How RPA can benefit banking and the public sector
Robotic Process Automation (RPA), an increasingly popular technology, can reduce costs and boost productivity, accuracy, data analysis and decision-making. Experts at convedo share how RPA can benefit two large sectors – banking and the public sector.
Widely seen as a major enabler of organisational transformation, Robotic Process Automation (RPA) denotes a process that utilises software programmed to autonomously carry out basic tasks across applications, reducing the burden of repetitive, simple tasks on employees. The cost effective process is able to be developed and deployed in the space of a few weeks, and can typically demonstrate returns on investment within a matter of months.
Thanks to these factors, RPA has been known to dramatically improve the speed and accuracy of processing, resulting in a quicker and higher quality service for the public. Unsurprisingly then, RPA has been recognised as the fastest growing segment of enterprise software with 63% growth in 2018 according to a poll by Gartner. However, while RPA continues to gain traction globally across various industries, it is not appropriate in every business case. Careful consideration needs to be exercised in ensuring that’s it’s not a one size fits all approach.
RPA is ideal for businesses fitting three broad criteria. This firstly includes those based around manual work, including any process which requires data entry, collection of data from various systems or even validating information across various internal or external websites. It is also well suited to repetitive roles, typically involving data entry and consolidation-type processes. Finally, RPA is better leveraged in mature sectors, as if the implementation process does not follow an efficient path, any return on investment will be diminished. Two main industries fitting these criteria, where RPA has clear benefits, are banking and the public sector.
Banking
The banking industry is exploring the potential of RPA in order to break down larger jobs, and reduce human-induced labour. RPA has already proven to be efficient in handling work overflow in this way, as well as tasks involving heavy data.
One example of the use of RPA in the banking sector includes collecting and validating customer data for Know Your Customer (KYC) – which has placed a huge regulatory burden on banks, and incurred a big overhead for financial companies as a result. RPA can reduce this by automating the collection and verification of customer data against internal databases, external systems and other criminal record checks. This can help reduce the time for verifying each customer’s identity and improve customer service.
Following on from this, automating the process of on-boarding a new customer can save time, money and improve the customer experience. Leveraging RPA in a retail banking scenario to collect information from the customer, and provide data to the customer service executive in the bank can help consumers with a decision on opening an account, approving a loan application, conducting the credit checks and more.
RPA has also been used to automate anti-money laundering checks, and automate invoice processing. The implemented combination of Optical Character Recognition (OCR) and RPA technology to automate the end to end invoice processing. Robotics can also be used to manage exceptions and human assistance can be brought in as optional if you still wanted some exceptions to be dealt by humans.
Public sector
RPA is a game changer when it comes to the automation of the public sector’s workload. According to the Reform, Work in Progress 2017 Report, in the UK alone, only 20% of public service employees do strategic work that requires analytical thinking. This is largely because of the huge number of labour hours instead put toward repetitive filing and admin work.
In response to this, RPA enables for digital transformation of various high-volume processes which underpin citizen services in the public sector. RPA can be used to automate processes that require processing documents received from people and processing the information, such as councils processing change of address forms. Robots can be trained to read the information from the documents received and change the information in internal customer databases. This can significantly reduce the time taken to respond to people’s queries, hence improve customer service.
At the same time, this can generate major savings for cash-strapped local authorities. By leveraging RPA to handle a variety of common tasks, local government can cut costs, and make workers more efficient and productive. For example, the North Tyneside Council in the UK expects to save up to £56 million over the next few years by bringing RPA into its workflows. Already, the council has used RPA agents to process customer service issues, improving speed and cutting data input times in half.
