-go car.
What new payment solutions will be needed for new business models? Is there a role for financial intermediaries like banks there?
Marina: Payments already exist. They can be card-based but will more likely be account-to-account based in the long run. However, what needs to be developed is more advanced virtual account structures and the construction of a contract engine, which is core. There is a role for banks as the trusted partner creating these legally binding contracts that need to exist. As an example, there can be IoT-connected assets which send signals to the contract engine which trigger payments based on usage or outcome. A bank can act as the trusted party in between the manufacturer and the user, and is responsible for that contract being legally binding.
Ville: Digital payment processing is a regulated activity, and most existing financial institutions should be in a good position to continue to provide these services in the future. Payment processing institutions will need new capabilities to authorise connected “things” to be able to pay in a controlled way, and on the other hand need to scale towards micro- and nano payments in massive volumes, as machines tend to operate much faster than us humans. In a way, you could see money movement becoming more of a “flow” rather than a series of small individual transactions. “Streaming money” might very well be the next big technical challenge we, as banks, need to solve in the transaction banking space.
The other technical challenge the industry needs to solve is standards in digital contracts. Creating a machine-readable digital contract that can be both legally enforceable and widely understood by different networks and systems is not a trivial task, and it requires a lot of practical on-the-ground testing in many jurisdictions before a practical approach can be developed. This will take time, but the upside of solving this challenge is significant for the entire society.
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