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Robotic Process Automation



Robotic process automation (RPA) is the use of software with artificial intelligence (AI) and machine learning capabilities to handle high-volume, repetitive tasks that previously requires human intervention. These tasks can include lookup queries, calculations and maintenance of records and transactions. Many companies are embracing RPA to eliminate tedious tasks, freeing corporate workers to focus on higher value work, streamline operations and reduce operating costs. RPA enables businesses to devote more time to serving customers and perform other higher-value work.

By 2020, automation and artificial intelligence will reduce employee requirements in business shared-service centers by 65 percent, according to Gartner, which says the RPA market will top $1 billion by 2020. By that time, 40 percent of large enterprises will have adopted an RPA software tool, up from less than 10 percent today.

"By 2020, automation and artificial intelligence will reduce employee requirements in business shared-service centers by 65 percent."

However, RPA has a downside and is not for every enterprise. As with any automation technology, RPA has the potential to eliminate jobs, which presents CIOs with challenges for managing talent. While enterprises embracing RPA are attempting to transition many workers to new jobs, Forrester Research estimates that RPA software will threaten the livelihood of 230 million or more workers, or approximately 9 percent of the global workforce. Even if CIOs navigate the human capital conundrum, RPA implementations fail more often than not. “Several robotics programs have been put on hold, or CIOs have flatly refused to install new bots” – McKinsey & Company, said in a recent report.


The global RPA market is expected to reach USD 8.75 billion by 2024, according to a Screen Shot 2018-09-07 at 12.19.13 PMnew report by Grand View Research, Inc. RPA is maturing in terms of clarity, credibility and applicability, as organizations are increasingly implementing these solutions.

RPA is emerging as a disrupting technology with capabilities of providing benefits such as enhanced accuracy, compliance, cost saving and scalability. As these tools are 65% less expensive than the full-time employees, industry experts have been expecting RPA to disrupt the conventional Business Process Outsourcing (BPO) model and alter the global outsourcing industry.


RPA technology was not introduced to replace humans, but to accompany their efforts and ease tedious tasks. Its wide-range of benefits are now becoming clearer.

In sectors like banking, finance, and insurance where companies regularly process large numbers of operations, RPA software can be used as a virtual low-cost worker to repetitive and mundane tasks. RPA can enable these businesses to meet security and data quality needs, whilst improving operational efficiency. In the retail industry, RPA can be designed to tackle fake accounts, update orders, and process shipping notifications. Similarly, for the telecommunications industry RPA can monitor CRM subscriber feeds, customer data updates, and fraud management.

So what does the future hold for RPA? The future of RPA should see an increase in the range of the robots’ functionalities:

  • Integrating more intelligence, while always making RPA more accessible and actionable by the users
  • Climbing the value chain to more cognitive: adding to RPA (which only “does”), the functions to “think & learn” and “interact” with the environment
  • Moving, in the longer term, to Artificial Intelligence (AI), including the ability to autonomously drive other robots. In a continuation of what we have seen in the second half of 2016, expected functionalities to be added to RPA will include:
  • Connection of RPA with data analytics systems (big data) to analyze actual data and predict future trends (e.g. share price trends): The robot is able to understand, think, decide and act (e.g. sell or buy shares) on the basis of the outcome of the analysis
  • Combination of Natural Language Processing (NLP) and cognitive: Virtual assistants (e.g. chatbots) able to interact with internal or external clients or operators, to facilitate their work. Chatbots will enable a better and faster adoption of RPA, making it more friendly and interactive
  • Combination of Natural Language Processing (NLP) and Machine Learning: Enabling the understanding of unstructured data received via text or pictures (E.g. unstructured data from incoming invoices using different formats). The robot is able to learn by itself through repetition, build patterns and understand new formats based on what it has learnt by experience
  • The robot will be able to learn by itself; solely through observing a human executing tasks on a computer, identify the tasks repeated regularly (e.g. daily, weekly), propose to robotize them by itself, and configure these tasks.


Technology is rapidly reshaping the way banks and financial institutions operate. Organizations understand that they need to invest in new disruptive technologies if they want to transform. The most powerful drivers of this much-needed transformation can be categorized in four C’s:

Customers: Tech-savvy customers expect differentiated digital experiences on the go

Competitors: To keep up with the competitive environment, adoption of disruptive technologies has become a mandate

Cost: The need to reduce cost using smart technologies and invest more in innovation and customer experiences

Compliance: Siloed data sources and paper-intensive processes demand speed and accuracy

To meet these needs and to successfully embark on the digital transformation journey, businesses require a strategic approach and that is where RPA will play the role of key enabler. Juniper Research predicts that the banking and financial services will represent 34% of the global RPA market by 2022.

RPA, the next wave of automation, is already being utilized by leading organizations to help address a slew of challenges such as frequent compliance changes and regulatory uncertainties, inability to adapt and build scale with legacy systems, higher error rates and constant pressure to deliver consistent user experiences across omni-channels. Time-intensive and manual processes are the best fit for core operations that can be automated with RPA.

It is predicted that robots could replace a significant portion of the current workforce. On average, the expectation is that 20% of Full-Time Employee (FTE) capacity could be provided by robots. This expectation matches the reality for those that have already implemented RPA.

KPMG estimates that by 2020, robo-advisors will manage $2.2 trillion in the USA. RPA technology offers promising business value such as increased security, reduced manual errors, costs and downtime, increased operational control, and most importantly freed up knowledge workers for customer facing tasks.


According to a Capgemini 2018 report “Unlike traditional automation, RPA has the potential to boost an insurer’s overall operational effectiveness with less investment, shorter cycle time, and higher short-term business value”