where RPA integration can smoothen the
functioning in the banking sector are:

Compliance and Reporting

RPA in the banking & financial sector can help reduce the workload of compliance reporting by collating data periodically. As the finance sector is period and format sensitive, this information is used to prepare reports in standard formats which are presented to the management and other sources to judge the performance and also make policy decisions. RPA helps in increasing productivity by functioning 24/7 with fewer FTEs and improving the quality of the compliance process.

Monitoring & Managing Regulatory Compliance in RPA
Automate Data Extraction with AI and Intelligent RPA

Data Extraction and Document Processing

These two are very important business processes in the banking industry and to solve the complexities surrounding data extraction and document processing, RPA in the banking sector is used heavily. RPA speeds up monotonous verification processes by extracting relevant information from various forms and documents. The information is validated against in-house and third-party databases depending on the end purpose of the information. The most common verification processes that can be automated using RPA are the following:

Know Your Customer (KYC) is a critical compliance process in every bank. Mid to large-sized banks can deploy 150 to 1000 FTEs to perform checks on the customer. 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 in the banking and financial sector to collect customer data, screen it, and validate it. RPA bots can help the banks to complete the process in a shorter duration with minimal errors and staff.

In the US, it ideally takes 50 to 53 days to close a mortgage loan. The process takes time as the application has to go through various scrutiny checks such as credit checks, employment verification, and inspection before approval. With RPA, banks can now accelerate the process by conducting parallel verification on different third-party platforms seamlessly.

Banks must ensure that their general ledger is updated with important information such as financial statements, assets, liabilities, revenue, and expenses. An enormous amount of details is required from disparate systems to create a financial statement. It is also important to ensure that the general ledger does not have any errors. An automated system like RPA leads to proper ledger maintenance.

Banks have multiple types of queries to deal with, ranging from bank frauds to account enquiry, loan enquiry, and so on. Low priority queries that have standard answers, and less decision-making are, in fact, high on volume. RPA helps in resolving the low priority queries, freeing up the customer service team to focus on high priority queries requiring human intelligence. The reduced waiting period and easy redressal help banks in improving their relations with the customer.

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 cancellation. However, with the help of RPA, the entire process can be streamlined to make the card dispatch process shorter.

RPA is used extensively in the banking sector for reconciliation of ledgers and accounts. RPA automation can be trained to identify credit debit entries and collate information from various sources to update the ledgers and accounts of customers and do instant reconciliation and statement generation.

Intelligent RPA combined with AI and ML can be used to alert customers and banks of potential banking frauds. RPA driven automation can also detect fraud on live transactions as well as execute data mining and trend analysis for potential fraud transactions to find a pattern of fraud. This helps the bank to scrutinize the account and investigate for fraud.

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 proof 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, there is a need for automation.

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 business rules with 100% accuracy. RPA is programmed to cover exceptional scenarios as well such as closing an account due to failure in KYC compliance. Thereby, it directly contributes to improving the efficiency of the bank.