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Did you know that human error in the banking industry costs an average of $878,000 annually, resulting in 25,000 hours of wasteful rework? It's not surprising that banks want to turn things around.

One option is to use Robotic Process Automation (RPA) development solutions. Are robots actually more efficient than humans? Yes, they can complete specific tasks five times more quickly, reduce the chance of error, operate around the clock, and free up teams to concentrate on more strategic tasks. Robotic Process Automation (RPA) is becoming more popular across industries, including the banking and financial sectors, for this reason.

So, what exactly can you automate in your banking or financial institution? When you've decided on the functions, how do you get started with RPA in banking?

Prepare to learn everything about Robotic Process Automation in banking and finance.

What is RPA in Banking and Finance?

RPA uses robotic applications to supplement human effort in banking and finance.

Simply put, RPA aids banks and financial institutions in the digital transformation by automating repetitive manual processes, freeing staff members to focus on more critical projects that ultimately give businesses a competitive edge and boost customer satisfaction. RPA is a helpful tool for meeting the urgent needs of the banking sector and assisting them in maximizing efficiency by reducing operational costs.

RPA provides the basics required to automate processes. Banks are beginning to use Intelligent Automation to improve RPA. Intelligent Automation improves RPA through machine learning and Artificial Intelligence. As a result, business process automation within banks has been dramatically expanded by the Intelligent Automation sector.

How are Financial Institutions Making Use of RPA?

We can see that the most notable users of RPA's automated processes are banks, financial institutions, and insurance firms. The primary goal of banks and other financial institutions is to improve customer satisfaction to compete with virtual banking solutions continuously. They have chosen to automate their processes because of the intense pressure to increase efficiency and optimize resources. Banks and financial institutions can use RPA for two primary purposes:

⦁ To install end-user device software bots

⦁ To develop a workforce for artificial intelligence

It is crucial to address the sector's demands and improve efficiency by cutting costs with the services-through-software model in the financial sector. They should adopt a strategic approach to seize emerging opportunities in their industry.

"In the upcoming years, there will likely be another wave of automation in which 10 to 25 percent of tasks across banking functions will be carried out by machines and bots, increasing overall capacity."

Predicted by Mckinsey.

The focus of RPA in the financial services industry is routine administrative tasks like copying data from emails into the system. Financial Services operations at the presentation layer include data scraping associated with numerous straightforward functions that take up a significant portion of the day. Many insurance companies and US banks have already implemented it, automating about 800 operations.

Use Cases of RPA in Banking and Finance

Let’s look at some of the use cases of RPA in finance and banking.

Process of Bank Reconciliation

Bank reconciliation is a time-consuming process requiring an extensive manual search for transactional data involving numerous banks and the final balance. To automate various manual tasks, such as verifying each payment entry against bank data and other records, RPA Bots can be created. If the entries are identical, the records are reconciled. However, if there are any discrepancies, the Bots can send the records to be verified further.

Customer Onboarding

One of the most difficult operations in the banking industry is customer onboarding. Manually verifying each customer's identity documents takes excessive time and effort. Furthermore, the Know Your Customer (KYC) process prolongs the process. If this is the case, RPA is the solution.

Robotic process automation (RPA) bots can automate customer onboarding, saving time and increasing work efficiency.

Loan Application Processing

The loan application process is an excellent candidate for automation for banks and financial institutions. Documents for loan and appraisal requests are typically received via email as bundled PDFs. Some vital manual tasks include data extraction from applications, verification against multiple identity documents, and creditworthiness assessment. RPA Bots with artificial intelligence capabilities can be used to extract intelligent data and automate a variety of these manual tasks.

Automated Report Generation

Many banks and financial service providers are using RPA to automate manual report generation tasks and are seeing an immediate return on investment (RoI). Automating the report generation process entails various activities, such as optimizing data extraction from internal and external systems, standardizing the data aggregation process, developing reporting templates, reviewing, and reconciling reports.

Opening and Closing of Account

Account opening and closing have become more straightforward, fast, and accurate since the implementation of robotic process automation in financial services. Automation eliminates potential errors and improves the system's data quality.

Robots successfully check document availability, send emails, update system information, and complete various other tasks. As a result, workers have more time to concentrate on productive operations.

Mortgage Lending

This process is an essential component of the operations of many financial institutions. Like many other tasks associated with document processing, mortgage lending takes a long time. In this procedure, RPA in banks can replace various manual jobs such as loan initiation, data processing, quality control, and more. Companies will eventually accelerate task completion and increase customer satisfaction.

Anti Money Laundering (AML)

One of the best uses of RPA in banking is automating the entire AML investigation process. A single case can take between 30 and 40 minutes to investigate manually, depending on how complex the case is and how much information is available across systems. These repetitive and rule-based tasks can be easily automated with RPA, resulting in a 60% reduction in process turnaround time.

Credit Card Application Process

Automating the processing of credit card applications with RPA has also produced astonishing results for banks. Customers can receive a credit card within hours, thanks to RPA. RPA Bots can easily navigate multiple systems, validate data, perform several rules-based background checks, and decide whether to approve or reject an application.

Customer Service

Banking and financial sector players typically handle a high volume of common client inquiries. Responding to these requests quickly can be difficult for support teams. Companies can reduce turnaround times and optimize internal workflows by implementing automation.

Customers also benefit because they can receive immediate responses whenever they contact an institution.

RPA For Accounts Payable

Handling accounts payable manually takes time because employees must digitize vendor invoices, validate all fields, and process the payment. Accounting RPA with optical character recognition (OCR) can handle this task. OCR can extract invoice data and pass it to robots for validation and payment processing. In case of an error, the system will alert bank employees.

