10 Use Cases of RPA in Banking Industry

use cases of RPA in Banking Industry

Recently, Japan’s largest banks such as Sumitomo Mitsui Financial Group Inc. (SMFG), Mitsubishi UFJ Financial Group Inc. (MUFG), and Mizuho Financial Group Inc. (MHFG) were in news for implementing banking automation through Robotic Process Automation (RPA) to save labor and operational costs. Major banks such Axis Bank and Deutsche Bank were also in the news for incorporating RPA in their processes.

With the voluminous data dealt with every day, several banks across the world are advocating the use of RPA to minimize errors and human efforts. The turnaround time in processing a request has reduced from days to hours and even minutes, and the processing cost has reduced by 30% to 70%. Several processes within a bank have benefitted from banking automation through RPA technology, allowing the teams to focus on engaging with the clients and growing business. Some of these processes include:

    1.Customer service

As banks deal with multiple queries ranging from bank frauds to account enquiry, loan enquiry, and so on; it becomes difficult for the customer service team to address them within a less turnaround time. RPA helps in resolving the low priority queries, freeing up the customer service team to focus on high priority queries requiring human intelligence.

RPA helps in resolving the low priority queries, freeing up the customer service team to focus on high priority queries. Click To Tweet

RPA also helps in reducing the time taken to verify customer details from disparate systems and onboard them. The reduced waiting period and easy redressal have helped banks in improving their relations with the customer.

     2. Compliance

With so many compliance rules, it becomes an arduous task for the banks to comply with each of them. RPA makes it easier for banks to adhere to the rules. According to a 2016 survey by Accenture, 73% of the surveyed compliance officers believed that RPA could be a key enabler in compliance within the next three years. RPA helps in increasing productivity by functioning 24/7 with fewer FTEs, improving the quality of the compliance process, and increases employee satisfaction by eliminating monotonous tasks and engaging the employees in tasks requiring human intelligence.

    3. Accounts Payable

Accounts Payable (AP) is a monotonous process that requires digitizing invoices from the vendors using Optical Character Recognition (OCR), extracting information from all the fields in the invoice, validating it, and then processing it. RPA helps in automating this process and automatically credits the payment to the vendor’s account after reconciliation of errors and validations.

   4. Credit card processing

Earlier, it took weeks for a bank to validate and approve the credit card application of a customer. The long waiting period resulted in customer dissatisfaction, sometimes even leading to a customer cancelling the request. However, with the help of RPA, banks are now able to speed up the process of dispatching the credit cards. It takes just a few hours for RPA software to gather documents of the customer, make credit checks and background checks, and take a decision based on set parameters on whether the customer is eligible for a credit card or not. The entire process has been streamlined perfectly by using RPA.

    5. Mortgage processing

In the US, it ideally takes 50 to 53 days to close a mortgage loan. The process took time as the application had to go through various scrutiny checks such as credit checks, employment verification, and inspection before approval. A minor error from the customer or bank’s side could slow down the process and lead to unnecessary complications and delays. With RPA, banks can now accelerate the process based on set rules and algorithms and by clearing the bottlenecks that delay the process.

     6. Fraud Detection

One of the major concerns of a bank was the rising number of fraud cases. With the advent of technology, the instances of fraud incidents have only multiplied. Thus, it becomes difficult for banks to check every transaction and identify fraud patterns manually.

RPA uses an ‘if-then’ method to identify potential frauds and flag them to the concerned department. For example, if there are multiple transactions made within a short time, then the RPA identifies the account and flags it for a potential threat. This helps the bank to scrutinize the account and investigate for fraud.

RPA uses an ‘if-then’ method to identify potential frauds and flag them to the concerned department. Click To Tweet

      7. KYC process

Know Your Customer (KYC) is a critical compliance process in every bank. The process is so crucial that it involves at least 150 to even 1,000+ FTEs to perform checks on the customer, and according to Thomson Reuters, some banks spend at least US $384 million per year on KYC compliance. Considering the cost and resources involved in the process, banks have now started using RPA to collect customer data, screen it, and validate it. This helps the banks to complete the process in a shorter duration with minimal errors and staff.

      8. General Ledger

Banks have to ensure that their general ledger is updated with all important information such as financial statements, assets, liabilities, revenue, and expenses. This information is used for preparing financial statements of the banks, which is then accessed by the public, media, and other stakeholders.

Considering the enormous amount of details required from disparate systems to create a financial statement, it is important to ensure that the general ledger is prepared without any error. This is where RPA comes to rescue. It helps in collecting information from different system, validating it, and updating in the system without any errors.

     9. Report Automation

As a part of compliance, banks have to prepare a report about their various processes and present it to the board and other stakeholders to show the performance of the bank. Considering how important the reports are to the reputation of the bank, it is important to ensure that there are no errors.

While there are systems to provide data, and templates to present them in a digestible format, what the banks required was accurate data with no error. RPA helps banks in preparing reports with accurate data. It gathers information from different sources, validates it, arranges it in an understandable format, and schedules it to be sent to different sources.

    10. Account Closure Process

Banks receive several requests to close the accounts on a monthly basis. Sometimes, the accounts can also be closed if the client does not furnish the proofs required for operating the account. Considering the high volume of data handled by the bank every month and the checklist they need to adhere to, the scope for human error also increases.

With RPA, banks can send automated reminders to the customers asking them to furnish the required proofs. It can also process the account closure requests in the queue based on set rules in a short duration with 100% accuracy. RPA is programmed to cover exceptional scenarios as well such as closing an account due to failure in KYC compliance. So, this makes it easier for the bank to focus on other functions that are less monotonous and require more human intelligence.

Conclusion

With so many advantages of RPA, banks must consider using it in all their functional areas to enhance customer experience and gain an edge over their competitors. It might seem to be a costly investment, but considering the value it delivers to the business, it can provide a good ROI within months of implementation.

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