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  • Adam Levy

What Happens When Industry 4.0 Meets Finance?


The following keynote took place at an event hosted by Association Industry 4.0 Austria – the Platform for Smart Production on September 9, 2019, in Graz, Austria, where I initially presented in German and later transcribed the audio to English. 


My topic today will cover industry 4.0's intersection in the financial world. This is perhaps a topic that’s a little bit different from traditional industry 4.0 topics.


Still, the industry clearly shows that the financial world, for example, banks, insurance companies, and leasing companies, are currently being affected by the new business models that arise from industry 4.0 innovation. 


In today’s discussion, I will answer the following question: how will new machines be financed in the future based on data and industry 4.0 technology?



A little about me: I have been aggregating and transforming machine data into actionable insights for management ever since 2000.


My experience began when founding MIM.365, which is a manufacturing IoT platform for industrial companies or producers that have distributed production sites who need help monitoring KPIs and tracking in-house performance to help reach various business goals. 


My current experience in the space got me thinking. What else could I do with my IoT know-how? Who else could benefit from such data?


That’s when we, Paul Bruckberger and I, founded our current project, linx4, operating in the industrial fintech sector.


Throughout our market analysis, we noticed that banks and leasing companies have little information and access to machine data; that’s why we founded linx4.


So that machine data can be quickly and securely shared with third parties.



The background behind our use case overlaps into the sharing economy where SaaS models have become fully established and in high demand.


People only want to pay for what they use and, in many use cases, prefer pay-per-use models over traditional ownership.


In linx4’s case, we leverage a similar pay-per-use structure for financial products where debt payments are dependent on actual machine use.



So, who are the stakeholders here? On the one hand, of course, there is the machine manufacturer, the OEM, who wants to continue to get one hundred percent of his financing from the bank.


On the other, there’s the manufacturer who buys this machine and expects more flexible funding. 


And of course, there is also the point where industry 4.0 intersects with the financial industry.


Banks and insurance companies have very little technical know-how and experience collecting data from machines and interpreting the information to create actionable insight.





The pay-per-use structure has an advantage that unlike traditional financing, PPU does not align with rigid repayments where actual machine usage isn’t taken into account, instead, the financing structure depends on a variable rate.


linx4 depends on how productive or how high my equipment utilization was for the previous month.


Once discovered, the repayment financing rate is then calculated in terms of upper and lower limit machine utilization; this is the overarching idea behind pay-per-use financing.



We at linx4, as IoT experts, see ourselves as enablers for this use case.


Why? Because financial institutions hardly have any knowledge about machine data acquisition and its processing.


For example, if you talk about two to three machines, then there might be an individual solution. 


But financial institutions want to enter new markets and maximize their dominance.


In their case, we are talking over five hundred thousand machines that can be financed by pay-per-use.


Of course, there is the problem of different machine manufacturers and different technologies.


A financial institution couldn't deal with such technicality, that’s why they need a platform backed by IoT experts who can record this data, process it, and then pass it on.


linx4 is a one-stop-solution for solving this scalability problem.


That means we have the secure connectivity and the know-how to capture this data. Of course, we store this data, but we also validate it as well.


So this data, which then also generates a financial repayment, must, of course, be valid and secure to be considered authentic.


And here we have the logic for comparing the accuracy of this data.



Also, the data must then be automatically forwarded in certain business cases to the correct users of such data.


So basically, our platform captures, stores, and validates this information securely and then transfers the valid data to the appropriate participating parties.


Our platform also provides tools to monitor the repayment rate with its calculated upper and lower limits.


How far in advance is the repayment planned? Does this meet monthly expectations? As a result, financial institutions gain a lot of insight into the actual use of the machine to conclude; for example, how's the customer doing overall?


By knowing such critical information, financers can minimize the risk of future investments.


For our model to successfully work, both the OEMs and financiers must work together to gain a mutual advantage.



So the main advantage for an OEM is clear: you can offer your buyers alternative financing options.


As a result, you increase machine sales because certain investment hurdles for the buyers is removed.


As for the buyer itself, the desirable switch from Capex to Opex occurs, which also optimizes their cash flow.



On the other hand, financial institutions benefit by expanding their customer reach all the while achieving more profit.


And the same goes so far that even third-party investors may take on more risk with partial financing, as they too have the opportunity to earn higher returns.


So, one could argue that this business model is a win-win situation for all stakeholders:


For the OEM, the machine buyer, and the participating financial lender.


We have already implemented a wide variety of past and on-going projects in the IoT sector with substantially recognizable clients too.


In the pay-per-use area, we've been able to win some industrial customers here in Austria and also partly already in Germany.


We collaborate with network partners.


Above all, Erste Group, as our financing arm, sees the potential of new business models in digitization and recognizes the massive opportunity growth of new markets arising from such pay-per-use concepts.


So that concludes my discussions, that was the overview of the business model industry 4.0 meets finance in a Pay-per-use case study.


About linx4 - Industrial IoT Fintech


Backed by over 15 years of IoT expertise, linx4 helps OEMs sell more machinery by providing equipment manufacturers with the most secure data management platform for adopting usage-based financing and accompanying pay-per-use models. Our end-to-end encrypted solution permits secure data sharing with third parties worry-free and without compromising information quality. Industry-leading financial and insurance partnerships position linx4 as the industrial sector’s risk-free provider for pay-per-use digitalization.


linx4: Your one-stop usage-based financing and data management solution.


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