How is RPA used in Finance and Banking?

The use of robotic applications to supplement (or replace) human labor in the financial industry is known as Robotic Process Automation, or RPA. Banking and accounting departments benefit from RPA by automating routine manual activities so that staff may concentrate on more important work and the company can acquire a competitive edge.

 

There are restrictions on what can be done with a simple rule-driven robotic process automation. To automate tasks, it merely adheres to the norms without changing them. It could log into an account, transfer some files, and then log out.

 

Banks employ intelligent automation by integrating artificial intelligence technology, including machine learning and natural language processing capabilities, to further improve RPA. This makes it possible for RPA software to manage complicated operations, comprehend spoken language, identify emotions, and adjust to real-time data.

 

The greatest opportunity for automation in finance, according to McKinsey, is in general accounting procedures. The percentage of automation for business development tasks is only 56%.

 

What is Robotic Process Automation (RPA) in Banking?

 

RPA is a technology that helps businesses automate manual processes so that banks can remain competitive in a developing market. Customers will have access to an RPA banking system that will enable them to perform payments, deposits, withdrawals, and other financial activities automatically without requiring human participation. RPA allows banks to see a return on investment extremely rapidly.

 

Banks can replace a lot of tedious human tasks by integrating banking automation with artificial intelligence. Forrester predicts that this market will surpass $2.9 billion in 2021.

 

As technology advances, RPA fully manifests in banking. Digital banking, cryptocurrencies, and mobile payments are all becoming more and more popular. These are only a few instances of RPA in banking. For many banks, these digital transformation initiatives are still at the top of the list, and they will continue to fuel the overall technological advancement of the banking industry.

 

RPA is being used by banks to handle repetitive operations like data input and customer support. We have to be accessible all the time in the world we live in. Thinking that a real person will be available so that RPA bank bots can fill in for them is simply illogical. We can teach these robots to become more customer-aware over time and offer better service by utilizing AI and automation.

 

Traditional IT initiatives sometimes require new infrastructure before they can start. But basically, no new infrastructure is needed to utilize RPA in banking. To start enjoying the advantages, banks may make use of their current IT infrastructure. As a "minimally intrusive" solution that effectively leverages existing infrastructure, RPA has the unique ability to utilize the natural user interfaces of existing legacy systems to carry out its automated operations.

 

Banks have been able to cut paperwork as a result of data digitization. RPA may gather important analytical data by swiftly scanning through pertinent material. There are several RPA applications available that offer drag-and-drop technologies to automate operations with little to no programming. Similar to this, bots labor nonstop to handle data entry, payroll, and other menial chores so that people may concentrate on more strategic or creative jobs.

 

RPA can assist banks in enhancing their customer service. Customers no longer need to contact employees to find solutions to numerous frequent issues. RPA robots are capable of swiftly analyzing consumer problems and responding to their inquiries. The banking personnel may then concentrate on dealing with the trickier consumer situations. Additionally, since robots are accessible around-the-clock to assist customers, customer satisfaction has considerably increased.

 

Similarly, other lengthy procedures can be sped up. RPA, for instance, can save the time it takes to process loans, making clients happier and more likely to do business with the bank.

 

Benefits of RPA in Banking and Finance

 

In a variety of sectors, including healthcare, manufacturing, and insurance, robotic process automation is being implemented. The market for RPA was estimated to be worth $1.57 billion globally in 2020, and it is anticipated to grow at a CAGR of 32.8% from 2021 to 2028. According to Gartner, 80% of financial industry leaders are already utilizing RPA in some capacity. Some of the most obvious advantages of financial process automation are listed below:

 

• Enables easy operation scaling when necessary. Robots don't require breaks and may perform longer shifts. During peak hours, they can handle an increase in the number of requests.

 

• Reduces time. Once set up, a robotic application can cut the time required to do particular activities by up to 90%.

 

• Costs are reduced. RPA adoption is expected to result in a 30% cost reduction, according to Deloitte. Accenture has a more upbeat prediction and advises using robotics in finance for some functions to save costs by 80%.

 

• Minimizes intervention from the IT department. It is possible to train employees to control their robotic helpers.

 

• Makes certain there are no additional infrastructure expenditures. Infrastructure modifications are not necessary for RPA implementation in banking and finance. The layer is placed on top of the current banking apps.

 

• Improves the effectiveness of human workers. Robots can complete certain activities up to five times more quickly than humans, according to studies. People may focus on something more satisfying since they do not need to squander time or energy on mundane tasks, which improves employee overall well-being and work satisfaction.

 

• Decreases human error Financial RPA manages the duties it has been given methodically. It will improve output quality by removing mistakes that ordinary employees could make as a result of human nature, such as failing to pay close attention to the task at hand.

