Several banks are implementing RPA technology across the world for different banking processes. RPA has surely improved the processing time for the various banking processes. According to an article published by Economics Times, various leading banks are adopting the use of RPA to automate processes such as IT support, email response, salary uploading process, funds monitoring, etc.
A case study recently published by Datamatics, an RPA vendor, explains, how the company successfully implemented its RPA tool named TruBot, to manage the entire banking KYC (Know your customer) process, which improved the processing time, productivity and developed an error-free system.
Here are some of the top RPA Use Cases in the Financial Industry -
Director, Customer Advocacy & Marketing at a computer software company with 1,001-5,000 employees
Vendor
Sep 25, 2019
Hello,
1. What are the potential uses for RPA bots in the financial industry?
Here are a few of the most widely adopted RPA use cases in Banking:
Customer Service
Banks deal with multiple queries every day ranging from account information to application status to balance information. It becomes difficult for banks to respond to queries with low turnaround time. RPA can automate such rule-based processes to respond to queries in real-time and reduce turnaround time to seconds, freeing up human resources for more critical tasks.
KYC Compliance Process
RPA increases productivity with 24/7 availability and highest accuracy improving the quality of compliance process. Know Your Customer (KYC) is a mandatory process for banks for every customer. This process includes conducting manual background checks on the customers. Banks have started using RPA to validate customer data. With RPA the process can be completed with minimal errors and staff and with increased accuracy and reduced costs.
Credit Card Processing
Traditional credit card application processing used to take weeks to validate the customer information and approve credit card. With the help of RPA, banks now can process the application within hours. RPA can talk to multiple systems simultaneously to validate the information like required documents, background checks, credit checks and take the decision of the basis of rules to approve or disapprove the application.
Mortgage Loan Processing
On average it takes approximately 50 to 53 days to process a mortgage loan. The Process of approving mortgage loan goes through various checks like credit checks, repayment history, employment verification, and inspection. A minor error can slow down the process. As the process is based on a specific set of rules and checks, RPA can accelerate the process and clear the bottleneck to reduce the processing time to minutes from days.
Fraud Detection
It is difficult for banks to track all the transactions to flag the possible fraud transaction. Whereas RPA can track the transactions and raise the flag for possible fraud transaction pattern in real-time reducing the delay in response. In certain cases, RPA can prevent fraud by blocking accounts and stopping transactions.
2. How has (or will) robotic process automation revolutionized the banking industry?
RPA has and will continue to help banking institutions reduce or eliminate reliance on inefficient, error-prone and expensive manual processes. RPA is already being used to optimize services that are used in Banking on daily basis including, generating financial statements, reconciliation of account balances, loan application processing (Credit cards, Installment loans, Mortgages) and other aspects of credit management like underwriting. RPA can minimize financial cyber threats by automating a broad spectrum of fraud prevention processes, like blocking or reissuing breached accounts, changing the account restriction criteria and automatically scanning negative files for the latest updates.
3. What processes are already being put to good use? What's in the pipeline?
RPA is already being used today to automate the processes listed in Q1. The future pipeline will include further integration of RPA with cognitive intelligence technologies such as machine learning and natural language processing (NLP) to enable more process automation and transformation. In addition, new RPA attended automation capabilities will enable customer service representatives to access data and collaborate with coworkers in real-time while on the phone or text chatting with customers.
Executive Manager: Shared and Support Services at a outsourcing company with 1,001-5,000 employees
Real User
Sep 25, 2019
In the healthcare insurance industry it has been successfully deployed in managing specific claims payments, onboarding of new clients and underwriting the benefits. Pipeline opportunities include scaling the existing process automation across the enterprise and all business units, plus expanding the use of RPA to automate the authorisation of benefits for hospital and specialised care.
Find out what your peers are saying about UiPath, Automation Anywhere, Microsoft and others in Robotic Process Automation (RPA). Updated: December 2025.
