Robotic process automation (RPA) in the banking and financial sector is becoming more of a must-have than a good-to-have. This is because it helps banks and other financial institutions remain agile and error-free. With robotic process automation in the banking industry managing millions and billions of transactions and handling numerous customer data points for each of them, all of it happens in a flash.
In 2020, RPA in the banking and financial sector was forecast to be worth USD 2.09 billion. But there is anticipation that it will be worth USD 23.9 billion before 2031.
This is the outcome of expanding the use of robot-based solutions across various end-user industries and in various use-cases. Additionally, RPA in financial services allows financial firms like yours to conduct repetitive activities accurately. Hence, increasing operational efficiencies while reducing human error.
Read on to learn more about RPA in the BFSI industry and its use cases.
Also Read: 10 Use Cases of RPA in the Insurance Sector
What is RPA in the Banking and Financial Sector?
Automation, in general, a set of programs or algorithms that act on different data continuously is a simpler way to explain RPA in the BFSI industry.
RPA, when deployed in the banking and financial sector, is a technology, or better still, a collection of software robots (bots) designed to carry out regular financial duties. These could involve data manipulation, data transfer across programs, triggering reactions, or authorizing transactions. These bots execute these jobs quickly and in large volumes without error.
Thus, assisting a financial institution manage the enormous demand to deliver a positive client experience and increase efficiency. You could call it an agile method for removing human scheduling and scalability problems, cutting HR costs, and lowering employee onboarding and training expenses.
However, RPA in banking is creating room for CFOs and staff to concentrate on more challenging industrial responsibilities.
How is RPA Used in Banking and Financial Services?
There are many uses for robotic process automation in the banking sector.
For example, let’s imagine you want to shorten the time it takes to open a bank account—let’s say it takes 15 days right now.
However, you now want to restructure the procedure for creating accounts to increase customer satisfaction and save on operating costs.
Introducing RPA in the banking and financial sector can quickly turn the account creation time from 15 days to 5 minutes. To get this done, you need to train these bots by writing programs that will automatically do the following:
- Identify missing documents, extract application data from different document types, and more accurately and quickly complete the KYC process.
- connects to numerous old systems using a solitary audit trail account creation procedure
- Recognize and compare user biometrics, images, digital or electronic signatures, and other account validation methods.
When these processes are carefully integrated, users can now create an account online in a matter of minutes. Therefore, eliminating the current manual method for creating accounts; frustrating for both customers and employees.
Let’s consider other RPA use cases in banking and other financial services.
RPA Use Cases in the Banking and Financial Sector
Since RPA can be applied to different financial sectors, there are numerous well-defined use cases in the banking and financial sector.
Here, we will discuss a few of these RPA use cases in the banking industry and other financial services.
1. To Generate Automatic Report
Compliance reports for fraudulent transactions are a standard requirement for banks and other financial institutions. RPA can assist in producing compliance reports for fraudulent transactions in the form of SARs or reports of suspicious activity.
The RPA software makes this possible with its ability to generate natural language and compliance officers’ data. This helps to decrease operational costs and the amount of time needed to compile a report.
2. KYC Implementation
Manually processing the “Know Your Customer” or KYC data collection could be exhausting. This process would require data screening from multiple personnel to ensure that consumer data is accurate.
Banks can automatically gather, screen, and authenticate consumer information with RPA. With RPA in financial services, banks can accomplish this task quickly, for less money, and with less chance of human error.
3. Customer Onboarding Processing
By employing optical character recognition (OCR) to extract the data from the KYC documents, RPA can significantly simplify the procedure. It speedily cross-checks the information customers input in the form and lodges them into the database.
It provides information on every step from registration to account activation. Then provide the processes to start using your financial services for the first time.
With this, staff members can do more work, thanks to RPA automation in client onboarding.
4. Credit Card Processing
Credit card activation is one of the time-consuming processes at banks and financial services. RPA allows banks to issue credit cards to customers in just a few hours.
An RPA can connect with multiple systems concurrently, verify the required data, and run background checks. Afterward, based on the regulations, choose whether to accept or reject the application.
With RPA in financial services, credit cards can now be made available in minutes as opposed to the usual traditional methods.
5. Customer Service
Banks respond to a wide range of customer inquiries. Employees get exhausted from multiple similar questions from customers. Now, this lengthens wait times, which makes customers unhappy. RPA can handle low-priority tasks, allowing the customer service team to concentrate on more sophisticated queries.
Software robots handle service requests, update client records, and gather data and documents from various systems to expedite customer support. Chatbots, voice assistants, and automated call centers are just a few instances of how software automation has transformed customer service.
6. Facilitate Compliance with Financial Systems
The implementation of RPA in the banking and financial sector ensures adherence to banking laws and regulations by both clients and staff. RPA can quickly scan through transactions to find compliance gaps or other irregularities because it operates around the clock.
7. Loan processing
Both customers and financial institutions find loan processing time-consuming due to the regulations, evaluations, and verification procedures.
The sorting of documents, data entry, financial comparisons, quality control, and data verification processes associated with mortgages can all be automated using RPA. RPA in banking reduces the processing time to 10-15 minutes.
8. Fraud Detection
Due to the numerous transactions that banks process each day, it may be difficult for banks to assess each transaction and identify fraudulent behavior. RPA uses some intrinsic algorithms to spot fraudulent transactions; report and forward them to the appropriate departments.
9. Customer ID verification
RPA in financial services facilitates ID validation across several legacy core systems. To automate client verification, RPA fetches information from external databases and centralizes all pertinent accounts or customer service documentation onto a single screen. Then compare and equate possible identification protocols.
RPA can assist with jobs that require verification, such as business registrations and licensing.
Conclusion
In today’s hostile financial industry, gaining and keeping consumers is the secret to success. And customer loyalty extends beyond simply handling their financial transactions. RPA in the banking and financial sector is one way to ensure a dynamic and flexible customer experience.
With RPA in the BFSI industry, customers can submit applications during the day or night with minimal hassle. Additionally, customers can promptly transfer money, pay bills, inquire about recent transactions, and handle other aspects of their accounts.
