This article was initially published in July 2018 and has been updated in August 2020.
Robotic process automation use cases have evolved during the past few years, to the point that you can now capitalise on your RPA investments with new use cases. You can now fully automate processes end to end, take advantage of intelligent automation, and scale your RPA deployment.
What does this mean for financial institutions?
- speed up compliance
- reduce costs and compliance backlogs
- increase operational efficiency
- eliminate manual errors
- automate unstructured data from emails, documents, and forms
- allow employees to focus on higher value tasks
Read on to explore some practical (and still current) real world use cases for robotic process automation in finance, and see software robots in action in two RPA demos. If you’re curious to watch more demos, check out our Youtube channel.
Of what use is robotic process automation in finance? Given the large amount of low complexity and high volume manual processes involved in finance (e.g., producing financial statements, card activation, account opening), it seems that automation might serve the industry well.
This is by and large right, but, as you can imagine, the truth is a little more complex than that. Moreover, with the recent RPA hype, we wish to advise you from the very beginning to keep a ‘critical eye’ so that you can safely stay on the reality side in the hype vs. reality match.
Recent statistics make such an over-enthusiastic outlook quite understandable. For instance, Horses for Sources reports that the global robotic process automation market — software and services included — had a boom of 63% in 2016–2017. And this was just the beginning.
Looking into the future, the same report envisages a compound annual growth rate of 36%, so that the market is expected to reach $1.2 billion in 2021. Genpact also foresees up to 50% increase in the productivity of companies which follow the automation trend.
For instance, a 2017 BBC article in the Technology section states that: “About 35% of current jobs in the UK are at high risk of computerisation over the following 20 years, according to a study by researchers at Oxford University and Deloitte.”
While embracing the potential of robotic process automation in finance, a wise executive who considers RPA implementation, should also bear in mind its limitations, e.g., the need to balance automation with human decision-making ability and other emerging technologies like cloud, big data, mobility, etc.
We also wish to recommend our favorite solution to keep your feet on the ground and not fall for the hype, while at the same holding on to the positive facts about automation: always mull over robotic process automation use cases.
Use cases allow you to learn the steps towards success ‘the easy way’, without having to deal yourself with potentially negative consequences. Peers’ real experiences in use cases provide the most useful learning environment, a sort of second order “learning by doing”, with the additional advantage that it saves you from erring yourself.
Robotic process automation use cases in finance
We believe that you need practical information to discern between wishful thinking (i.e., hype) from facts, so we will present you with 8 robotic process automation use cases in finance. These describe a successful trajectory of actions, from now to the time when the goal that you are set on will be presumably achieved with the help of software robots.
You can learn from here which processes in the financial industry are best suited for automation and why. This way, you can equip yourself with concrete plans towards attaining your objectives. As a result, your automation journey will unravel on more solid ground.
Before we start discussing specific use cases in finance, we should also mention that this article is the starting point in a series about RPA applications in various industries. In fact, here you can find more generally applicable, trans-industry, application areas, but we focus on finance for now.
1. Maintain data consistency
Customers’ details are constantly changing — their names, their addresses, or their credit scores. Software bots can use bank statements as reference points, extract the relevant data, and update records.
You probably know that robotic process automation drastically minimises errors, while saving human employees the effort to do data entry or data gathering (when more applications are involved in a process). Probably anyone who has ever worked in accounting, knows that the effects of errors can be daunting, but also that it’s quasi-impossible to avoid them when you have to spend neverending hours entering data.
In this case, automation can be seen as a win-win situation, both for the organisation and for the individual employee. From invoicing to accounts receivable, RPA can speed up the process, keep it error-“clean”, and, consequently, keep customers happy (and hence, more loyal).
Watch the tutorial: Robotic Process Automation (RPA) Demo: Invoice Processing
Executing finance and accounting processes, specifically accounts payable (A/P), poses a significant pain point for many businesses across various industries. Below you can see another demo of RPA in action in accounts payable.
3. Quick account opening
Banks need to play it safe and verify thoroughly customers’ details, such as identity, past credit scores, or their conformity with compliance rules. RPA can be of great help in the detail validation process by managing any encountered divergence. The new account is then created automatically by the software robot, and its details are delivered to the client. Nice and clean, right?
4. Streamline card activation
Request validation by checking the compliance rules, coordination between departments in order to keep data consistent, manual data entry, and so on. These are just some of the (boring, unexciting) operations involved in activating customers’ card. Before automation, such processing, usually done under time pressure due to customers’ (legitimate) requirements for fast results, used to be prone to human error.
Software robots, on the other hand, are not the least distressed by “come on, come on, I need my card, I can’t afford to wait any longer!”, and they simply don’t make mistakes. If, however, some inconsistencies arise, RPA can immediately address the department where the problem resides, and thus lead to much faster resolution. What do you get out of this? More satisfied customers and less tired and distressed employees.