Investment banks are currently in the eye of a perfect storm, facing the conflicting pressures of reducing margins and managing ever-increasing compliance requirements.
Despite many years of investment in technological solutions to improve efficiency and decrease costs, full automation is still a pipe dream. Many challenges have emerged, including incomplete upstream data feeds, poor quality reference data, multiple golden sources of data, evolving regulation and legacy IT infrastructure that is often tactically updated rather than strategically reviewed.
As a result of these process shortcomings, organisations require multiple manual workarounds to maintain controls and quality. Recognising this, firms are exploring new ways to innovate, most notably through robotic process automation (RPA). But is RPA worth the hype?
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Investment banks dedicate significant amounts of labour to perform repetitive, rule-based efforts and operations. These processes, such as managing data exceptions and data entry, are unique to each organisation because the front-to-back connectivity sophistication varies significantly from firm to firm and function to function. RPA can add value by automating those repetitive duties and focusing a staff’s energy and attention on more strategic and fulfilling tasks.
RPA effectively provides firms with a digital workforce of software robots that is cost-effective, efficient, productive and scalable and can often be applied within weeks rather than months. Robots work 24/7, 365 days a year, without a break, bringing some significant productivity gains. Robots are not susceptible to fatigue or human negligence, which means fewer error corrections. They will not make biased decisions based on personal inclinations or pressure from managers and auditors.
The goal of process automation RPA is to automate repetitive and labour-intensive efforts, in order to increase operational efficiency and decrease operational cost. Typically, this type of RPA is applied on top of traditional operations IT systems, such as a content management system (CMS) and business process management (BPM) platform, extending their automation capabilities. Process automation RPA will further speed up certain back-office work in finance and operations like data entry.
Applying RPA in the real world
Investment banks still dedicate significant amounts of labour to perform repetitive, rule-based efforts and operations, such as managing data exceptions and data entry. These are unique to each organisation because the front-to-back connectivity sophistication varies significantly from firm to firm and function to function. RPA can add value by automating those repetitive duties and focusing a staff’s energy and attention on more strategic and fulfilling tasks.
RPA is also ideal in situations where a data entry conduit is mandatory. Some legacy platforms require the data to be entered or actions to be conducted via the user interface in order for it to be processed. In these scenarios, RPA tools can synthesise the actions of the user and mitigate the need for manual intervention.
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As with the introduction of any new software product, RPA comes with challenges. Time must be set aside for the adaptation and stabilisation of the newly adopted platform. Organisations must carefully plan the introduction of RPA due to the low level of standardisation across the enterprise and a number of proprietary in-house processes.
It is important to note that RPA is also likely to be affected by a quickly changing technology landscape and will require updates and bug fixes. It is also highly sensitive to any changes in the user interface (UI) on which it operates, so any changes to the UI must be communicated to the owners of RPA and all changes are tested to ensure the RPA does not break upon the production release of a new UI.
Other potential challenges include limitations with existing infrastructure, automation and data ingestions. RPA will successfully automate a process performed by humans, but it will not magically resolve data quality issues or existing platform limitations. If a process is fundamentally flawed or broken and this is converted from human-owned to robot-owned, the underlying data quality or connectivity issues that existed in the old world will also exist in the new.
Further, many RPA tools cannot process 100 percent of data formats. Firms may be required to build adapters using technologies such as C# or Java in order to transform such data into a readable form for the RPA tool. If this is the case, firms should perform the necessary cost-benefit analysis to ensure the effort required and any essential adapters would not be better spent on the implementation of full straight through processing (STP).
Just as the industry landscape for operations has evolved significantly over the past 30 years, so has the need for a far more efficient and controlled approach to covering inadequacies in the front-to-back trade lifecycle. RPA provides a solution for the management of repetitive processes that is cost-effective, efficient, productive and scalable and can often be applied within weeks rather than months.
However, RPA by itself should not be seen as the answer. It is, in essence, the next evolution of an interim solution for investment banks, and firms should always seek to ensure that they do not lose sight of implementing strategic change. Optimisation and synthesisation of front-to-back infrastructure will help close control gaps and eliminate many repetitive processes. This should continue to be the ultimate goal.
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Where the application of RPA becomes very interesting, however, is when it is combined with more advanced, cognitive artificial intelligence tools to deliver intelligent process automation (i.e. robotic automation that not only processes pre-programmed functions, but also makes autonomous decisions using a sophisticated rules engine based on learning algorithms).
While many traditional technologies are still not advanced enough to fully automate processes with complex decision-making, the application of tools that learns and thinks, as well as do, opens up a myriad of new automation possibilities.
To evaluate RPA and its viability within the business, firms should look to answer the following three questions:
1. Is RPA the only answer? While it is true that many legacy operational processes cannot be easily automated via existing software, there have been cases where operations departments have sought to apply RPA to processes that could be fully automated using available industry platforms or even existing tools within their in-house technology suite. It is crucial that firms conduct the necessary due diligence before embarking on the RPA route.
2. Can RPA cover all in-scope use cases? Some RPA tools struggle to cater to all data formats. It is vital that the right level analysis is performed to mitigate the risk of building technology on top of technology.
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3. Is the process being managed via RPA mandatory? If the answer is “no” and RPA will be used to cover a control gap inadequacy in the front-to-back infrastructure, firms should, in parallel with the definition of the business and functional requirements for the RPA implementation, produce a roadmap for how the process can be eliminated altogether.
In summary, RPA can be extremely useful for increasing control, improving efficiency and reducing cost if it is applied in the right way. However, before implementing it, firms should perform the right level of upfront analysis to ensure that significant benefits will be realised for the short, medium and long term.
Sourced by Nick Fry, director of Sapient Global Markets and its lead post-trade subject matter expert based out of London and Lukasz Hassa, manager of Sapient Global Markets based in London, with experience in middle-office operations, trade lifecycle management and enterprise data in the capital and commodity markets
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