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Robo Treasury: Positives and Pitfalls RPA is a concept that is beginning to make waves in the treasury industry, delivering countless efficiency benefits and helping to automate tasks that were previously highly manual. But, how can treasurers get the most out of this new technology?

Robo Treasury: Positives and Pitfalls

Robo Treasury: Positives and Pitfalls

By Eleanor Hill, Editor, TMI


Robotic process automation has the potential to be a powerful tool for treasurers – especially those looking for new ways to garner efficiency gains. What’s more, as a relatively easy-to-deploy technology, RPA can deliver significant value in a short timeframe. But is RPA really a silver bullet for treasury? We ask four industry experts for their opinions.


Whether you’re an R2-D2, RoboCop, or WALL-E fan, stereotypical movie views of robots aren’t helpful when it comes to discussion around robotic process automation. Unlike the all-singing, all-dancing robots of science fiction, RPA is simply an automated rules-based software that executes pre-programmed tasks.

Nevertheless, RPA is making waves among the treasury community. According to PwC’s 2019 Treasury Benchmarking Survey, 47% of treasurers believe RPA will be either relevant or highly relevant over next two-to-three years. The survey also identifies interesting use cases for RPA – ranging from payment execution to accounting and management reporting (see fig.1).

 

Fig 1: RPA Use Cases

Fig 1: RPA Use Cases

Source: PwC Treasury Benchmarking Study 2019

 

While the opportunities around RPA are significant, there are limitations to consider as well. To get a balanced view on all of the RPA arguments, TMI gathered together the following experts for a roundtable discussion:

  • Séverine Le Blévennec, Senior Director, EMEA Treasury, Honeywell 
  • Roger Comins, Director of Product Management at GTreasury
  • Steven Lenaerts, Head of Product Management – Global Channels, BNP Paribas
  • Jasmin Ng, Head, Group Cash Product Management, Global Transaction Services, DBS


Eleanor Hill, TMI (Hill): Let’s start with the basics. How would you define RPA?

Steven Lenaerts

Steven Lenaerts
Head of Product Management - Global Channels, BNP Paribas 

Lenaerts: Basic RPA is essentially using software to create a certain level of automation for a repetitive process that is currently not digitalised or automated. That piece of software is referred to as a ‘robot’ or ‘bot’, but, of course, it is not an actual robot – that’s a common misconception.

The robot captures and automates these repetitive actions, typically to unlock legacy infrastructure and to connect the dots between different systems. It’s important to remember, though, that RPA can be combined with other technology to increase its level of intelligence.

Comins: The important difference between RPA and traditional automation tools is that it operates extremely well across the multiple systems that a human employee would use in their day-to-day. For example, RPA offers integration with email, Excel and PowerPoint, as well as browser automation.

This means that RPA can string together all of the information and processes that a human employee would need to perform a defined task – but in a much quicker timeframe. If you get RPA right, it can be like having a digital employee.


Hill: Could you outline some of the potential use cases for RPA in treasury?

Le Blévennec: Treasurers can use RPA in many different ways – at Honeywell, we currently have 48 different processes in mind to apply RPA to. One of the most successful RPA projects we have live optimises the intra-day cash forecast of the in-house bank. And I believe that all types of cash forecasting could potentially benefit from RPA, provided that structured data is available.

To explain more about what we have done here, Honeywell has 162 bank accounts that directly impact the EUR and USD balances of the in-house bank. By leveraging RPA, we can see during the day which cash has reached a source account in a particular country and which funds will reach the in-house bank later in the day.

Séverine Le Blévennec

Séverine Le Blévennec
Senior Director, EMEA Treasury, Honeywell

Because we have this early visibility over funds, we can actually invest cash before it hits the in-house bank. This means that when performing our investments, we take into account every flow that hits any of the 162 bank accounts until our investment cut-off times. In the past, as we were manually tracking the data, we could only consider 40 out of the 162 bank accounts because we physically didn’t have enough time between the transactions occurring on a source account and our investment cut-off times. We also use the bot to perform reconciliations for the in-house bank, looking at the funds that were expected to come in and the amounts that actually arrived, as well as any breaches.

We also plan to use RPA to help with compliance monitoring and ensuring data integrity in our systems. For example, we have been doing a clean-up of our databases as part of a TMS re-implementation and as part of that process we have introduced some reports that detect any anomalies in our database. If an anomaly is detected, defined rules will allow the bot to clean up the anomalies where possible. Of course, there are exceptions that require human intervention, but a significant proportion of the workload will be taken on by the bots. Automation will also enable us to increase the frequency of the data audit.

So, when deployed properly, RPA can significantly raise treasury’s productivity. Using a bot takes away the boring, repetitive work from the treasury team – and bots will work 24/7 without getting tired. As such, we schedule many of our bot processes to run throughout the night, so that when we come into the office in the morning, all the information we need is already prepared.

Ng: In the past, we’ve seen treasurers using RPA for recurring, scheduled activities, such as management reporting or cash flow forecasting. Essentially, treasurers have been using RPA to extract information from different reports or different systems – whether revenue or expense-related – and to aggregate that data. 

 

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