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Exploring the future of RPA and the specific use cases with the financial sector

Exploring the future of RPA and the specific use cases with the financial sector

By Tarja Pitkänen, Head of Banking and Insurance at Digital Workforce

The financial sector was the first to benefit from Robotic Process Automation (RPA) in automating rule-based and repetitive business processes and tasks that human employees performed. In the past five years, many financial services companies have gained significant cost savings, improved customer experience, shorter throughput times and increased competitive advantage. How does the future for RPA in the financial sector look?

When Klaus Schwab, founder and executive chairman of World Economic Forum, published his book “The Fourth Industrial Revolution”, he has said that intelligent automation (IA) is a central component of this revolution. Intelligent automation is an umbrella term for various technologies (RPA & AI) that can be utilized together to automate processes.

According to Gartner, “RPA is the fastest growing market in enterprise software: by using RPA, organizations can quickly accelerate their digital transformation initiatives, while unlocking the value associated with past technology investments”. RPA market is forecasted to grow at double-digit rates through 2024 despite economic pressures from COVID-19. Also, HfS and KPMG have conducted CIO research, where AI and RPA are the top of mind investment areas. RPA provides a cost-effective and quick tool to build interoperability between applications and automate and streamline end-to-end processes.

The role of RPA will increase in the financial sector

Tarja Pitkänen

Tarja Pitkänen

To give concreteness to these estimations, I share a few use cases. RPA is a proven, mature technology for financial institutions, which has helped them automate also critical business processes. However, the role of RPA is expected to increase when application vendors constantly bring more advanced features to their solutions. For example,  RPA bots are augmented with AI and ML components to allow more human-like features, allowing companies to automate more complex end-to-end processes instead of individual tasks. And we should not forget other application vendors that have also introduced and will introduce intelligent solutions to the RPA ecosystem. Financial institutions have also started to automate customer service or front office processes in scale with attended automation tools. Citizen development (non-professional RPA developers who automate small tasks specific to their roles) will grow, but the role is still unidentified.

It is also essential to mention the COVID-19 epidemic, which is driving process automation as a part of digital transformation. Especially lockdowns in lower labour cost countries and remote work have increased organizations’ needs to ensure business continuity. The post-COVID-19 period will accelerate digital transformation and thus the need for RPA.

One business area where RPA has helped financial institutions to improve customer satisfaction is mortgages. Reducing the handling times from weeks to few minutes and reducing the operational costs has led to happier customers. Last year at this time, financial institutions were busy automating Covid 19 related processes. Some banks could automate processes related to Covid 19 mortgage payment holiday in less than two weeks by utilizing RPA combined with advanced analytics. Fast automation was the only reasonable option to solve the sudden peak in demand. Even smaller banks needed tens of bots 5 to 10 times faster than human beings to handle the situation.

Part of the future RPA growth comes from those financial institutions which have not yet properly started their RPA journey or have started but are focusing on task automations instead of end-to-end process automations and utilization of several technologies. They can hardly afford not to follow their most advanced competitors.

From a traditional financial institution to a modern tech company

There are many task automation use cases, like transferring data from an online application to a legacy system or mortgage offer creation.  Adding other Intelligent automation tools like Business Process Management to combine process orchestration between the front office and back-office and introduce a virtual workforce or leveraging OCR and Machine Learning to take structured data from paper-based documents are some examples of end-to-end automation use cases delivering high value for the organizations.

Some financial services organizations have a self-service digital platform leveraging intelligent chatbots combined with RPA, which has provided high value, especially in the card business. During a chat conversation, the end-user can, e.g. order a new card, request a PIN code or address change, and close cards, all of these transactional tasks can be completed in the backend systems by RPA bots.

Other areas where intelligent automation is influential within the financial sector include analyzing historical customer transactions and behaviour related, e.g. to bank transfers, card transactions, or cheques. RPA bots can give the customer the correct risk scoring and identify unexpected and unusual client transactions to create necessary alerts. In case of detecting fraud, evidence like forms and police reports can be collected and archived. Companies can also use the data collected for KYC purposes to find new sales opportunities, e.g. in the annual customer meeting.

The transformation from a traditional financial institution to a modern tech company won’t happen without the support of RPA.  RPA is a powerful tool to support structured data conversions that systems cannot do automatically. By adding intelligence to the solution and utilizing AI, you can also transfer free formatted text from the old legacy system. New highly standardized legacy systems may require that new tasks are completed, which takes time but doesn’t create any new value – an ideal use case for automation.

Global Banking & Finance Review


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