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Robotic Process Automation (RPA) is a rule-based software solution that automates repetitive tasks without any self-learning capabilities. It is not inherently artificial intelligence. RPA vendors now offer AI-tools as add-ons to their automation platforms. This includes RPA applications in banking where some form of AI, such as computer vision or natural language processing, is a part of the automation workflow.

In the banking and financial industries, which involve large-scale manual workforces, RPA has been used with the aim of saving cost, time, and human effort. For instance, banks have used RPA software to automatically retrieve information from external auditors or correct formatting and data mistakes in incoming funds transfer requests. 

In this article, we are going to zoom into the use cases that involve RPA  in the banking industry, along with its many functional benefits to the growth of each and every financial company.

1. Benefits of RPA in Banking

Banking and financial institutions have been known for the long-lived traditional processes, which affected the overall productivity and customer satisfaction levels to a certain extent. Although these businesses have already been trying to upgrade the process, applying RPA would create further opportunities to automate and shorten the complicated processes, as well as to assist many other developments in this angle:

1.1. RPA fuels digital transformation

Digital transformation could be done via different approaches. One of them is Robotic Process Automation (RPA) that helps to automate the bank’s front and back-office business processes and achieve greater operating efficiencies. In specific, RPA will affect digital transformation (or vice versa) by 4 major dimensions: People, Processes, Platforms, and Products.

1.1.1. People

One of the critical factors of any transformation is people. New processes could be significantly affected by the number of FTE headcounts (full-time equivalent) needed to perform them and could change the requirements to the staff competencies. In addition, the changes in the business processes could be designed and developed only with the active encouragement of senior managers, experts, and developers.

Using RPA to automate processes allows banks to:

  • Reduce and/or optimize the FTE number.
  • Improve employee culture. The processes most suitable for RPA are typically the most exhausting and least enjoyed. When the employees are freed from them, they can refocus on more rewarding and higher-value activities.
  • Decrease the dependency of the human factor. Robots are programmed to follow rules and robots do not make typos, mistakes, or forget to do the task, and so on.

1.1.2. Processes

The goal of any business transformation – digital or any other – is always to deliver a better customer experience. Reviewing, simplifying, optimizing the business processes is the main step of any transformation.

RPA can help banks to:

  • Optimize the processes and reduce hidden wastage. In this case, we are talking about all types of wastage – money, time, and efforts.
  • Decrease costs and increase profitability.
  • Reduce cycle times and improve throughput. Software robots are designed to perform tasks faster than a person can.
  • Increase the quality of processes monitoring. The tasks performed by a software robot can be monitored and recorded at every step, producing valuable data and an audit trail that can support further process improvement.
  • Help to collect data and follow the rules connected with regulatory compliance.

1.1.3. Platform

Successful business transformation that really delivers better customer experience can only occur with the support of modern platform tools. It’s a comprehensive task to integrate new technologies with many legacy systems that are still parts of the bank’s IT infrastructure.

RPA, in this case, has many advantages, comparing with other approaches of the transformation of the business processes (for example, Business Processes Modeling (BPM) or IT-transformation):

  • RPA could be integrated faster and easier with existing software infrastructure.
  • This approach is very flexible and easily altered or updated to adapt to the changing world. Robots can be quickly reassigned when other, more important processes arise—as each robot is typically capable of performing many types of processes.
  • It has high scalability. Once a process has been defined as a series of instructions that a software robot can execute, it can be scheduled for a particular time, and as many robots as required can be quickly deployed to perform it.

1.1.4. Products

The digital transformation could support the new products and services delivery or modification of basic products. Banks’ digital products must be designed within the context of the other digital properties that their customers are engaging with on a daily basis.

Using RPA allows banks:

  • Increase the quality of the services. Robots can work faster and do not need to sleep. So, the 24/7 service becomes cheaper and more reliable.
  • Implement new services or refine existing ones. Better data collection and optimization of the processes can be the base of significant changes in core business processes.


1.2. RPA helps smooth credit card businesses

Credit cards constitute a major component of the banking business. With several countries pushing for a cashless economy, the share of the payment card business is expected to grow significantly. Fierce competition and a thin spread mean that success depends on the ability to handle volumes efficiently. Thereby, process automation – or RPA in specific – will play a significant role in enhancing both the efficiency and profitability of the credit card domain.

