Top Uses Cases of RPA in the Banking Industry
Major banks were all over business news for implementing banking automation through Robotic Process Automation (RPA) to save labor and operational costs. Among them are Japan’s largest banks such as Sumitomo Mitsui Financial Group Inc. (SMFG), Mitsubishi UFJ Financial Group Inc. (MUFG), and Mizuho Financial Group Inc. (MHFG). Indian’s third-largest private Axis Bank and multinational investment company Deutsche Bank also joined in the trend by incorporating RPA in their processes.
As the speed and volume of financial transactions increase, several banks across the world advocate the use of RPA to minimize errors and human efforts. Banking automation through RPA technology reduces turnaround time in processing requests from days to minutes, and cuts processing costs by generally 30 to 70 percent. This enables bank personnel to focus on more important tasks such as engaging with the clients and growing business.
According to Deloitte’s 2018 Automation in Onboarding and Ongoing Servicing of Commercial Banking Clients report, these are examples of how RPA is automating common banking tasks today:
- Opening emails and attachments
- Filling in forms
- Copy and pasting data, then merging data from multiple places
- Following “if/then” decisions and rules
- Extracting and reformatting data into reports or dashboards
- Moving files and folders, and extracting structured data from documents
- Connecting systems through APIs
- Reading and writing to databases
- Making calculations
- Scraping data from the web
- Logging into web/enterprise applications
These tasks are part of greater processes and procedures in finance. Here are a few use cases in the banking industry that can be automated using RPA:
Customer onboarding in banks is a long process, which sometimes stretches from days into weeks because of several documents requiring manual verifications. RPA can help banks assess the risk of new customers by automating customer onboarding functions such as customer due diligence (CDD) and know your customer (KYC) processes. RPA can make the process much easier and faster by capturing the data from the KYC documents using the Optical Character Recognition (OCR) technique. The data can then be matched against the information provided by the customer in the form.
Account opening process becomes much more accurate and faster with RPA eliminating the data transcription errors and enhancing the data quality of the overall system. RPA can extract information from input forms and subsequently feed it into different host applications. By minimizing error-prone, time-consuming, manual data entry process, banks maintain complete operational accuracy and mitigate costs.
Accounts payable is a repetitive process which includes digitizing invoices from vendor using OCR, extracting data from all the fields in the invoice, validating, and processing it. RPA helps in automating this series of processes and make the next steps easier by automatically crediting the payment to the vendor’s account after reconciliation of errors and validations.
Loan applications can sometimes be slow and tedious even after a sequence of automation. With the use of RPA, integrated with other AI technologies, this monotonous task can be further accelerated, bringing the processing time down to a maximum of 10 minutes. No more long hours of waiting for your clients.
Credit card processing
Credit card processing is one of those time-consuming processes that typically takes a week. Through RPA, banks are now able to issue a credit card to clients within hours. An RPA tool can be programmed to communicate with multiple systems at once, validate the required information, conduct background checks, and make a decision based on the rules to approve and disapprove the application.
Fraud detection and prevention are considered major advantages in utilizing RPA capabilities in banking. Using the “if-then” method, RPA can identify potential frauds and flag them to the concerned department. When properly implemented into a well-designed process, RPA can minimize the human element of fraud.
Account closure happens mostly due to the non-compliance on the part of the clients in the submission of mandatory documents. This kind of case happens numerous times that banks have to deal with enormous account closure requests on a monthly basis. RPA helps banks tackle this issue by tracking all non-compliant accounts and sending automated reminders asking them to furnish the requirements. RPA can also be programmed to close an account due to failure in KYC compliance.
Banks and financial institutions are increasingly realizing the transformative power of Robotic Process Automation as it has proven to digitize the manual tasks in core banking functions while increasing operational agility. With the current demand for digital services, other players in the banking sector must consider using it in all their functional areas to enhance productivity, improve customer experience, and gain an edge over their competitors.