Use Cases

Predictive Preventive Maintenance for your ATM Infrastructure

Background

The ATM Industry Association has predicted there will be over 3 million ATMs worldwide by 2015 – and that number is expected to grow significantly as financial service firms continue their march toward self-service customer enablement. While offering significant convenience to the customer, these ATMs represent a huge investment in physical infrastructure that involves both complex electronic components (screens, readers, boards, etc.) and physical cash balances that need to be maintained, purged, and replenished regularly for optimum ATM performance.

Challenges

Traditional methods of infrastructure management rely on replacing hardware components before they fail. Maintenance is handled on a strict hardware refresh calendar with components cycled out of service before they are “supposed to fail”, regardless of how well (or poorly) they are functioning. The difficulty with hardware refresh calendars is that they rely on statistical models for the “average” component life, rather than actual data on each component. As a result, many perfectly good components, with years of functional life left end up being replaced simply because the amount of time that has passed while failing components are left in place.

To get the longest life out of every component, requires that component are monitored and alerts issued as anomalies or errors occur. The ultimate goal is to utilize component analytics data to predict failures. It is hard to manage an extensive ATM network while looking only at historical data. True competitive advantage lies in continuous predictive real-time response to changes in your network. But, building a predictive real-time infrastructure with limited resources is both complex and cumbersome to maintain and continually improve upon.

Striim Solution

Our platform allows you to view your entire network of ATMs in real time to inform both your cash management and infrastructure teams of current and predicted anomalies and issues. Each component in every ATM streams data into the Striim platform creating a holistic, correlated, and aggregated view. Instant visibility into all ATM data across your network is correlated with history and context. Instantaneous predictive and prescriptive insights ensure that scheduled maintenance work is now focused on machines that are showing likely signs of failure. Distressed components are now automatically scheduled based on the criteria of the financial institution such as ATM productivity and risk of downtime.

Striim not only monitors hardware health, but real-time cash balances are also correlated with current, scheduled, and predicted events that will impact ATM activity. Holidays and unexpected events (e.g. the hometown underdog team making it to the Final 4 in March Madness… the bars are suddenly full and the ATMs empty) are correlated with rea-ltime ATM events to efficiently manage the cash demands in your network.

Striim offers real-time transparency like never before.

Benefits

The Striim platform provides increased ATM efficiency through the reduction of hardware and infrastructure downtime, as well as more efficient cash management (leading to lower treasury borrowing costs). Additionally, maintenance routes are optimized and components are no longer replaced on an arbitrary calendar, they are only replaced when they show signs of distress, ultimately saving money across the network by keeping functional components in service as long as possible.

Every aspect of your entire ATM network health can now be visualized in a single real-time dashboard that allows you to drill down deeply into actionable intelligence with unlimited drilling options.

 

Industry

  • Financial Services

Realtime Use Cases

  • Remote device management
  • Stream correlation and aggregation

Business Impact

  • Decreased operating expenses
  • Increased ATM efficiency and uptime
  • Network transparency
  • Efficient cash management
  • Increased data security
  • Won’t lose revenue, customers, or credibility

Data Source

  • ATM component health pingbacks
  • Enterprise ERP systems
  • IT infrastructure management systems
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