Getting into gear with the Internet of Things

The increased data and visibility of company value chains through digitalisation and technology such as the Internet of Things (IoT) undoubtedly offers all sorts of opportunities for developing financial services that effectively utilise this new transparency. An age of new digitalised industries requires new digital financial services to match.

In the Industry 4.0, machines in factories and other physical production facilities are augmented with wireless connectivity and sensors and connected to a system able to visualise the entire production line and, in some cases, make decisions on their own. Industry 4.0 encompasses a wide area of connecting data or industrial IoT data with payment capabilities, identity capabilities and then financing. It is easy to imagine that financing the future fourth industrial revolution will be derived from this combination of data and financial services.

On a Rolls

One concept that may be interesting to look at is what is known as the ‘car as a service’ model. This relates to using connected cars with IoT data capabilities to understand how the car is being used and by how much, so that drivers can be charged based on real usage of the car rather than an estimate, which is usually the case with traditional leasing models.

Rolls Royce’s ‘engine as a service’ provides a good source of inspiration and with their ‘power by the hour’ model, they are able to provide airlines with engines and charge them by the number of hours they are being flown instead of requiring a full upfront capital cost. The interesting story about ‘power by the hour’ is that it was actually invented in the 1960s. This was way before any proper computing capabilities or let alone any type of connectivity that would allow IoT to happen. Back then they were simply measuring how long the plane was in the air and charged accordingly.

Rolls Royce decided that instead of letting the airlines manage these engines, they would offer maintenance as a service where they would take over all of the upkeep and life cycle management of the engines. They would make sure they had the right spare parts in place and the right type of competencies, the right type of engineers in the right locations to maximise the life time value of a single engine. The benefit for the airlines is that they don’t have to preserve their own separate maintenance capabilities or spare parts inventories. They just pay per use of the engine.

Now that we have digital connectivity in all of the planes that are in the sky right now, Rolls Royce have started to move to a model where they not only use these predictive maintenance capabilities from the IoT side to make sure that they have a very up to date understanding of the state of the engine; they’re also working with models where they can charge not only by the hour but for the actual usage and actual depreciation of the engine.

Engines in

Looking at this ‘engine as a service’ concept, a potential role for banks is ensuring that payments happen in real time within given thresholds and security limits set by the operator, removing the need for a build and measure model.  The car is an interesting way of looking at this because it is highly connected and there is a definite movement towards more vertically integrated business models on both the mobility and automotive sides.

In the future, a consumer should be able to buy a new car by creating a contract that states “I would like to operate the car and here are the conditions that I will fulfil” with most of the actual payment being based on the actual usage and depreciation of the asset, in this case the car. The change to the traditional leasing model is first of all, simplifying the value chain in terms of distribution, but also simplifying the value chain in terms of maintenance. The car manufacturer could theoretically, in the very same way as Rolls Royce managed for airplane engines, take over the maintenance and ownership of the car as the best possible entity to make sure the most lifetime value is derived from it.

The consumer can also be charged not only based on the kilometers that they have driven but also on other sustainable principles such as safe and economical driving. The safer and more environmentally friendly they drive, the less they pay, for example. This would not only be a benefit for the overall value of the car but also from a broader perspective, especially if the car manufacturer is interested in promoting safe driving, this is a very concrete way they could actually make that happen.

On the other side of that value chain, which is the other critical part of the business model, manufactures will be able to repurpose, refurbish and redeploy, possibly recycle, the cars in a very efficient way. So once the first life cycle of ownership is over, perhaps after three or five years, manufacturers can recycle or make some replacements to different parts of the car and then redeploy it into the traffic with a new contract in place. These are critical aspects that may support increased sustainability.

Common capabilities

Once a service has been defined, there is no reason to narrow the approach to any specific industry. In theory, the ‘as a service’ model could work for anything from cars to airplane and ship engines, power generators and anything form forestry to mining equipment. Our aim is to understand the common capabilities that actually allow these new ecosystems to work so that we can go to any industry and create this ‘as a service model’ and machine payment-based models in an effective way. We are looking at the common capabilities that we need to really unlock these future business models.

There are three different areas where banks should be able to generate revenue from these IoT based service models. The first area is the transactional payment capabilities or providing the basic ‘plumbing’ to make this happen. Here there are undoubtedly opportunities in making performance-based transaction revenues through processing machine to machine payments.

The second revenue generating area may come from financing the machine economy. Moving into service-based models requires new kinds of thinking in the financing space as well. It’s not immediately obvious for example on whose balance sheet these future assets will sit, as they’re being used for production. In our thinking, this capital risk could be distributed on a completely different scale compared to today’s models.

The third potential revenue track can be described as the predictive machine economy. It’s inevitable that the amounts of available data will increase as Industry 4.0 moves forward. Once we create a reliable and secure consent management mechanism for our customers to share selected data streams with banks, it may enable us to create predictive models for capacity and market demand on a macro-economic level. These insights could for instance be used on a practical level to help manufacturing customers scale the right amount at the right time.

This of course leaves many open questions when it comes to the accessibility of customer data and making sure that the customer knows how this data is being used. At least theoretically there are a lot of interesting opportunities out there and a lot of big questions for banks to solve. But it’s a journey!

For more information on emerging technologies at Nordea, write to Ville at Ville.Sointu [at] nordea.com (Ville[dot]Sointu[at]nordea[dot]com).