RPA in Finance


The use of robots to perform human tasks has been the topic of numerous science fiction movies over the last century, though anyone who’s witnessed robotics on the Robotic Process Automation (RPA) has enabled the motoring industry to improve product reliability, enhance the quality of the manufacturing process and drive profound changes in its ability to produce a car to order.

By using software that mimics the actions of humans, tasks can be completed faster, more accurately, and at a fraction of the cost.  The ever-increasing power of computing and evolution of smarter algorithms allows us to automate more and more of this activity.

Increasingly the line between RPA and automation in general is blurring. A more accurate, catchall title might be Intelligent Automation. Cognitive computing is expected to blur those lines even further as our desktop computers take over more of our routine tasks. For example IPSoft’s Amelia is a ‘virtual service-desk employee’ that learns on the job, can reply to email, answer phone calls and hold conversations. IT infrastructure support jobs – help desks, data centres - are likely to be some of the first to feel this wind.

The business benefits of RPA are undoubted. Robotics helps improve profit and loss by reducing errors, avoiding costly off shoring and providing rapid results within weeks. It also helps achieve operational excellence by improving quality and offering the ability to respond to changing business processes or handle increased volumes at marginal costs.

Furthermore, RPA helps a company leverage talent by giving employees time to innovate and focus on human centred activities such as customer service. Ultimately it gives business both the freedom and toolset to be creative and entrepreneurial. The things humans do best.
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Here are just a few examples of where RPA can help:
  • Pre-checking – run all case volumes through a process to perform checks, filter out the simple cases, let humans to do the complex work.
  • New systems with missing functionality – if a system can’t be configured to do exactly what you want (or is too expensive) use automation to deliver the work. More cost effective than throwing people at it.
  • Dirty interface – Gartner’s term for when lack of integration between systems means having to go through the user interface. In short, re-keying. Also true when input has to be provided to more than one system.
  • Multiple sources of data input – again, if a process requires input from multiple sources then it is suitable for robotic automation.
  • Manual checking, decisions and calculations – as long as these follow a rule set, then they can be automated. This is not about a technology that will take away our jobs, but a step change that frees us from mundane, repetitive tasks, increases our value and lets us innovate in new areas.
 

Telecommunications

A Fortune 200 telecommunications company engaged looking for ways to reduce the headcount of their 2,000+ call center employees. Given a specific headcount reduction target, the task was to set about performing the common activities one would expect for this type of engagement: After interviewing employees to determine the cost of process elements, looking to improve efficiency and reduce unnecessary steps whenever possible, and optimised the process overall. Unfortunately, although this did help in meeting the headcount reduction target, it did not fully achieve the objective.
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The next step was  then brought in Worksoft, which worked hand-in-hand with the consultants. Employees performed their normal day-to-day activities while Worksoft technology automatically captured the business process tasks they performed. The following automation assets were generated as a result of the work:
  • Process flow diagrams were created which automatically consolidated like paths and shared processes into a single flowchart view. Path segments performed by individuals or departments were automatically joined together to form an end-to-end process view.
  • A multitude of workflow statistics were captured and stored for analysis, including the number of clicks and specifically what was clicked for each part of the process, which applications were opened, the sequence in which activities were performed, the objects the user interacted with, and how the process varied across multiple users. Heat map overlays were applied including information such as the duration spent on each activity both in an aggregated and individual capacity, which helped to determine the cost per business transaction and of the overall process. When the process automation is run, statistics also include error information and system time to execute each part of the process.
  • Documentation was created detailing the exact transaction path each user took, including screenshots of each screen and button clicked, as well as what was entered, the objects the user interacted with, and a narrative of the process they performed.
  • Process automation was generated based on the actions users took throughout the system.
Using these assets as a starting point, the consulting company applied a custom heat map which matched every process step with the associated dollar value cost to manually execute the process. Analysts then easily identified which elements to automate first for the most effective return on investment (ROI). This helped them pinpoint not only what the company could do to fully meet their objective, but also what FTE reduction targets they could achieve for a subsequent contract they proposed to the telecommunications company.
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Automation helped the consulting firm deliver success for the company

insurance

While some speculate about what happens in insurance when these “bots” get so smart they make better decisions than human brains, others are getting on and implementing basic robotics solutions now.  These implementations are taking place at the simpler end of the spectrum getting machines to do some of the simpler tasks that the industry has traditionally done manually, often on an outsourced basis. This is referred to as Robotic Process Automation or RPA. 

In essence, RPA is desktop software that emulates the human execution of repetitive processes. A digital or virtual worker which can either sit alongside an existing workforce (Assisted Automation) so as to streamline their tasks and increase their efficiency or replace the existing workforce (Autonomous Automation) because they can be left unattended to perform specific tasks.

The inescapable truth is that while most of the insurance community are curious about technology innovation, they really don’t think that any of the buzz topics like blockchain, AI, IoT etc. apply to them, but the business case for RPA is different. It’s not about improved data analytics or customer engagement, it is about efficiency and cost savings. Some reports suggest it can save up to 70% on manual data entry tasks. The main reason for that is that they can work 24/7 and once fully trained the accuracy rate is much better than manual equivalent.

So, what is RPA being used for in insurance? The tasks where they are most often seen at the moment are:
 - Application migration – data migration as part of a system upgrade
 - Data entry - simulating user rekeying of data from paper or image to systems.
 - Information validation and auditing - referencing data sources to inspect and validate the information and provide compliant outputs
-  Legacy enablement - interfacing disparate legacy systems, doing data translation and rekeying where a full API or coded integration is not possible.

So, what has the experience of the early adopters been like?

Well, it is not just a case of downloading the software and off you go. Implementation is quite difficult and considerable investment in terms of time is required at the start to define inwards data formats, iteration so as to enable the robots to learn and accuracy to improve. There are also complexities around the configuration of the robots, how they prioritise, their hierarchy, spread the work and so on.

Accordingly, a separate industry has grown up around implementation with the big consulting houses to the fore again.  This has upfront cost implications suggesting that the cost benefits are rarely achieved within a year, but are of such magnitude in future years that it is usually worth persisting. Some complain that the levels of accuracy achieved are less than desired, but rarely less than they were achieving manually.

 Improvements in the self-service features of the RPA software is starting to bring down implementation costs so that you no longer require code changes to refine implementation. There is also an increase in the amount of AI meaning that the software’s ability to teach itself is improving too. It’s probably worth checking on the maturity of these two features when reviewing potential RPA vendors.

As you would expect, many of the early adopters are themselves BPO providers so in several cases tasks that you think are being performed manually are increasingly done by RPA.  There is a useful White Paper reviewing the Xchanging adoption of RPA with Blue Prism (which was over a year ago now) containing some useful myth busting insights - http://www.xchanging.com/news/xchanging-blue-prism-lse-outsourcing-unit-reveal-results-insights-paper-robotic-process
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So, when you next read an article about robotics and dismiss it as science fiction, bear in mind that some of your competitors are using it, and probably your BPO provider too!