What are the potential uses for RPA bots in the financial industry?

RPA is only growing bigger, with statistics predicting an increase in the industry worth to $2.1 billion by 2021 up from $250 million in 2016. The massive growth can be attributed to the dozens of advantages that RPA is offering businesses, the most significant one being cost-effectiveness.
The financial industry has not been left behind in the RPA frenzy. More banks and financial institutions are finding more applications for RPA bots to offer their clients the best experience. RPA is especially helpful for the financial industry. It offers cost-effectiveness, efficiency, and excellent security. Moreover, RPA has lifted the weight of boring, tedious, and repetitive tasks from bank employees’ hands, which has increased accuracy and lowered staffing costs. This article will take a closer look at the roles that robotic process automation can transform in today’s banks:
Compliance
Banking, being the core of the economy, is a heavily regulated industry. A survey by Accenture showed that 73% of respondents believe that RPA can make compliance less hectic for financial institutions. Thanks to its accuracy and productivity, RPA can readily improve the quality of the compliance process. For instance, KYC (Know Your Customer) is a requirement where every bank must perform necessary checks on their clients. The manual process of complying with this rule costs banks over $380 million every year. RPA is now being used to verify client data, which reduces the number of people needed to carry out the job and errors.
Customer service
Banks have to handle multiple requests every hour; from account registration, bank account balances, reactivation, among others. Bankers can quickly find handling these tasks overwhelming, considering their large volume. The slow rate of obtaining a response can also ruin customer satisfaction. RPA has made it possible to offer reliable and accurate responses to clients in seconds. This way, bank personnel can handle more critical tasks. Today, cognitive RPA has made it possible for banks to resolve queries that require intelligent input. Other chatbots respond to clients as a human would.
General ledger management
All banks must have a general ledger on which they store updated information on aspects like assets, liabilities, revenues, and expenses. The general ledger is then used to create financial statements like balance sheets, which are viewed by other stakeholders, like the media and shareholders. Keeping the general ledger error-free is, therefore, paramount to avoid corporate image damage. The general ledger is maintained with information from multiple systems that are not integrated. To eliminate the error-prone process of obtaining data from each system separately, RPA can quickly and effectively integrate data from the two systems regardless of their formats. This integration reduces errors, as well as data handling and exposure.
Automatic report generation
Banks are required to fill out different kinds of reports, such as the Suspicious Activity Report, in the case of a cybersecurity event. Since these reports are usually well-structured, RPA can quickly scan through them and extract relevant information to create automatic SARs.
Credit card processing
Traditionally, applying for a credit card meant waiting for weeks on end as the bank verified your information. This long wait eventually causes client dissatisfaction, which will be an added cost to the bank. With RPA, credit card application, processing, and receipt can take hours. RPA can communicate with multiple systems at a go-to carry out background checks, documentation, and other important factors, before deciding to approve or flag an applicant.
Fraud detection
White-collar crimes involving banks have been on the rise with the invention of electronic systems. Banks encounter thousands of transactions a day, and to determine fraudulent ones manually may be impractical. RPA can quickly detect and flag fraudulent transactions if a pattern or parameters are set. This quick detection will save clients and bank money and reduce the time taken to respond. RPA can also block the accounts of involved individuals or stop the transaction altogether.
Conclusion:
Whether offered by external vendors or built internally, RPA has a myriad of benefits for the financial industry. Clients will benefit from faster and more effective service delivery, while staff will not have to spend their days doing the same repetitive tasks. RPA has already been around for a decade, and it will continue to do more service to the financial institutions that embrace it.