Banking is one of the most data-intensive sectors that operate in highly regulated markets. RPA automates labor-intensive manual processes and drastically reduces the need for traditionally repetitive manual work, data reconciliation, and transcription by up to 70%, so employees can focus on more complex banking operations. Axis Bank, Deutsche Bank, and other major banks have used RPA to automate business processes. Let’s read some more common use cases of RPA in Banking.

RPA in Banking

Many banks around the globe are recommending RPA to reduce human errors and save time due to the volume of data they have to deal with daily. Processing time has decreased from days to hours to minutes to just seconds. The processing cost has also dropped by between 30% and 70%. Banking automation using RPA technology has benefited several processes in a bank. It allows the team to concentrate on the client and the growth of the business.

RPAs are useful tools that can be used to support the banking sector’s needs. Let’s now look at the different applications of RPA in the banking sector.

1. Customer Service

Banks deal with many queries, including bank frauds, account inquiries, loan inquiries, etc. It is difficult for customer service to respond to these questions in a shorter period. Chatbots and RPA tools can be used to handle a large portion of this traffic. The bots can answer routine questions about account statements and transactions. However, queries that require human decision-making are escalated to the appropriate knowledge workers.

2. Customer Onboarding

Banks’ customer onboarding process is complex due to the manual verification of multiple identity documents. The Know-Your-Customer process is an integral part of the onboarding process. It requires significant operational effort to validate documents.

RPA tool allows customers to validate their identity and extract the relevant information from the application form. Automation not only eliminates manual errors but also saves time and effort for back-office staff.

3. Accounts Payable

The process of accounts payable is simple but not complicated. It involves extracting vendor information, validating it, and then processing payment. This case is ideal for RPA because it doesn’t require intelligence.

This problem can be solved by robotic process automation with optical character recognition (OCR). OCR can extract the vendor information from the digital copy physical form and send it to the RPA system. It will verify the information against the system and then process the payment. RPA will notify the executive if there is an error.

4. Bank Reconciliation Process

Bank reconciliation is a time-consuming process that requires knowledge workers to manually locate large amounts of transactional data from multiple banks and balance them. RPA Bots can replace manual effort with several rules-based automations. It includes verifying each payment entry against other records. The records can be reconciled if they match. If there are any discrepancies between the entries, the Bots may send the records to verify.

5. Automated Report Generation

Many financial service providers and banks use RPA to automate manual tasks associated with report generation. They can see an immediate return on investment (ROI). Automating report generation includes many activities such as optimizing data extraction from internal and external systems, standardizing data aggregation processes, creating templates for reporting, reviewing and reconciling reports, and standardizing data extraction.

6. Compliance

It can be difficult for banks to adhere to all the compliance rules. RPA makes it easier to follow the rules. Accenture’s 2016 survey found that 73% of compliance officers believe RPA can be a key enabler for compliance in the next three years. RPA can increase productivity by working 24/7, requiring fewer FTEs, and improving quality and compliance. It also increases employee satisfaction by eliminating monotonous tasks and engaging employees in tasks that require human intelligence.

7. Credit card processing

It used to take weeks for banks to approve and validate a credit card application from a customer. Customers were often dissatisfied with the long wait time and sometimes had to cancel their requests. RPA software allows banks to speed up the dispatch of credit cards. It takes only a few hours to gather the documents and background and credit checks on the customer. Then, it decides whether or not the customer is eligible for credit cards. RPA has made the entire process much easier.

8. Fraud Detection

A bank’s biggest concern was the increase in fraud cases. The number of fraud cases has increased exponentially with the development of technology. Banks are now unable to verify every transaction and spot fraud patterns manually.

RPA uses an “if-then” method to flag potential frauds to the appropriate department. It will identify the account and flag it as a possible threat if there are multiple transactions within a very short time frame. This allows the bank to examine the account and look for fraud.

9. General Ledger

Banks must ensure that the general ledger is updated with financial information, including revenue, assets and liabilities, income, expenses, and revenue. This information is used to prepare a financial statement. Stakeholders and the media can access public documents such as financial statements. An error in the report could have a devastating impact on the bank’s image, given the detail contained in it.

The bank must update the information from multiple legacy systems to create the statement. They also need to verify the data and ensure that it is correct. It is likely to contain errors due to a large amount of data from multiple systems. RPA comes to your rescue. RPA can be used to integrate data from legacy systems and present it in the desired format, regardless of whether they are in the same format. This allows for a reduction in data handling time and effort.

10. Account Closure Process

Many banks receive requests to close accounts monthly. Sometimes, accounts may be closed if customers do not provide proofs that they have the necessary documents to open the account. Human error is also possible due to the large volume of data banks handle each month and the strict checklist they must follow. Banks can use RPA to send automated customer reminders, asking them for the necessary evidence. It can process account closure requests quickly and accurately based on established rules. RPA can be programmed to handle exceptional situations, such as account closure due to non-compliance with KYC. This allows the bank to concentrate on more complex functions that are less repetitive and require greater human intelligence.

Conclusion

RPA has many benefits that banks should consider to improve customer experience and give them an advantage over their competition. Although it may seem expensive, the ROI it provides to the business can be substantial within months.

Cogniwize is one of the leading RPA service providers in this segment. We can help you if you’re looking for the best RPA solutions to improve your banking operations through intelligent automation. Request a demo or visit www.cogniwize.com to learn more about our RPA Services.