RPA automates repetitive and rule-based processes, allowing businesses to streamline operations and reduce human error. It integrates with existing systems to perform tasks like data entry and report generation without human intervention.With the ability to mimic human actions, RPA software enables organizations to optimize their workflows and boost efficiency. It is easily scalable and can handle complex workflows by operating continuously, unlike traditional manual processes. Users...
Several banks are implementing RPA technology across the world for different banking processes. RPA has surely improved the processing time for the various banking processes. According to an article published by Economics Times, various leading banks are adopting the use of RPA to automate processes such as IT support, email response, salary uploading process, funds monitoring, etc.
A case study recently published by Datamatics, an RPA vendor, explains, how the company successfully implemented its RPA tool named TruBot, to manage the entire banking KYC (Know your customer) process, which improved the processing time, productivity and developed an error-free system.
Here are some of the top RPA Use Cases in the Financial Industry -
RPA Use Cases for Banking - https://trubot.datamatics.com/resources/rpa-use-cases/banking and RPA Use Cases for Finance & Accounting areas - https://trubot.datamatics.com/resources/rpa-use-cases/finance-accounting
Hello,
1. What are the potential uses for RPA bots in the financial industry?
Here are a few of the most widely adopted RPA use cases in Banking:
Customer Service
Banks deal with multiple queries every day ranging from account information to application status to balance information. It becomes difficult for banks to respond to queries with low turnaround time. RPA can automate such rule-based processes to respond to queries in real-time and reduce turnaround time to seconds, freeing up human resources for more critical tasks.
KYC Compliance Process
RPA increases productivity with 24/7 availability and highest accuracy improving the quality of compliance process. Know Your Customer (KYC) is a mandatory process for banks for every customer. This process includes conducting manual background checks on the customers. Banks have started using RPA to validate customer data. With RPA the process can be completed with minimal errors and staff and with increased accuracy and reduced costs.
Credit Card Processing
Traditional credit card application processing used to take weeks to validate the customer information and approve credit card. With the help of RPA, banks now can process the application within hours. RPA can talk to multiple systems simultaneously to validate the information like required documents, background checks, credit checks and take the decision of the basis of rules to approve or disapprove the application.
Mortgage Loan Processing
On average it takes approximately 50 to 53 days to process a mortgage loan. The Process of approving mortgage loan goes through various checks like credit checks, repayment history, employment verification, and inspection. A minor error can slow down the process. As the process is based on a specific set of rules and checks, RPA can accelerate the process and clear the bottleneck to reduce the processing time to minutes from days.
Fraud Detection
It is difficult for banks to track all the transactions to flag the possible fraud transaction. Whereas RPA can track the transactions and raise the flag for possible fraud transaction pattern in real-time reducing the delay in response. In certain cases, RPA can prevent fraud by blocking accounts and stopping transactions.
2. How has (or will) robotic process automation revolutionized the banking industry?
RPA has and will continue to help banking institutions reduce or eliminate reliance on inefficient, error-prone and expensive manual processes. RPA is already being used to optimize services that are used in Banking on daily basis including, generating financial statements, reconciliation of account balances, loan application processing (Credit cards, Installment loans, Mortgages) and other aspects of credit management like underwriting. RPA can minimize financial cyber threats by automating a broad spectrum of fraud prevention processes, like blocking or reissuing breached accounts, changing the account restriction criteria and automatically scanning negative files for the latest updates.
3. What processes are already being put to good use? What's in the pipeline?
RPA is already being used today to automate the processes listed in Q1. The future pipeline will include further integration of RPA with cognitive intelligence technologies such as machine learning and natural language processing (NLP) to enable more process automation and transformation. In addition, new RPA attended automation capabilities will enable customer service representatives to access data and collaborate with coworkers in real-time while on the phone or text chatting with customers.
In the healthcare insurance industry it has been successfully deployed in managing specific claims payments, onboarding of new clients and underwriting the benefits. Pipeline opportunities include scaling the existing process automation across the enterprise and all business units, plus expanding the use of RPA to automate the authorisation of benefits for hospital and specialised care.