There are lots of opportunities for RPA to benefit in this matter:

Function Process Opportunities for RPA
  • KYC (know your customers) & other checks
  • Credit scoring
  • Decisioning
Straight Through Processing and instant decisioning can be achieved through: 

  • Artificial intelligence – Business rules for application validation and decisioning can be parameterized or coded and automated.
  • Automated interfaces – Both internal and external – bureau checks, KYC, and so on.
  • Automated underwriting process – Credit scoring, risk assessment, collaterals, LoC assignment, and terms and conditions assessment.
  • Document management – physical application, signature capture, and storing.
  • Workflow management – Exceptions handling and initiating fulfillment.
  • Card personalization
  • Delivery
  • Activation
Straight Through Processing Automated activation 
Authorization  Referral handling Auto dialler for customer and issuer contacts
Transaction processing  Exception handling  Review, update, and re-process validation failed records
Clearing and settlement 
  • Reconciliation Exception handling 
  • Interchange optimization
Review, update, and re-process validation failed records Verification of the fees or charges collected by card schemes 
Collections  Delinquency monitoring 
  • Identification of delinquent accounts based on multiple parameters and business rules.
  • Dunning letters generation Monitoring and tracking.
  • Automatic card blocking based on business rules.
  • Alerts to customer support executives.
  • Collaterals tracking and appropriation.
  • Securitization.
Collection agencies management 
  • Assignment of accounts to agencies based on business rules.
  • Monitoring and tracking the performance of agencies.
  • Re-assignment of accounts.
  • Payables computation.
  • Promise-to-pay tracking.
  • Auto dialler for telecalling.
Customer communication and alerts 
  • Event-based and periodic communication
  • Transaction alerts
  • Transaction alerts.
  • Customer education on fraud risk.
Customer servicing 
  • Cross-sell
  • Customer complaints handling 
  • Auto dialler for telecalling.
  • Customer behavior analysis and offers. Redemption of rewards.
  • Automated messages to the customers on dates and events to remember 
Merchant management
  • Merchant acquisition and fulfillment
  • Merchant settlement
  • Merchant servicing 
  • Application processing and decisioning POS testing, certification, and merchant activation.
  • Merchant statements and other communications 
Partner management
  • Issuing partner 
  • Reward partner 
  • Periodical partner communication.
  • Partner accounts – settlement and reconciliation.

2. Use cases of RPA in Banking

Since RPA can be applied to a large number of business process automation projects, there are various well-defined use cases in this space. Some of them naming:

2.1. ATM testing

A global bank deployed an ATM testing robot to automate the test cases that were earlier conducted manually. The robot came with 5 components: 

  • Vision system for screen reading and identifying keyboard number, card slot, cash, and receipt identification.
  • High dexterity robotic arm to reach out to all areas of ATM operations.
  • End effector to handle multiple cards as well as perform keyboard, cash, and receipt operations.
  • Processing unit.
  • Defect logging engine that interfaces with the defect management system.

The robot tested various aspects including the screen, keypad, card dispensing mechanism, cash and check handling mechanism, cash counting mechanism, and debit and credit card differentiator, to deliver up to 80% cost and time savings.

2.2.  Transaction processing and sweep operations

For a bank, robots could be deployed in the areas of transaction processing and sweep operations. This eliminated manual effort, which reduced turnaround time (TAT) by 30 to 35% and significantly improved accuracy, increased productivity by 20%, and sizeably reduced full-time equivalent resources.

2.3. Automatic report generation

Generating compliance reports for fraudulent transactions in the form of suspicious activity reports (SARs) is a regular requirement at banks and financial institutions. Conventionally, compliance officers are supposed to read all the reports manually and fill in the necessary details in the SAR form. This makes it an extremely repetitive task, which takes a lot of time and effort.

RPA technology, with natural language generation capabilities, can read through these lengthy compliance documents before extracting the required information and filing the SAR. For optimal results, the RPA software can be trained with inputs from the compliance officers on the parts of each document which best fit each section of the report. Not only does this help in reducing the operational costs, but it also saves the time taken to perform the task.

