Top 5 Use Cases of RPA in the Banking Industry


Robotic Process Automation (RPA) is a kind of productivity tool, a business process automation technology, that automates various repetitive tasks without any human intervention. RPA in the banking sector means the use of software robots that understand user actions at the very user-interface levels, automating repetitive, routine tasks that are usually done by knowledge workers in banks. It allows users to configure scripts  (bots) to activate certain specific keystrokes in an automated manner that leads these bots to do mimicking and simulating the tasks selected.

The inherent benefits of RPA in the banking sector are three-fold

  1. Creates, tests, deploys newer schemes in few hours rather than days or months
  2. It reduces human error by virtually eliminating mistakes of entering the same data into multiple systems
  3. Instant output by completing automated tasks in seconds thus delivering high values to customers

 Let’s discuss various real-time use cases of RPA being leveraged by the Banking sector across places!


Robotic Process Automation (RPA) has massive benefits in the banking sector as it reduces gaps between various applications by processing and integrating tasks at micro-levels. For instance, RPA, in general, does the following jobs-

  • Helps in Accounts Payable (AP)
  • Helps in Accounts receivable (AR)
  • Helps during financial closing & reporting
  • Helps in accounting data reconciliation
  • Helps in bank statement reconciliation
  • Routine or daily  P&L preparation

Besides the above-mentioned uses of RPA, specific use cases are there within the banking domain. What are they?


Suspicious Activity Reports or SARS are a general phenomenon in the banking segment. SARS are the general compliance reports that are prepared to check the fraudulent transactions and suspicious activities that happen to be a routine cadence in the work domain. In a conventional method, compliance officers manually do this job, read the reports, fill in the detail in the SARS, and so on. The reports would be generally prone to having errors and redoing them would follow thereafter.

             Robotic Process Automation (RPA)technology has the capabilities to sort out this issue. By using its natural language generation capability, RPA does the rigorous regimen of reading all the documents, the lengthy compliance documents, and then eventually extracting the information required to fill up the SARS.


Once again, the manual verification of a large number of documents to decide the credibility factor of customers, for onboarding purposes, is an uphill task. RPA makes this task very easy, accurate, and convenient. The Optical Character Recognition (OCR)technique is the keyword. RPA uses its OCR capability to capture the required data from Customers’ KYC documents and verifying the very same. Thus, the OCR technique capability of RPA helps match the data extracted with those provided by customers. This leads to identifying the loopholes and the verification process becomes a very simple and trusted one.


As compared with the traditional model of banking solutions, RPA  implementation proves to be a very cost-effective and time-saving model in the process mentioned. Normally, Know-Your-Customer (KYC) and Anti-Money Laundering (AML), are very rich data-centric, and a traditional banking solution cannot handle this job efficiently. RPA due to its inherent capabilities does the automation for the entire manual process and extracts all suspicious transactions in seconds if any.


RPA efficiently removes any scope of data transcription errors that had existed once between the core banking system and account opening requests. The automation process automatically eliminates all kinds of transcription errors and customers have a smooth account opening experience ultimately.


Loan processing has always been a tedious, slow process . It used to be completely manual work and involved several stages to get the loans approved and sanctioned. RPA technology has accelerated the loan processing segment, too, in a banking system. RPI implementation means the integration of some front-end application onto the ongoing IT system without causing any disturbance in the current flow of  IT structure. 

Banks form the core of the economy of a country and the role of Robotic processing Automation (RPA) technology is manifold. RPA technology helps increase productivity and ensures the accuracy and efficacy of the entire banking system. Integrating RPA into the banking system is actually a part of the digitalization process involved in the very system.

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