Banking RPA and AI: The next step in the bank efficiency game to deliver a better customer experience

Banking’s future is to adopt Robotic Process Automation (RPA) and Artificial Intelligence (AI) to better customer experience. To remain competitive in an increasingly saturated market— particularly with the more widespread adoption of virtual banking — banking firms had to find a way to provide their customers with the best possible customer experience. Internally, there was also an increase in the challenge of maximizing efficiency and keeping costs as low as possible while maintaining maximum safety levels. For years, banks have been looking for cost-reduction strategies. Robotic Process Automation (RPA) is a powerful and effective tool to reduce costs and move from service-through-labor to service-through-software to respond to these demands.

Since the introduction of RPA into the financial services world, virtual workforces have helped banks minimize (or, in many cases, eliminate) human intervention in task and decision-making and dramatically improve operational effectiveness, at times up to 70%. Companies like Ntansa are working with customers by shifting most of the manual tasks, tedious, from human to machine.  As a result, banks have been able to reduce the need for human involvement significantly; this has had a direct impact on all things, from performance and efficiency levels to staffing issues and expenses.

Many financial institutions and other industries have widely adapted RPA; however, if you think that stand-alone RPA is by far the most trendy technology, you may already be lagging behind.

Artificial Intelligence (AI) has begun to permeate intelligent organizations and advance to the basic toolset for customers and employees to engage with people on a daily basis.

AI is defined by technologies such as speech recognition, natural language processing (NLP), semantic technology, computer vision, machine and deep learning (ML & DL), biometrics , and swarm intelligence.


The Banking Sector’s Adaptation Of RPA And AI

Although the customer experience space has the most prominent examples of AI, AI technology also plays a significant role in driving further operational efficiency across different sectors. In conjunction with RPA, AI can replicate labor activities that require expert judgment or complex decision-making on a larger scale, speed and accuracy than humans, not only simple but also complex.

RPA has helped banks dramatically speed up work and adherence to repetitive and manual-work-heavy processes and procedures. However, if banks take advantage of AI power and the growing popularity of cognitive technologies in addition to RPA technology, they can lead the innovation transformation and open unexploited opportunities. Banks can use Computer Vision and DL to understand and action digitized documents, use ML to find the best solution to any unforeseen event in a process, and monitor human transactions closely through NLP tools, prompting alerts for any unusual activities. AI helps deliver efficiencies, reduce risk, and foster better compliance through these and other types of applications.

At Banks, lawyers are often required to assess financial deals for easily thousands of hours. An AI system is able to do the challenging job of interpreting trade loan agreements, taking on a task that lawyers and loan officers to take on the several thousand hours of work. An AI/RPA system can review documents in seconds and is less likely to make mistakes. The system cuts in the interpretation of thousands of new wholesale contracts per year on loan service errors, many of which resulted from human error.

Key processes suitable for banking automation

  1. Account Origination
  2. Account Receivable
  3. Loan Processing
  4. Collections
  5. Lapse
  6. Investment Processing
  7. Cheque Processing
  8. Underwriter Support
  9. KYC Processing
  10. Deposit Account Receivable
  11. Surrenders
  12. Fraud Detection
  13. Service Desk
  14. Compliance
  15. General Ledger
  16. Customer Service
  17. Employee Onboarding And Offboarding
  18. Billing
  19. Credit Card Processing
  20. Report Automation
  21. Account Closure Process

RPA Highlevel Value Proposition

  • The robots work 24X7 with maximum precision at the lowest cost. They can complete the task on their own or complete one initiated by humans.
  • Robots are highly scalable, which means you can click on more robots during your business peak hours.
  • As well as generating full audit trails for each process, Robotic Process Automation help achieve process compliance and minimize business risk.
  • The impact of RPA from starts from day one, in that, customers realize a 30–70 percent reduction in processing costs or a reduction in turnaround time from days to hours or minutes.


Artificial Intelligence Is Now And Future-Ready

Thanks to better computing power and specialized hardware, AI is enhancing its capabilities with increasing speed and has increasingly proven itself in historically human-centric fields. AI is able to analyze what’s going on in the open digital world (internet), combine internal data with open data, and pursue ideas suggested by the AI algorithm. We might even see one AI solution creating another in the not too distant future.

Today, from a sci-fi movie, the rise of machines and AI is no longer something straight out of fiction. In the near future, robots will replace human labour, for specific jobs or tasks completely. So now is the time for banks to take the opportunity in the efficiency game to shift gear and use AI to their best advantage.

In conclusion, banking firms today face increasing demands to keep their operation as lean as possible while also providing exceptional customer experience at the lowest cost. In an ever-changing environment, robotic process automation enables financial institutions to achieve these goals and remain competitive.