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How do AI and RPA enhance the banking sector significantly?

Can RPA, AI, and IPA elevate the banking experience for customers as well as the bank employees? Believe it or not, it can! Read more to know how.

RPA or Robotic Process Automation is gaining real prominence in the banking arena lately. Banking is one sector, where the intensity of performing repetitive tasks is pretty high. So, if there’s loan processing, the banking personnel has to get the documentation verified, check the credit scores, make information reports, and even analyze whether or not the customer is likely to default. And, the number of applications that a bank receives for loans is quite dramatic. This means that a lot of manpower will be required to get the processing done in time and with efficiency, resulting in increased costs.

To automate such mundane processes, without disrupting the current infrastructure and ecosystem of the bank can be a challenge.

RPA handles and manages these monotonous tasks for the banks, to free up the space for employees, to be utilized for more important tasks at hand.
It is a non-intrusive tool that is programmed in a way that it can carry out repetitive processes across systems and applications at a fraction of cost.

RPA in banking is a smarter step towards a digitized environment that doesn’t have much scope for human error, with time utilization as a byproduct.


RPA or Robotic Processing Automation in banking is leveraged to automate mundane tasks.

AI or Artificial Intelligence in banking is utilized to derive intelligent insights from the processes.

IPA or Intelligent Processing Automation in banking is deployed to encompass RPA with AI capabilities to enable its learning capabilities.

How can RPA, AI, IPA enhance the banking sector significantly?

Let us have a look at the most significant ways through which the power combo of RPA, IPA & AI has helped the banking industry significantly and resultantly increased the customer experience on a multifold level. 

  1. Credit Card Processing

We can swipe our credit cards anywhere and anytime almost immediately, to make a transaction. But, there’s a lot that goes on in the background in real-time that decides the transaction’s fate. When a cardholder tries to make a payment via the credit card, the first step that is taken is payment processing through the gateway. This information of the transaction request is then passed on to the issuing bank to approve or reject the payment.

In order to make that decision, the issuing bank has to –

–         Check the availability of sufficient funds

–         Check the legitimacy of the transaction

–         Collect and forward the necessary information and details

With RPA, banks can automate some of these processes to reduce the time taken to carry them out as well as enhance the visibility of every particular step in the entire processing cycle.

  1. Advanced Charting for Trading

Banks nowadays also offer trading as one of the offset services to allow customers to make investment choices. But, trading again is something that requires extensive information gathering and streaming them into charts, for informed decision making.

Edelweiss’s TX3 platform can create and stream complex live charts such as Renko, Heiken Ashi, etc. It also allows users to collect and view insightful market data dating as old as 10 years. Users can create heavy charts with available data in almost no time and accordingly make their trading and investment decisions.

Here, automation of the process along with advanced analysis is the technical USP that banks can offer.

  1. Smart Market Analysis

Be it lending, mortgage, loans, accounting, KYC, fund transfers, or even audits, banks can conduct an in-depth analysis of the market conditions to enhance their product offerings, leading to customer retention.

Smart Market Analysis of any of these processes requires AI capabilities that can pinpoint the problem areas along with areas of improvement. Banks can use these insights to reform their services and take a statistical approach to curate their offerings as per the customer needs and personas.

Product personalization can be achieved with advanced AI and IPA to deliver the business logic-fueled customer-centric frameworks.

  1. Chatbot Support

Customer support is a huge part of the present digital banking environment. And multiple pieces of research indicate that the new-age customers would rather use self-service support than talking to customer support.

Chatbot support that can collect and store user data, driven by RPA as well as harness that data to deliver excellent customer experience, driven by AI, is the need of the hour. The tasks and FAQs that are not of high priority can be taken care of by these bots, and the customer support team can be laser-focused on situations that require human intelligence.

Moreover, these bots are live 24*7. Meaning, thorough customer support, whenever the customer needs it.

The during and the post-pandemic world requires a higher attention to detail and less time spent on repetitive tasks. With RPA, AI, and IPA, banks can now elevate their customer experience and automate their tedious manual tasks to reimagine the way banking services get delivered!

For more such updates and perspectives around Digital Innovation, IoT, Data Infrastructure, AI & Cybsercurity, go to

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