Audit & Compliance
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 manual processes, RPA implementation proved helpful in saving both cost and time than labor-intensive traditional banking solutions.
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.
Data Processing and Verification
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.
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.
In the banking industry, 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.
Enterprises waste arduous energy each year in manually validating and reviewing online 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.
RPA use cases in banking including account approvals, collection, receivables, accounting origination, underwriter, general ledger, and account closure transform banking operations like never before. 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 out 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.