2.4. Know your customer (KYC) and Anti-Money laundering (AML)

The fact that both KYC and AML are extremely data-intensive processes makes them most suitable for RPA. Whether it is automating the manual processes or catching suspicious banking transactions, RPA implementation proved instrumental in terms of saving both time and cost as compared to traditional banking solutions.

2.5. Customer onboarding

Customer onboarding in banks is a long, drawn-out process, primarily due to several documents requiring manual verification. RPA can make the process much easier by capturing the data from the KYC documents using the optical character recognition technique (OCR). This data can then be matched against the information provided by the customer in the form.

If there are no discrepancies post the automated matching, the data is automatically entered into the customer management portal. RPA automation in customer onboarding not only helps in avoiding manual errors but also saves a lot of time and effort put in by the employees.

2.6. Account opening

With RPA, the otherwise cumbersome account opening process becomes much more straightforward, quicker, and accurate. Automation systematically eliminates the data transcription errors that existed between the core banking system and the new account opening requests, thereby enhancing the data quality of the overall system.

An excellent example of this is global banks using robots in their account opening process to extract information from input forms and subsequently feeding it into different host applications.

The results in the elimination of an error-prone, time-consuming, manual data entry process, and a sharp reduction in TAT while, at the same time, maintaining complete operational accuracy and mitigated costs.

2.7. Mortgage lending

Lending is one of the critical service areas for any financial institution. The fact that the process of mortgage lending is extremely process-driven and time-consuming makes it extremely suitable for RPA automation. RPA technology can be used for effortlessly handling the process with clearly defined rules.

RPA allows for easy automation of various tasks crucial to the mortgage lending process, including loan initiation, document processing, financial comparisons, and quality control. As a result, the loans can be approved much faster, leading to enhanced customer satisfaction.

Another benefit of RPA in mortgage lending deals with unburdening the employees from doing manual tasks so that they can focus on more high-value tasks for better productivity.

2.8. Loan processing

Loan processing is somehow considered a tediously slow process. Although the bank has automated the process to a certain extent, RPA further accelerates it and brings it down to a record 10–15 minutes for processing.

2.9. Optical character recognition (OCR)

RPA platforms can come with intelligent OCR solutions that can help banks take handwritten forms or applications and automatically convert, verify, and edit the appropriate field in corresponding electronic forms. For example, if a customer submitted a handwritten KYC form, human employees are required to manually transcribe all this information into digital forms in several steps along the process. This is a time-consuming, repetitive task.

When an RPA platform is used, an employee could scan a paper KYC form and the digital image is sent to a software robot. AI-enhanced RPA software can automatically read through each character in the form and replicate it in digital forms.

The software gets better at this process over time through inputs from customer service operators during the training process where each character that is not correctly identified is corrected, eventually increasing the accuracy of character recognition. The overall business benefit is in cost and time savings for banks.

3. RPA Implementation Approach

Implementing RPA solutions in banking generally begins with the identification of accurate and feasible processes. It is pivotal for banks & finance companies to shortlist the right procedures followed by assessing them based on overall impact. For your convenience, we have prepared this cheatsheet to assist your success in RPA implementation:

3.1. 360 assessment

  • Conduct a detailed analysis to shortlist the processes suitable for RPA. 
  • List the operational issues that can be resolved through RPA. 
  • Assess their feasibility and impact.

3.2. Develop strong business cases

  • Document the cost and efficiency gains that RPA will deliver.
  • Consider running a proof of concept to demonstrate the benefits along with metrics on costs, time and effort, efficiency, and resource utilization.

3.3. Prepare a well-defined execution strategy

  • Choose the appropriate operating model considering your organization’s needs and identify key people to manage the execution. 
  • Check out the service provider landscape and identify the right partner – this is crucial as the right partner can help in end-to-end implementation spanning ideation, solution definition, planning, execution, and support. The execution can either be on a turnkey basis with the partner taking up complete responsibility or on a collaborative model. The right partner can also help identify the appropriate third-party tools to be used. These tools do not require customizations or enhancements, and significantly bring down the cost and effort. Moreover, they function as independent peripheral applications without interfering with mainstream applications.

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