Benefits of RPA in Banking and Finance

According to Gartner, 80% of financial sector leaders already utilize some form of RPA for various purposes. Here are some of the most obvious advantages of financial process automation:

Improved Customer Experience

Positive word-of-mouth recommendations can, without a doubt, make or break a company's reputation.

The banking and financial sectors are not an exception to organizations' general emphasis on the customer experience. But working in a busy industry leaves no time for effective communication and customer service.

The RPA system comes into the picture because it enables banks to use bot technology, which will attentively respond to customer inquiries and provide practical solutions for working with customers. The bots are crucial for automating and processing financial transactions, from customer onboarding through mobile apps to customer retention.

Increased Efficiency and Productivity

Another advantage of RPA systems is how easily and quickly they complete tasks because they listen to and carry out instructions without any room for ambiguity. Robotic accounting procedures don't have any drawbacks, unlike manual ones.

Gartner estimates that banking automation can prevent up to 25,000 hours of unnecessary work caused by human error.

Cost Savings

By removing redundancy and reducing the need for manual intervention, banking and finance companies can significantly cut the additional costs associated with their resources, systems, and workforce.

Employees could easily avoid repeated tasks like entering new data and scheduling manual processes. As a result, using this technology in the financial system can reduce costs by about 20–25% due to increased efficiency, reduced energy use, and shorter processing times.

Lower IT Expenditure

RPA functionalities are not expensive.

No matter their size, financial organizations can integrate digital systems with the bare minimum of functionalities without the help of expert IT teams. Robotic software frequently doesn't require specialized coding knowledge to learn the system's complexities and run them optimally.

The system automates the tasks so businesses won't need more IT specialists.

Increases Human Employee Efficiency

According to studies, robots can complete tasks five times more quickly than humans. People can focus on something more fulfilling instead of wasting time and energy on mundane tasks, which raises employee well-being and job satisfaction.

Banks and Financial Companies Using RPA

Following are some examples of banks and financial companies using RPA in their operations.

Zurich

By implementing RPA, an international insurer, Zurich could free up to 40% of its commercial underwriting process. This has enabled them to concentrate on tasks with high value-added and spend more time on complex policies. Zurich reported that the 50% cost reduction of its pilot program encouraged further implementation. Additionally, it has also won an award for the same.

Overseas Chinese Banking Corporation (OCBC)

The Singaporean bank OCBC has been able to cut the time it takes to re-price home loans from 45 minutes to 1 minute by implementing RPA. Additionally, the bot verifies the customer's eligibility. It offers suggestions for loan re-pricing options and can create a recommendation email for clients.

SunTrust

Headquartered in Atlanta, SunTrust Bank implemented RPA in 2016. To support the implementation of banking RPA technology at that time, the bank reportedly established a group within its IT division.

SunTrust has implemented Pega Robotic Desktop Automation in payment-operations areas like consumer bank cards and wires. The bank noted that among the benefits of robotics were an increase in average transaction speed by 3.8x, a decrease in average training time by 4x, and a remarkable reduction in average error rate by 65 percent.

What are the Challenges?

The industry has to face many challenges. Some of them are discussed below.

Intervention of Automation and AI

Although some accounting processes are still automated, major accounting tasks like gathering receipts and converting bills into financial statements have been automated with the development of artificial intelligence and virtual reality technology.

By implementing an automated method in accounting, operations can reduce labor costs by 25,000 hours while also improving productivity. Although this may be good news for businesses, it has endangered the jobs of accountants.

Competition

Competition is still fierce within the financial services industry. As was already stated, customers prefer more individualized care. Additionally, they want more user-friendly digital systems to be implemented. Any of these programs would have a significant market share for the institutions that offer them. Brand identity and loyalty are less important to consumers today. They care for themselves. Customers will stay with institutions that provide such services.

Organizing Big Data

Big data is both a necessity and a barrier for businesses that provide financial services. Big data is expanding as numerous sources produce more data. Due to the structured and unstructured nature of the received data, these outdated data structures cannot handle the volume. Financial service providers must sort their data to determine what is and isn't useful.

Implementing RPA in Banking and Finance

Identifying accurate and feasible processes is typically the first step in implementing the RPA solution in banking. Banks and finance companies must carefully select the procedures that will have the most significant overall impact.

Thorough Assessment

First and foremost, a thorough assessment and detailed analysis are required to shortlist the processes suitable for RPA implementation. Make a list of the significant operational issues RPA can address and resolve, then assess their impact and feasibility.

Make a Business (Use) Case

In the next step, calculate the cost component and efficiency gains delivered by RPA implementation in your organization. Additionally, compare the benefits of RPA based on various metrics such as time, efficiency, resource utilization, and efforts. Also, to avoid disappointments due to misaligned expectations set achievable and realistic targets in terms of ROI (return on investment) and cost-savings.

Prepare a Comprehensive Executive Strategy

Choose an appropriate operating model and workforce to manage the execution based on your organizational needs. At this stage, it is critical to identify the right partner for end-to-end RPA implementation, which includes planning, execution, and support.

Remember that not all RPA vendors suit an organization's specific needs. Choosing the right RPA tool and implementation partner can significantly impact the project's outcomes.

Conclusion

The finance sector is currently being revolutionized by innovation. Because of this, the market is competitive and needs products that satisfy rising customer demands. RPA has been shown to increase operational agility while digitizing manual tasks in core banking functions. Although it may appear to be a significant investment, given the benefits it brings to the company, it can yield a positive return on investment (ROI) within a few months of implementation.

Is your bank considering an automated solution to help it meet the demands of the modern world? If you're thinking about it, contact us today to discuss how RPA can improve your business.