Did you ask Alexa about the weather this morning? Or tell Siri to fire up your breakfast playlist? Perhaps your smartwatch is tracking your activity at this very moment, while your doorbell cam keeps an eye on the home front. And each of those devices is harnessing real-time data that helps them work more effectively and efficiently.
These “connected,” IoT devices have become ubiquitous in our daily lives, from home to work to shopping and everywhere in between. In fact, Gartner expects the number of IoT devices globally to reach 25 billion by 2021[1]—that’s nearly four connected devices for every person on the planet!
Commercially, real-time IoT connectivity is quickly becoming just as prevalent. So-called “smart cities” lead the way in IoT implementation projects globally[2], and there’s already a new acronym to identify broader manufacturing-related IoT: “Industrial Internet of Things” or IIoT.
The Power of Connected Services
In the services realm, more connectivity directly correlates with improved service rates—and higher uptime for terminals and devices. Real-time, automated analysis of potential issues is driving predictive maintenance capabilities unlike anything our industry has ever seen. Organizations that have begun to explore the possibilities of connected devices and services have discovered how dramatic the results can be: in 2018, predictive maintenance initiatives saved businesses $17 billion[3].
Furthermore, Samsung illustrates the story of UPS, which, in 2010 (yes, nearly a decade ago!) installed over 200 sensors on its trucks to monitor actual performance, eliminating the “one-size-fits-all” approach to maintenance they’d used in the past[4]. That shift helped the organization maintain trucks at the optimum time, and led them to discover inefficient fixes—in one example, the company discovered that its mechanics were replacing fuel injectors when they could’ve simply replaced an O-ring.
Financial institutions (FIs) can benefit in similar fashion from tapping into real-time visibility across their self-service network at both the highest and most detailed levels: data patterns across the entire fleet can reveal usage fluctuations, while information about individual machines can drive appropriate maintenance. Not only does automation drive efficiencies, but the additional data being pulled from the fleet enables you to make better business decisions for your long-term strategic growth.
“Low cost sensors coupled with appropriate machine learning can not only detect maintenance issues, when properly tuned, it will also be able to identify when the ATM is visited without any interaction or when criminals try to insert a skimmer,” said Tim Sloane, VP of Payments Innovation at Mercator Advisory Group. “When done right, detecting security, maintenance and usage data via machine learning tools is the most effective approach and costs less that other methods.”
Yet many organizations in the financial industry continue to hold a risk-averse attitude toward cloud-based connectivity. Their most basic security instinct—don’t let the data out of the network!—hampers them from exploring new opportunities to grow their business and reduce costs.
If this sounds familiar, ask yourself: with the right precautions in place, might something positive happen if I DID supply my monitoring partner with information about my terminals?
Security Comes Standard
Connectivity has come a long way since a soda machine, “the world’s first IoT device,” (according to IBM), started spitting out data (and cold beverages) for Carnegie Mellon computer science graduate students in the early 1980s[5].
Today’s devices must operate more privately—and security is a paramount concern for any organization managing data in the cloud. When Diebold Nixdorf connects a self-service terminal to the cloud (whether public or private), the connection is PCI compliant. It’s fully encrypted and often far better protected from modern threat vectors than data sitting on a laptop.
Equally important, our proprietary monitoring tools ensure no consumer data is ever transferred from the terminal. Powered by DN AllConnect Data Engine℠, our services team streams and aggregates system data in a one-way feed from a terminal’s internal sensors to take faster, more informed actions that keep your ATMs up and running at the highest levels of availability. The data flows through your own networks before it comes to ours, ensuring you have complete visibility and control over your data.
“It is important to recognize that machine learning models become more accurate with more data and so collecting data from multiple locations enhances the model” said Sloane.
The Old Model is Gone
Ten years ago we could only dream at the technological advancements that have become standard fare for consumers and organizations alike. Modern financial institutions must take advantage of the opportunities that these new innovations offer, and tap into cloud-based connected services that can enable them to continue elevating the consumer experience and driving process efficiencies.
Gone are the reactive service days; we’re moving toward a proactive service model where real-time information enables us to execute diagnostics, conduct remote maintenance tasks and ensure the right tech arrives at the right time, with the right part, to fix a terminal as quickly as possible. Imagine a scenario in which your ATM doesn’t go down—because we’ve fixed the problem before it can affect your terminal. As the only vendor that has fully integrated actionable performance data into the very design of our latest ATMs, DN Series™, we have the capability to access data that can transform your entire network.
If you’ve ever Googled something, only to have an ad for that exact thing pop up in your email 10 minutes later, you’ve experienced the power of real-time data analysis. That speed is your “X factor”—with immediate data continuously monitored, failures and potential issues are spotted faster than ever before, driving downtime to ever lower levels.
Big data, machine learning and IoT were, until relatively recently, buzzwords to throw around at industry events, or worse, their own kind of vaporware. But today, they’re concrete, tried-and-tested approaches that are being applied to make meaningful changes, from the highest-ever end-user availability, to best-in-class customer experience and better opportunities to retain high-value transactions. A recent study from Statista found that 90% of senior executives across industries including tech, media and telecomm say IoT is critical to some of all of their business!
IoT is here to stay—and it’s not just for enterprise organizations. Whether your financial institution is a local credit union, a regional bank or a global player, this new services connectivity is leveling the playing field, enabling every FI access to the data they need to make better business decisions. The data is there—what will you do with it today?
Learn more about DN’s approach to connected services at DieboldNixdorf.com/AllConnect.
[1] https://www.gartner.com/en/newsroom/press-releases/2018-11-07-gartner-identifies-top-10-strategic-iot-technologies-and-trends
[2] https://iot-analytics.com/5-key-insights-from-350-smart-city-iot-projects/
[3] https://iot-analytics.com/numbers-of-predictive-maintenance-vendors-surges/
[4] https://insights.samsung.com/2018/11/21/3-ways-fleet-maintenance-is-using-sensor-technology/
[5] https://www.ibm.com/blogs/industries/little-known-story-first-iot-device/