RPA for the banking industry is like a match made in heaven. With robotics, all the mundane, labor-intensive, rule-based, repetitive tasks across the banking sector can be automated using simple software bots. By implementing pre-programmed rules, software bots automate high-volume business processes to optimize costs, improve operational accuracy, and assure improved talent management.
The most significant advantage of RPA is that they function on top of applications to smartly mimic all human actions at the primary user interface level. Let’s look at the most automated processes in the banking industry that have undergone complete digitization with the touch of automation:
- Loan processing
Loan processing is one of the most tediously slow processes across the banking industry. RPA can bring down months-long processes to a record time of 10-15 minutes.
Automation allows extracting relevant information from the documents submitted by the customer to verify all details. Systems use machine learning, backed by more straightforward statistical approaches to making more decisive decisions based on data analytics. Intermediary bots derive business logic, asking the user to fix all incorrect entries, assuring safer loan decisions, backed by automated confirmation letter generation. - Account closure process
The monthly burden of account closure requests that banks struggle to manage is way too enormous. The biggest reason for such over-burden is the clients’ non-compliance, leading to delayed submission of mandatory documents.
RPA enables banks to tackle this issue by seamlessly tracking all accounts and sending them a continuous automated notification and additional reminders for timely submissions. Automation allows cancellation of standing orders and direct debits, change of interest charges, and fund transfers with accessible online forms. - Know Your Customer (KYC)
Know Your Customer (KYC) is not only a critical compliance process for every bank, but it is the most complicated one as well. This process involves a minimum of 150 to even thousands of FTEs to perform checks on the customer.
Thomson Reuters confirmed that few banks spend a minimum of US $500 million per year on their KYC compliance. Banks have now started leveraging RPA to collect customer information, screen it, and perfectly validate it to reduce the considerable cost and resources. This empowers banks to complete the KYC process in a comparatively shorter duration with limited staff and minimal errors. - Anti-Money Laundering (AML)
AML is one of the most data-intensive processes which can be simplified using a touch of RPA. Whether it is catching suspicious banking transactions or automating the manual processes, RPA implementation proved helpful in saving both cost and time than labor-intensive traditional banking solutions.
- Accounts Payable
Accounts Payable (AP) is confusing and highly monotonous as a process that requires invoices digitization from vendors based on Optical Character Recognition (OCR), extracting data from all the necessary fields in the invoice, and validating them quickly.
Robotic Process Automation empowers businesses to automatically credit all payments to the vendor’s account after detailed validations and reconciliation of errors. - Credit card application processing
Credit card applications previously took a weeks-long waiting period, resulting in customer dissatisfaction, sometimes even pushing the customer to cancel the request. However, with the power of RPA, banks can speed up the process of dispatching credit cards promptly.
It now takes only a few hours for the RPA software to gather all customer documents, make credit checks with detailed background verifications, and take a wise decision based on pre-defined parameters to check customer eligibility. RPA has perfectly streamlined the entire process of credit card processing, making the lives of banking staff and customers easy.
- Fraud Detection
With the banking fraud landscape expanding, banks are worried about strengthening their fraud detection mechanism. With the advent of the latest technology, banking frauds have only multiplied. Thus, it is next to impossible for banks to check every transaction to identify fraud patterns manually in real-time.
RPA smartly deploys an ‘if-then method to identify any potential fraud and flag them for a quick resolution to the concerned department. - General Ledger
Banks need to mandatorily keep their general ledger updated with crucial information like revenue, assets, liabilities, expenses and revenue, which is necessary to prepare financial statements. With this vast amount of data from diverse systems, the manual management process is highly error-prone.
RPA comes to the rescue, in this case, integrating data from diverse legacy systems to collaboratively present them in the required format. This reduces the amount of data handling efforts and time. - Mortgage Processing
Mortgage processing is highly labor-intensive and tedious for both banks and their customers. Banks take over a month to manage their mortgage process, including numerous worrisome steps, including employment verification, credit checks, and inspection before approving each loan request. Even the slightest error by either the customer or the bank could dramatically delay the mortgage loan processing.
But, RPA has accelerated this process for banks. Robotics goes through a defined set of rules to eliminate all potential bottlenecks, to speed up mortgage processing. - Bank Reconciliation
Enterprises waste arduous energy each year in manually validating and reviewing inline transactions. Though the advent of various technologies and fragmented solutions have mitigated the painstaking process of managing journal entries, banks are still swimming upstream towards different challenges like muddled processes, transaction volumes, and eternal sources of data feed.
RPA allows enterprises to make quick cost reductions while improvising the back-office staff workload and enabling them to engage in more fulfilling activities. Leveraging RPA solutions would allow banks to build applications for reconciliations that offer automated journal entries, sophisticated data comparison, and long-term archiving.
Conclusion:
Robotic Process Automation plays a drastic role in improvising several banking aspects, including account approvals, collection, receivables, accounting origination, underwriter, general ledger, account closure, etc. The prospects for RPA in banking are vast and profound. In the near future, they are only bound to expand further and grow.
Today, the world is pacing rapidly towards digitization, and so are the banks. To match up with the accelerated pace of digital transformation and an aggressive competitive landscape infused with mounting market pressures, it has turned to be pertinent for banks to adopt RPA. Robotics and automation allow effective cost management as well as resource utilization for customer/employee satisfaction. Robotic Process Automation is undoubtedly the dawn for modern digital banks.