Automate Banking ATM Reconciliations with RPA Bots

Regardless of your core system, you can now “park bots” on this tedious, time-sucking daily chore 

For every bank with an ATM network—and that’s all of them—there’s the daily chore of reconciling the transactions across its constellation of automated teller machines.  

You—or, more specifically, lots of smart people in your back office or Deposit Ops—need to reconcile lots of numbers. “Reconcile” is just a fancy word for “seeing if they match.”  

But none of this is simple. To the contrary, it’s exceedingly difficult, tedious, laborious, and prone to errors. Consider some of the steps:  

  • You’ve got to log into your core system and pull reports.  
  • Download files to Excel.  
  • Eliminate duplicates. 
  • Check transactions against the general ledger.
  • See what matches—and what doesn’t. 
  • Create and send out reports.

And make no mistake: Your bank’s staffers absolutely hate doing this work. It’s not even a question. It’s like being trapped in a circle of Hell in Dante’s Inferno.  

Automate your way to success–No matter what core application is used

When you think about all of the different systems that these workers must touch in the course of their reconciling day, you might think it’s impossible to tie them all together and automate them. After all, that’s why the people are there in the first place: The systems don’t talk to each other. Even different modules from the exact same core provider! Thus the required “human glue.”  

But robotic process automation, or RPA, from The Lab, changes all that. Think of an RPA bot as a very simple “person” who can “sit at a computer” and do all of those exact same tedious things that a human worker does every day. The bot can log into systems, with its own login and password. It can navigate portals and apps. It can filter for given date-ranges. It can select the data it gets. And then it can copy and paste it into to other applications, such as Excel, where it can manipulate it (including, for example, eliminating duplicate entries), and save its output onto a shared drive, even giving it a rational, custom filename. Other bots can even step in to email the output to the right people!  

We’ll get to even more of the bot benefits in a minute. But first, let’s address a question that’s surely on your mind by now:  

“How can this possibly work for our core system and our way of doing daily ATM network recons?”  

That’s a great question. Let’s answer it for you.  

“Custom” is the name of the game

Different banks have different ways of reconciling their ATM network data each day. On top of that, they employ different core systems, such as those from FIS, Fiserv, or Jack Henry. To which The Lab says, “No problem!”  

That’s one of the great things about RPA bots. They’re core-system agnostic. Remember: If a person can click their way into FIS or Fiserv, so can a robot.  

To illustrate just how seamlessly The Lab can do this for your bank, we’ve made a little video about it. It shows the exact same ATM network recon, being performed on three different core systems, at three different banks. Here it is; watch it for yourself:  

The FIS version

The FIS-based bot suite works like this.  

And we say “bot suite,” because, typically, there will be a few bots, working together as a “team,” handing off work from one to another, almost like a relay race.   

For the FIS-based ATM recons, it starts with the first bot, which:  

  1. Opens Horizon.  
  2. Navigates to the General Ledger inquiry, and then to the “Transaction History” screen.  
  3. Then it navigates to the ATM general ledgers, pulls the transaction history from the selected date-range, and downloads it. 
  4. At the same time, it opens the bank’s home page (via Internet Explorer—are you keeping count of all the systems being touched?), and navigates to Centrix Cloud DTS.  
  5. It then filters the Adjustment Transaction Report for the specified date-range, and downloads it.  

Now Bot Number 2 steps in:  

  1. It opens FIS Image Center (yep, another core product), and logs in, with its own user name and password—just like a person would.  
  2. It navigates to the COLD research.  
  3. It searches for, and then downloads, all Institutional Settlement Reports within the specified date-range.  
  4. It then writes the ATM Network Reconciliation to the appropriate folder on the shared network drive—even typing in a logical, unique filename.  

Finally, the third bot picks up the task, and emails the report to a pre-determined list of human recipients.  

There. Done. Impressive, huh?  

Even more impressive: This one bot suite saves 500 hours of labor annually.  That’s worth more than $18,000 of labor in a bank, year after year! 

ATM Recons, Fiserv- and Jack Henry-style

Same task—ATM network recons—but a totally different setup: Fiserv Signature and Nautilus, with a Lawson ERP (enterprise resource planning) used as a general ledger or GL. Yet bots from The Lab handle it with equal aplomb:  

The bots extract all the data they need from Lawson. Next, they log in and grabs the corresponding data from Fiserv Nautilus, and reconcile the Balancing Recap Report against the GL, line-by-line—just like the deposit-operations worker would.  

Want to see how it works for Jack Henry setup? The steps go something like this:  

  1. The first bot opens and then logs into the Jack Henry Symitar core.  
  2. It searches for the GL account 
  3. It navigates to, and then extracts the ATM transaction history data. 
  4. The next bot then searches for and pulls the ATM settlement and exception data to be balanced.  
  5. It then processes all the data, in the background.  
  6. Bot Number Three then writes the balancing report for the specified date-range, saving it to a network drive.  

Where humans fear to tread

So far, we’ve said that bots can do everything that people do. They do it faster. They don’t take breaks, get tired, or make mistakes.  

But there are also things which bots—such as these ATM network-reconciliation bots—can do, which people won’t, can’t, or don’t want to do:  

  • What happens when a bot tries to log into a system that’s unresponsive? It has unending patience. It waits a pre-determined amount of time, then tries again. And again. And again. Until it gets in. And if it doesn’t, it helpfully emails its human “supervisor” with an update.  
  • Humans don’t like to work late nights, early mornings, or weekends. But bots don’t care. Which is why The Lab often puts them on schedulers. They simply run in the morning, so their work is done by the time the humans arrive. Or they’ll work late at night, when network traffic is slower.  

Book a free Demo to see Bottom-line benefits for yourself

As we’d hinted above, ATM-reconciliation bots from The Lab are a case study in ROI. Consider the numbers:  

  • It takes a person one to three hours to do a single daily recon. The bot does it in anywhere from four to 15 minutes. That’s 15 to 45 times faster.  
  • Humans generate an 11-percent error rate. For the bots, it’s zero!  
  • ATM recon bots can save you 25 percent of the cost for this daily reconciliation in Year One, and 75 percent every year thereafter! 
  • The Lab creates bot-suites like these in just three to four weeks—remotely, from our offices in Houston! Nothing is outsourced or offshored.  

It’s one thing to read about RPA for ATM-network reconciliations.  It’s another thing, entirely, to see it in action, in a real, live demo. So get one! The Lab invites you to schedule your own, no-obligation 30-minute screen-share demo, in which we’ll show you all this power at work, and answer any questions you may have. (We have more than 800 banking bots, ready-to-deploy!) Simply call (201) 526-1200 or email to book your demo today! 



For 2021: We have updated our bank client offering. Much of these findings and implementation results can be reviewed in the 3-part-series of “Big Rocks for Banks” below. Find out how to strategically lower costs, increase operating leverage, improve customer experience, and automate what previously wasn’t automatable in your bank.

Find them all here:





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