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RPA for financial services – 5 steps to success

RPA for financial services – 5 steps to success

Jonathan Ebsworth, partner of the disruptive technologies practice at Infosys Consulting

Businesses in the financial sector could make a killing from automation; and if they implement it correctly, they could save themselves from incredibly costly human errors. UBS Warburg, for example, might wish they’d put a robot in the role of a trader whose ‘fat finger error’ saw the company sell 610,000 shares at six yen rather than six shares at Y610,000 as intended – a mistake that cost the company around $100m.

Humans and machines are both fallible, albeit in different ways. The key for financial services businesses is to learn where robots – in the form of robotic process automation (RPA) – can bring enormous value while lowering risk. We’ve already seen organisations making their first tentative steps in RPA by applying the technology to repetitive, rules-based processes.

There is enormous potential to bring RPA into other areas of finance; for example, in areas such as compliance, anti-money laundering activity, and Know Your Customer (KYC) initiatives. What’s more, RPA can bring huge cost- and time-savings by automating many of the tedious, process-heavy transactions such as account opening or customer service.

There is always the temptation of thinking that bots can replace entire sections of the workforce, but they are best suited to repetitive, manual, time-consuming and rule-based tasks; financial service enterprises that think they’re a substitute for skilled, experienced staff are in for a rude awakening.

As, indeed, are those who think that RPA is simply a matter of ‘plug-and-play’. There are plenty of misconceptions about bots, and one of the most overlooked areas is how they require a fundamental shift in strategic thinking if RPA is to solve current business challenges and deliver their full potential.

Missed opportunities 

Anyone who has had had to deal with a bot when trying to resolve a complex customer service problem will understand that RPA is a long way from replacing human workers. Yet in financial services, the large majority of customer service enquiries are strictly transactional – for example, sending money or checking a payment has been received. These are not queries that take an enormous amount of intuition or knowledge to resolve.

Recent research by Infosys Consulting on a range of intelligent automation solutions revealed that only 10 per cent of organisations currently using RPA or AI believe they are maximising their full benefits and capabilities. For example, a single RPA agent involves a one-off cost of between $5,000 and $15,000 – far cheaper than even the most junior employee. Failing to take advantage of bots represents a spectacular missed opportunity, and the reason is more often than not a lack of clear strategic vision for RPA, and poor understanding of the requirements for effective implementation.

We should all be tremendously excited about RPA’s potential; to achieve this, however, businesses must take a pragmatic and strategic approach to bots in the enterprise. Here are our five steps to RPA success:

  • Forget ‘like-for-like’ replacement

In our experience, bots are around three times more efficient at certain processes than an equivalent human worker, so it’s tempting to think that one bot can replace several existing employees. Yet it’s foolish to expect a bot to demonstrate the same lateral thinking, intuition, or problem-solving ability as a human. Organisations shouldn’t calculate their RPA strategy on like-for-like replacement, but must give careful thought to how bots and humans complement each other in various roles such as compliance, invoicing or customer service – as well as considering the costs of retraining, redeployment and sometimes organisational adjustment required.

  • Beware the business continuity risks

Bad things happen when organisations surrender too much responsibility to automation. Never is this truer than in the case of a disaster, when an enterprise needs staff who are fully familiar with business operations and their underlying processes. When a spade slices through a critical cable or floods deprive your premises of power, will the bots keep functioning – and will they have intelligence to understand how this disaster affects day-to-day processes? Business continuity questions like these are often overlooked, but should be at the heart of any RPA strategy.

  • Understand the security challenge 

Because of increasing security challenges across the workplace, biometric and two-factor authentication are becoming increasingly widespread. Bots obviously have no biometric data, and struggle with two-factor authentication. Financial services enterprises cannot reasonably allow automated processes to operate in a less secure environment than one that is human operated; they must therefore be alive to the potential vulnerabilities of RPA, and integrate bots fully into their organisational security strategy.

  • The impact on agility 

A tactical or poorly-planned RPA deployment can significantly reduce the agility an organisation has, tightly coupling automated processes to the underlying platforms. Automated processes can be quite fragile, sensitive to even minor updates to the core systems they drive. Bots and AI solutions at scale should be governed within the overall architecture framework that underpins the business, not as a stand-alone solution sitting outside of the enterprise architecture. 

  • Remember, it’s early days for RPA 

The tools across this space are developing quickly. Today’s winner will not necessarily be around in its current form in a year or two. Switching from one RPA vendor to another is difficult and expensive. The risk and consequences of new versions and new products need to be factored into your journey. The boundless enthusiasm for these technologies needs to be tempered with a little realism. The secret to success is knowing how to complement human activity with RPA, rather than have them compete. It’s crucial to establish a business rationale for each use case, to know exactly what errors you want to eliminate, and be fully aware of their impact on operations and organisational strategy. Only then will they deliver their full potential – and human workers will be assured of their continuing value to the organisation.

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