Top 10 RPA Use Cases in Banking Industry

Today, RPA has become an essential tool for most businesses, including banks. The banking industry is witnessing rapid turbulence caused by the global pandemic and economic instability. Amidst the COVID-19 situation, banks are looking for all the possible ways to cut costs and drive revenue growth. RPA in the banking industry is proving to be a key enabler of digital transformation.

There are numerous RPA use cases in banking. The list below highlights some of the most rewarding RPA use cases in the banking industry.

1. Customer Service.

As banks handle multiple queries ranging from bank fraud to account inquiry, loan inquiry, and so on, it is extremely difficult for the customer service team to address them in less time. RPA helps the low-priority queries to be resolved, freeing the customer service team to focus on high-priority questions. RPA also helps to reduce the amount of time it takes to check customer details from and disparate onboard systems. The reduced waiting time and easy redress helped banks improve their customer relationships.

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. Credit Card Processing.

RPA-enabled automation for credit card application processing is another use case where banks have seen phenomenal results. RPA allows for the issuance of a credit card to customers within hours. RPA Bots can navigate through multiple systems with ease, validate the data, conduct several rules-based background checks, and decide to approve or disapprove the application.

4. KYC Process.

While dedicated KYC solutions are emerging, it is also possible to use RPA bots to automate portions of the KYC process. For edge cases that require human intervention, the case can be forwarded to an employee. For regular cases, RPA bots can speed up processing times, improve security and compliance, and reduce error rates for this customer-facing process.

5. Audits.

Banks need to reply to requests by the auditors for company audit reports. Bots have been used to find all the customer’s accounts year-end balances and return the audit to the audit clerk in the form of a Word document. This can reduce an average audit, which can take several hours to complete and an extensive audit that can take several days into an operation that can be completed in minutes.

6. Regulatory Monitoring.

RPA can be used to scan regulatory announcements for future changes, to catch changes early, or to access the latest updates as new information is released. As regulation is established, changes may not always be apparent. RPA can be used to cross-compare notifications to show what has improved. This significantly reduces the time spent on identifying regulations and decreases the possibility of noncompliance fines due to errors.

7. 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

8. 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.

9. Automated Report Generation.

Many banks and financial services providers are utilizing RPA to automate manual tasks involved in report generation and are able to realize an immediate return on investment (RoI). Automating the report generation process includes a range of activities such as optimizing data extraction from both internal and external systems, standardizing the process of data aggregation, developing templates for reporting, review, and reconciliation of reports.

10. Account Closure Process.

The end-to-end account closure activity involves a range of manual tasks such as checking documents’ availability in the bank’s records, sending emails to clients and branch managers, and updating the data in the system. RPA Bots can automate all of these manual tasks so that the knowledge workers can focus more on productive operations.

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.