How Robotic Process Automation is Transforming Key Banking Functions and Financial Services

How Robotic Process Automation is Transforming Key Banking Functions and Financial Services

Robotic Process Automation (RPA) is growing at a rapid pace and transforming every industry. Banks are increasingly adopting Robotics Process Automation to become agile, competitive, and profitable. Businesses are realizing their potential and integrating it into their daily operations to stay competitive.

Banking and financial services aren’t an exception to the ever-growing demands of the consumers and the need for quick mechanisms, workflows, and processes to, in turn, offer fast-paced services and solutions. Although relatively a new technology, RPA (Robotics Process Automation), with the concept that it boasts, looks extremely promising and beneficial when it comes to its operational and strategic advantages to various industries.

The modern banking sector isn’t confined to account openings, cash deposits or the loans vertical. It has grown exponentially to launch various departments including credit card, recovery, contact center, fraud detection, and so on and so forth. Strategically, the criticality of each department does not approve of manual operations, and even if the bank tries to do it forcefully, there are chances that the bank may lag behind in the race, and therefore only end up losing customers. Yes, as a solution to this, RPA has become that important!


Significance of RPA in the banking sector?

RPA addresses the key challenge of attaining efficiency but keeping costs as low as possible. But within the banking sector, this goal comes with an additional complexity of maintaining optimum security levels. To meet these demands, RPA(Robotic Process Automation) has become an effective tool. It has taken forward the transition from service-through-labor to service-through-software.

The Financial sector has adopted Robotic Process Automation –most banks follow a process of integrating web robots for increasing efficiency and accuracy of data. And all this while cutting costs and reducing risk of non-compliance and security breaches. Web robots are, in simple terms, software applications designed to emulate what humans can do, but faster, error-free and more efficiently. RPA is finding application in not just banks, but other related financial services as well.


How does RPA work in the context of banking?

The use of software Robots to automate mundane, repetitive tasks. RPA uses software robots or software to perform several tasks like automating transactions, data-processing, establishing communication with systems, performing huge calculations without errors, and fast problem-solving. The banking industry is exploring the potential of this technology in order to breakdown proper jobs,reduce human-induced labor, continuously increase productivity, improve efficiency, and perform rather time-consuming jobs faster. RPA tools and software are capable of mimicking human actions and replicate them to perform tasks that are repetitive in an accurate manner. RPA has proven to be quite efficient in handling work overflow and tasks involving heavy data. Some examples of use of RPA in the banking sector include.


  • Collecting and validating customer data for KYC
  • Automating the process of onboarding a new customer – RPA is being used in the Retail Banking scenario to collect information from the customer, provide data to the customer service exec in the bank to be able to take a decision on opening an account, approving a loan application, conducting the credit checks and more.
  • RPA has been used to automate anti-money laundering checks.
  • To keep track of data and its audit trail for compliance purposes and meeting regulatory standards.


Key banking functions getting transformed by RPA:


Daily operations:

The banking industry deals with the heavy volume of data. Manual processing of this data is a time-consuming and error-prone process. Further, the manual input of data from legacy software to newer models delays daily operations. RPA facilitates seamless communication and transfer of information from legacy to newer software. It automates menial and repetitive tasks, thereby reducing the turnaround time in processing a request. As per reports, banks have been able to reduce their turnaround time from days to hours and even minutes. In addition, the processing cost has been reduced by 30 percent to 70 percent.


Customer service:

Banks deal with multiple queries every day, ranging from general information to account inquiries to complaints, and so on. If a bank aims to be seen as customer-centric then it is extremely important to resolve all these queries in real-time. RPA helps in resolving the low priority queries, freeing up the staff to focus on high priority queries that require human intelligence. That is not all, RPA fast-tracks the customer on-boarding process by reducing the time taken to verify customer details from disparate systems. This reduces the waiting period, and quick grievance redressal helps banks in improving customer relations.


Risk and compliance management:

The banking industry deals with a stream of complex and expansive regulations, tighter deadlines, spanning KYC, financial reports, risk assessment reports, periodic disclosures, and so on. With the stringent regulatory guidelines, banks are looking at RPA solutions to increase efficiency and reduce compliance costs. RPA solutions automate manual and repetitive reporting requirements of upcoming and existing regulations that mandate frequent disclosures. It also enables operational agility to scale up or down as per changing regulatory expectations.


Loan processing:

Underwriting is the most crucial step in lending. It means predicting if a potential borrower would be able to pay back. However, often banks get it wrong because they rely on inaccurate information. The manual process of collecting information is tedious, complex and error prone. RPA powered software enables the compilation of a prospect’s record from multiple systems, websites, channels, and service providers. Once the data is collected, it is entered into a company’s systems for underwriters to analyze it.