Top 10 RPA use cases in the banking industry


Robotic Process Automation (RPA) refers to the process of using software bots, programmed to perform tedious and repetitive tasks. It is compatible with many applications in banking, which is one of the most data-intensive industries operating in a strictly controlled market.

Robotic Process Automation has been adopted in many business fields considering its benefits and applications. The banking industry is dealing with rapid turmoil and they are under extreme pressure to boost efficiency and optimize the resources due to the Covid19 pandemic, unstable economy, and competition from virtual banking solutions.

Some of the challenges faced by the banking and financial sector today are a lack of efficient resources, a rapid boom in personal spending, and the need to improve process efficiency. Amid the Covid-19 scenario, banks are exploring the possibilities to reduce costs and increase revenue growth. All these reasons led to the adoption of RPA in the banking sector and it is proving to be an important tool for digital transformation in the banking industry.

Robotic Process Automation in Banking 

RPA is the very next step in technology that can help solve many issues in the banking and financial sectors. It evolves as an effective way for financial organizations to support their digital transfiguration efforts. In banking and finance, Robotics is mainly defined by the use of robotic process automation software for –

  1. Installing software bots at the level of end-user device and desktop
  2. Create virtual assistance or an artificial Intelligence workforce.

RPAs in the financial industry helps in increasing efficiency by lowering the cost using the services-software model, in order to act as a useful tool to meet the needs of the banking sector. Now, let us move into the various application of RPA in the banking sector.

Top 10 RPA use cases in banking  

As we discussed before, there are different types of well-defined RPA applications or use cases in the banking and finance sector. Therefore, let us go through the use cases of RPA one by one.

  1. Generates automated reports: Unlike the obsolete traditional system that cannot implement integration between multiple systems, RPA bots are capable of copying data from one system to another one to create a report. RPA can perform such tedious tasks as it can mimic human workers, which cannot be performed by obsolete systems.
  1. Account closure: Robotic Process Automation tracks all accounts with closure issues and helps the banks to tackle such issues by sending them an automated notification and other reminders to submit all the necessary documents. The account closure comprises a number of manual tasks, including confirming the availability of the document in the bank records, sending emails to customers and branch managers, and updating system data. RPA bots are capable of automating these human resource tasks so that human workers can invest their time on o productive activities.
  1. Customer experience: Banks are dealing with a wide range of queries including bank fraud, account and loan inquiries, etc. Therefore, the customer service team finds it difficult to solve every issue in a short period of time. Here, RPA plays an important role by resolving low-priority questions, allowing the customer service team to concentrate on queries of high priority. Moreover, RPA takes lesser time to verify and isolate customer details from onboard systems. The shorter wait times and easier solutions have helped banks enhance their customer relationships.
  1. Mortgage processing: Usually it takes 50 – 53 days to close a mortgage loan as it undergoes several scrutiny checks including a credit check, verifying jobs, and valuation or inspection, which have to be carried out before giving approval. This process can be slowed down or delayed in case of any minor error from the banks or customer’s side. RPA can be implemented here to carry out such tasks and to avoid errors that may delay the process. It not only accelerates the process but also reduces the burden of manual workers.
  1. KYC process: KYC (Know Your Customer) is a data-intensive process that requires 150- 1000 FTEs to perform customer checks. As per the reports, banks are spending 385 million US dollars on compliance with KYC. One can use RPA bots to support the automation of the KYC process. Under normal circumstances, RPA bots can accelerate processing time, enhance safety and compliance, and lowers error rates for processes encountered by customers
  1. Credit card processing: Earlier, banks took weeks to validate and approve a credit card application of the customer. Most of the time this delay has led to customer dissatisfaction and the cancellation of application requests as well. One of the main use cases of RPA is that it enables an automated process for credit card applications in which banks have received extraordinary results. RPA helps customers to receive a credit card within hours. RPA bots can easily go through varied systems, validate data, perform background checks based on various rules, and decide whether an application should be approved or rejected.
  1. Fraud detection: Rapid rise in the number of fraudulent cases is one of the major threats of a bank. With the introduction and use of advanced technology, the fraud cases have increased making it difficult for banks to verify and cross-check all transactions in order to manually recognize fraudulent patterns. The RPA uses an ‘if-then method to detect potential fraud and label the relevant department. For example, if different transactions are made within a short period of time, RPA can easily identify the account and mark it for serious threats. It helps in bank account checking and fraud investigation.
  1. Accounts payable: Accounts Payable (AP) is a repetitive process and needs to be digitized using OCR (optical character recognition), obtain, corroborate, and process information from all the fields using invoices by the vendor. RPA facilitates automation of this process and automatically deposits the payment to the account of the vendor after rectification of error and validation.
  1. Anti-money Laundering (AML): An excellent example of an RPA in banking is the automation of the entire AML query process. It is a physical process and can take from 30 to 40 minutes to investigate a single case, based on the availability and difficulty of information in different systems. These tedious and rule-based applications can be mechanized using RPA, thus enables a reduction in process return time of more than 60 percent.
  1. General Ledger: Banks should make certain that all important information including the financial statements, income, expenses, assets, and liabilities are updated in their general register or records. The bank prepares its financial statements based on this information, which is accessible to the public, media, and other interested parties. Considering the vast details required by the various systems for making financial statements, it is necessary to ensure that the general ledger is compiled with not a single error. Here is where RPA serves its function. It assists in collecting, validating, and updating information from a variety of systems without error.

Benefits of RPA in banking 

Some of the key benefits of RPA in the banking and financial sector include;

  1. Scalability – RPA bots are highly scalable as they allow banks to concentrate more on advanced strategies to liberate employees from routine tasks and to promote the growth of the business.
  2. Enhanced functional efficiency – RPA helps banks and financial institutions to function effectively at a faster pace.
  3. Cost-effectiveness – balancing the cost-saving is one of the important features of banking institutions. Using RPA, banks can save up to 20% – 50% processing time and expense.
  4. Quick implementation – As RPA tools provide a drag-and-drop technology for the automation of banking processes, it is easy to execute automation workflows and maintain using minimal or no coding requirements.
  5. Availability – the RPA bots work 24*7 to complete the tasks assigned to them and therefore eliminates the chance of manual errors and greater accuracy at a lower cost.

Wrap Up 

Robotic Process Automation facilitate the automation of various business sectors using software bots. Implementation of Robotic Process Automation services can reduce the use of human resources to a large extent and is not limited to a single business operation.

This article discusses the application of RPA in various areas of the banking and financial sector. If RPA is implemented properly, it can withstand a lot of adverse conditions in the banking sector. For the successful application of RPA, it is important to have participants with proven expertise in RPA equipment and technology during the implementation process. This will not only bring essential benefits to banks and financial institutions but will also guide them on how and when to switch from RPA to other next-generation tools such as AI and CPA.

Aravind NallasivamAbout the author: Aravind Nallasivam is a solutions architect at ClaySys Technologies. He deals with robotic process automation tools and technologies.