The Banking and Finance Industry has witnessed exponential growth in the past few years. This has resulted in the need to adapt to the most advanced technologies to remain competitive in the market.
With the increasing adoption of virtual banking, the main concern is to deliver the best user experience while ascertaining maximum security. Moreover, the banks also have to maximize efficiency while keeping the costs as low as possible.
Robotic Process Automation (RPA) becomes a powerful and useful tool for banks with so much to manage within the budget and time constraints. Leading banks around the world have already adopted RPA for automated and more organized banking operations.
Through RPA, we can efficiently and effectively handle most of the tedious back-office work that gives the bank employees a headache. By incorporating RPA in the banking and financial sector, banks and organizations can significantly reduce the need for the workforce, thereby saving a lot of money and enhancing performance, speed, and efficiency.
Besides, this could be a perfect option to reduce errors while processing voluminous data. Not to mention that it can process data much faster and can reduce the processing cost by up to 70%.
Benefits of RPA in Banking
While the banks are always looking for measures to cut costs, implementing RPA can save up to 50% of banks’ operational costs.
Through process automation in the banking sector, the overall processing becomes much faster and more efficient.
Owing to the rising competition, banks need to become agile and flexible, now more than ever. RPA is the best option to gain agility and flexibility in operations.
Through RPA, banks can merge legacy data and new data into one system to make processes smooth and fast. This, in turn, also helps create more rapid and more accurate reports to develop business strategies.
It can increase the CAGR (Compound Annual Growth Rate) by 65% while reducing the process execution time by 60%. In simple words, the business response time decreases, and the growth rate increases.
It can be integrated within the existing infrastructure and does not require any unique setup. So, banks get an efficient and highly cost-effective solution.
Last but not least, customer trust and experience are enhanced. Customers don’t have time, and a bank that can quickly address their needs will definitely gain their loyalty.
Use Cases of RPA in Banking
In the BFSI segment, RPA can be applied to multiple processes to reduce human resources and errors. For example, chatbots can take customer service executives’ place to solve customer queries, complete KYC, credit card or account closure processes, fraud detection, mortgage processing, collection, and much more.
One can easily imagine how much time and resources could be saved through Robotic Process Automation in banking. Let us discuss the most common use cases for better understanding:
Better Customer Experience and Service
Banks receive numerous queries every single day. Some inquiries are regarding loans or accounts; others include bank fraud, debit cards, or transaction-related questions. A customer service team might find it very difficult to address these queries in a short turnaround time.
However, by integrating RPA, the bots can address generalized queries, and the customer service team can handle complex inquiries.
Faster Processing of Credit Cards
Until a few years ago, the processing of credit cards was a lengthy process that took weeks for only validation and approval. Thanks to robotic process automation in finance, it takes just a few hours to collect the required documents, running credit and background checks, and making the decision to approve or disapprove the request.
The whole process from validation to dispatch has become much faster, leading to a surge in the number of credit card users.
There are a plethora of compliance rules for banks, and banks have to collect a lot of data for reporting. By implementing RPA in banking and finance, complying with the regulations becomes easier. Many complex processes involved in the collection of data can be automated to enhance banking operations and risk management capabilities.
Faster KYC (Know Your Customer) Processes
According to Thomson Reuters, ‘several banks spend around $384 million every year on KYC compliance’. Due to such huge costs associated with KYC processes, this becomes a perfect use case of RPA. Through automation in banking and financial services, banks can aggregate customer data, evaluate, and validate it faster with fewer errors and manpower.
With a rise in technology, the numbers of fraudulent transactions are also rising, and monitoring all the transactions manually to identify fraud patterns is nearly impossible for the banks. To reduce such incidents, RPA's role in banking and finance is crucial as it automatically inspects suspicious transactions flagged by the AML (Anti-Money Laundering) systems.
According to ComTec, it takes more than 50 days, on average, to process Mortgage Loans. With multiple parameters to check, a slight error slows down the process considerably. Due to numerous scrutiny checks and a defined set of rules, this becomes one of the perfect use cases of RPA in finance.
By incorporating RPA, banks can speed up mortgage processing and also avert any issues that might cause a delay.
The manual process of creating reports is time-consuming, boring, and prone to errors. However, RPA systems hold all the data and can quickly fill up the required fields in the report without any mistakes. This will help the decision-makers to come up with strategies faster to gain a competitive edge.
Account Closure Process
The banks might receive many account closure requests in a month. This could be due to any reason. RPA can track the customers, send automated notifications, and schedule calls to find out the ‘why’ so customer executives can offer a solution. After this, depending on the course of action, RPA can initiate further action.
RPA is the modern solution for smart banking operations and offers a competitive edge to banks and a great customer experience.