We already know that the financial services sector is set to become one of the largest adopters of ‘intelligent automation’. To give one example, when HSBC announced its major transformation project in June 2015, two numbers stood out. The bank announced that headcount would be reduced by 25,000 – about 10% of its global workforce – by the end of 2017 and it would spend US$1bn of its US$4.5bn transformation warchest on “accelerating digital and automation programmes.”
HSBC is far from being the only financial services group reaching for automation as a weapon in the fight to preserve profitability in an increasingly margin-pressurised environment.
Financial institutions need to overcome costly and cumbersome legacy IT architecture, provide better customer service and deliver an cleaner experience for all employees. Intelligent automation – using robotic process automation (RPA) as well as more advanced cognitive systems and artificial intelligence (AI) – now offers them a way to drive cost out of a huge variety of processes, without totally reinventing their business model or redesigning their IT infrastructure.
Robot software sits on top of existing systems; effectively replicating human inputs and outputs. That means discrete processes can be automated quickly and without changing underlying transaction systems – making it ideal for delivering fast results. A great example is BNY Mellon which uses “bots” for a variety of processes. Senior executive vice president (EVP) Doug Shulman told American Banker magazine that it took a human five to 10 minutes to reconcile a failed trade. The bank’s bot can do it in a quarter of a second.
Automation isn’t just driving cost out of the back office, either. The use of algorithmic trading systems is well established in investment banking, with Royal Bank of Scotland (RBS) the first to announce the use of ‘chat bots’ to engage with customers in place of a contact centre. Other banks are using voice digital assistants (VDAs), virtual agents and natural language processing (NLP) to pick up programmable tasks, freeing up people to focus on exceptions, analysis and creative tasks.
A long, long time ago…
Although RPA and other “intelligent” technologies are relatively new, their attraction for financial services organisations is rooted in two related factors. High transaction volumes mean any automation at all delivers meaningful efficiencies; while long-standing banks, insurers and asset managers are stuck with old underlying systems (in a way challenger institutions are not).
Throwing ever-increasing maintenance and development resources at legacy systems is not cost- effective – and won’t build either the infrastructure or a culture capable of continuous improvement. Financial services businesses want to embrace digital transformation to keep up with new market entrants (challengers), low returns and increasingly demanding customers.
Intelligent automation, unexceptional intelligence
Intelligent automation tackles these issues head on. From a systems point of view, intelligent automation can be a way to effectively connect legacy systems with modern tools. These systems replicate human processes, which means they will also map perfectly onto wholesale infrastructure.
Because they are designed to be learning systems, the volume of transactions is a huge plus because they learn faster. Furthermore, large numbers of transactions mean even where the automation is limited to non-exceptional cases, there is still a massive reduction in human interventions. As Oxford University fintech expert Nguyen Trieu said: “In all types of banks you still have millions of processes in which a similar task is repeatedly executed. The major trend will be going back and seeing which of these processes can be digitalised and automated.”
With the automation of these straightforward and repetitive ‘swivel chair’ tasks, financial services firms can redirect valuable human resources toward supporting key internal initiatives or programmes that aim to deliver exceptional customer experiences.
A robotic approach to automation
RPA is typically the starting point for the automation journey, then. Successful banks and insurers don’t look at the technology first, however. The key is identifying the right processes to automate. Here are some key questions to ask about a candidate process:
- Is it well defined and documented? This will accelerate robot design and identify processes with built-in inefficiencies that ought to be eliminated before being automated.
- Is it rules driven? Robots are getting better at learning, but clearly-defined rules are more easily mapped into software.
- Is it complex? Human intervention in complex-yet-uncreative processes often introduces errors robots will avoid.
- Can freed up employees be reassigned? The best case scenario is humans bring their fuzzy, creative, problem-solving skills to bear speeding up the handling of exceptions, for example, or adding value elsewhere in the business.
- Does it create options for further automation? Grouping processes around a workflow or platform creates low-cost opportunities for extended automation projects.
Many companies start with a proof of concept (POC) to see how the technology works and estimate the impact in their business. Typically they’ll automate a task or sub-routine of a higher-level process, such as retrieving and passing information from one system to another. Financial services businesses are often grouped around product or system platforms, and successful automation of one part of the process often flags up dependent processes for future stages of automation.
Supporting and connecting the digital transformation programme
Like any new technology or process, automation must deliver results. The beauty of RPA for financial services firms is that a process can be automated in a few weeks, while the results in terms of completed transactions and freed-up human resources is visible immediately. That’s in stark contrast to the typical core system transformation projects that take years to map out, much less execute. Yet the incremental improvements to process design and efficiency that RPA introduces also helps these firms to re-invent themselves.
Today’s digital consumer has ever-greater expectations. He or she wants personalised customer service, delivered fast, and they want to receive it via the channel and device of their choice. New challengers in financial services start with this as their credo. They are making life easier than ever for customers – and at lower cost to themselves.
That means financial services institutions cannot wait for wholesale digital transformation projects to bear fruit; and further tinkering with legacy systems will add cost and complexity to those systems.
Intelligent technologies offer a very cost-effective way to address both process design and market demands that will allow frontline staff to focus on value add, not drudgery; IT resources to concentrate on long-term wholesale digital transformation; and management to fix processes that hamper outstanding customer experience.
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