 

RPA use cases in finance and banking:

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RPA use cases in finance and banking

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1. Fraud detection:

 

For financial institutions in the US and Canada in 2019, the overall cost of anti-money laundering compliance was $31.5 billion. According to research, highly trained analysts who are tasked with finding such crimes waste about 75% of their time gathering data and another 15% putting it into the system. The ability to automate these activities frees fraud prevention specialists to concentrate on their primary duties.

 

Robotic process automation in finance can aid anti-money laundering investigations further by employing an "if-then" strategy to identify probable fraud. For instance, RPA can flag the account as a possible danger and notify the relevant department if several transactions were performed in a short amount of time.

 

2. KYC Process:

 

Banks are required to complete KYC for each customer, which takes time. To complete this procedure in a compliant way, up to 1000 full-time equivalent (FTE) hours and $384 million are required annually. The investigation of warnings takes time as well because up to 85% of daily alerts are false positives and about 25% require level-two senior analysts to analyze them. Banks are losing €50 million annually due to KYC compliance fines despite all their efforts.

 

The KYC process will be improved by the use of robotic process automation in finance, which will reduce errors that would otherwise need uncomfortable client encounters. RPA will thereby hasten client onboarding and improve customer experience.

 

3. Mortgage processing:

 

One of the most well-known RPA use cases in banking and finance is this one. The Mortgage Reports claims that banks may need up to 60 days to close a mortgage deal. Loan officers must go through several procedures, such as checking their credit, verifying their job, and doing various forms of inspections. 

 

Furthermore, even a minor mistake made by the employee or the applicant might cause the case to go much more slowly. Robotic process automation in the financial industry can reduce the time it takes to handle loans by 80%, which would be a huge relief for both banks and customers.

 

To expedite the processing of mortgages, Radius Financial Group used RPA in banking. Before RPA, processing 30 loans in their pipeline would make loan processors feel overburdened, but now that they have robotic assistants, they are at ease handling up to 50 loans without feeling worried. Radius was able to reduce the cost of loan processing by 70% because of this setup.

 

Even during the COVID period, Radius was able to prosper because of intelligent robotic automation. Compared to the average of the Mortgage Bankers Association, the company's income from loan origination was up 30%. Additionally, the company's net income was roughly 50% higher than the banking industry average.

 

4. Accounts payable:

 

Accounts payable management takes time when done manually since staff members must scan vendor invoices, confirm all the details, and then execute the payment. OCR-enhanced robotic process automation (RPA) in accounting can take over this job. Information from an invoice may be extracted using OCR and sent to machines for payment processing and confirmation. The technology will alert bank staff in the event of problems.

 

5. Automated report generation:

 

Numerous reporting chores, such as monthly closure, reconciliations, and management reports, may be automated with financial RPA.

 

Banks and financial institutions are required by compliance regulations to create reports outlining their performance and difficulties and deliver them to the board of directors. These papers contain an enormous amount of data, making it a time-consuming and error-prone effort for people to create them. Robotics in banking and finance, on the other hand, can rapidly compile data from many sources, present it clearly, and produce error-free reports.

 

Societe Generale Bank Brazil simplified a workflow that previously required six hours of workers' working days by integrating RPA for report production into their procedures. RPA in banking can aid compliance officials in processing reports of suspicious behavior in addition to assisting workers to create reports (SAR). Officers use software with natural language processing skills rather than reading lengthy paperwork by hand. Such a machine can fill out the SAR form with the essential data it has extracted.

 

6. Credit Card Application Processing:

 

Another application area where banks have achieved outstanding success is RPA-enabled automation for processing credit card applications. Customers can receive credit cards within hours because of RPA. RPA Bots can easily move across several systems, evaluate the data, do a number of rules-based background checks, and determine whether to accept or reject an application.

 

RPA is one of the primary technological enablers in the present environment, and several big banks have already started to re-strategize their operating models to utilize automation-led disruption. While many of these solutions make use of RPA for straightforward automation, others are more complex and use a variety of different technologies that are built right into the platform's inherent Hyper Automation support.

 

Conclusion

 

RPA has a promising future in banking and finance. While intelligent automation may handle more difficult jobs, such as evaluating previous client data to identify fraudulent transactions and send alerts, basic chatbots can carry out extremely repetitive chores, such as allowing consumers to purchase new bank cards and update PIC codes.

 

When opposed to large-scale transformations, RPA serves more as an opportunistic and point-based solution that is quick and simple to adopt, which is why certain banks and financial institutions have already started applying it in their operations.

 

Robotic Process Automation (RPA) services, which automate manual, repetitive, and time-consuming processes, have the potential to fundamentally alter the banking industry if correctly implemented. Increased productivity, a substantial drop in mistake rates, and an outstanding turnaround time would be the results of automating such routine procedures.