RPA in finance:
10 use cases, benefits, and challenges

RPA in finance: 10 use cases, benefits, and challenges

March 22, 2023

RPA software market stats

market share of BFSI, the leading RPA market segment in 2021

Grand View Research

of finance leaders plan to adopt advanced digital technologies like RPA by 2025

Gartner

expected global RPA market size by 2030

Grand View Research

10 RPA use cases in finance

P&L reporting

P&L reports are a critical component in overall data analysis and reporting processes for any financial services company, as they summarize the revenues and expenses over a given period. However, since these financial statements are compiled by manually combining several individual reports, inaccuracies and errors add up, creating significant headaches for the accounting department.  For this reason, delegating such back-office tasks to bots that automatically compile, validate, and merge reports can be helpful. According to our partner UiPath, implementing bots resulted in a 70% reduction in average handling time (AHT) and a 100% accuracy achieved for one global financial services company.

Investment and asset management

Software robots can also lend a hand in managing investments. For example, in a typical asset management firm, analysts regularly receive updated estimates from brokers via email. This data is manually merged, entered into master totals spreadsheets, and used to create reports and graphs.  RPA bots can completely automate the procedure: they open emails autonomously, extract the relevant data, and process it to create reports with valuable insights into the stock market’s trends.

Reconciliation

Bank reconciliation is a delicate operation that involves verifying the correspondence between the actual balance of a bank account and that reported in the most recent bank statement. Due to its complex nature, however, it often suffers from manual errors and inaccuracies, reducing the efficiency of the process and leading to costly mistakes. Robots can cross-check the cash flow, search for any inconsistencies between payment details and bank records, and trigger a request for further record validation if something is wrong. If, on the other hand, there are no discrepancies, the bots will compile and send a report to the administration for approval.

Accounts payable

Handling vast amounts of incoming invoices from different suppliers and through multiple channels is a challenge for every accounting department. In fact, accounts payable are among the most tedious and error-prone activities, but they still need to be processed quickly and accurately to avoid conflicts with suppliers and increase turnaround time.  In this regard, bots are a precious ally, thanks to their ability to extract data from invoices of different formats and re-insert them autonomously in standardized and easily accessible forms. Furthermore, they can dispatch these reworked invoices to the right accountants and, if necessary, send a reminder in case of late payments.

Accounts receivable

If it's clear that payables to suppliers should be honored on time, imagine the rush that companies go through to collect their receivables. Once again, bots come in handy for streamlining and speeding up accounts receivable activities.

Custom accounting applications with RPA-based capabilities can streamline various processes, including financial data validation, invoice processing, emailing customers, and creating reports. This way, the time required to collect payments (namely DSO) is significantly reduced, avoiding annoying cash gaps.

Tax reporting

The next meaningful use case of RPA software in the financial and accounting field concerns tax reporting, which requires the utmost precision for apparent reasons of legislative compliance. For bots, however, extracting and combining data from multiple sources to compile the necessary tax documentation is child's play. Major financial institutions have understood the potential of RPA, including Ernst & Young. Their Shanghai branch has developed a similar solution for one of its clients to automate VAT filing tasks and reduce processing time from 1,400 to 280 hours.

Compliance reporting

In the financial sector, compliance is not a matter to be taken lightly. Banks and investment companies need to comply with a massive array of regulations that often change over time. On top of this, they have to report their activities regularly to stay within the boundaries of the law. The use of RPA can streamline this task.  Bots can automate the collection and aggregation of data from different sources (including distributed databases and multiple documents) to generate reports compliant with regulatory standards. Also, they can monitor data movements and activities in real-time, continuously alerting stakeholders if something is wrong or an unexpected event occurs.

Fraud prevention

Fraud constitutes a major issue for financial organizations – especially when it comes to online banking and payments. Here again, robots can prove to be an invaluable asset, as they can detect suspicious events very quickly and accurately. For example, RPA-driven bots can autonomously cross-check payment details against fraud databases, identify unusual payment patterns, spot inconsistencies between payment details and bank records, and analyze customer behavior to identify suspicious activities based on predefined criteria. Ultimately, this helps companies save time and money while increasing their level of security.

Audit processes

Robotic process automation can also improve the accuracy and efficiency of financial audits. By automating manual time-consuming tasks such as data extraction, bots can reduce the time it takes to review large datasets. In addition, they quickly detect errors and highlight any discrepancies in the reported figures.  Furthermore, certain RPA solutions allow for the creation of audit trails and automated alerts to track any changes in financial records, enabling auditors to identify any potential issues quickly.

Client onboarding

Organizations have traditionally struggled to onboard new clients quickly and efficiently due to the complexity of the process. By taking advantage of RPA, companies can dramatically accelerate customer onboarding and KYC procedure by automating mundane tasks such as verifying data accuracy, setting up accounts, and performing background checks.   Automation reduces the time it takes to complete these processes and minimizes the risk of errors that could result in costly regulatory fines. Furthermore, the automation of customer onboarding allows organizations excel in customer service, improving customer satisfaction and increasing engagement and retention rates. Moreover, RPA can streamline new employee onboarding and payroll processing.

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Real-life examples of RPA in finance

Societe Generale Bank Brazil

Societe Generale Bank Brazil is one of the leading banks in Brazil that provides services for both corporate and institutional clients. The financial institution faced a common problem among banks - employees spent too much time on daily reporting, preventing them from performing more important and cognitively-demanding tasks. The bank decided to implement RPA to streamline daily reporting. In partnership with a software development company Fortra, Societe Generale automated the entire reporting process with RPA, saving 6 hours of work per employee per day.

RPA came to join other technological projects aiming at making our collaborators’ work easier and enabling us to offer increasingly better services to our clients.

Mario Lopes

Mario Lopes

CIO at Societe Generale Bank Brazil

Credigy

Credigy, a global specialty finance company, was looking for a way to accelerate its growth with automation. Given that the company has to process thousands of data-intensive documents daily, keeping them in order is paramount. Previously, employees had to manually validate and rename files and move them to appropriate repositories, which was time-consuming and laborious.  Currently, RPA takes care of the entire process, allowing employees to focus on more strategic activities. Besides file governance, Credigy also automated due diligence, invoice processing, and reporting, resulting in a 15% increase in a compounded annual growth rate.

Fleet Innovation

Fleet Innovation, a prominent Finnish car leasing market player, has seen tremendous growth in recent years. However, strong business development resulted in more purchase invoices and more tedious work for employees. Therefore, Fleet Innovation decided to handle the increased number of manual administrative tasks, such as invoice processing, more efficiently with the help of robotic process automation.  After a joint effort with UiPath partner Efima, Fleet Innovation managed to automate the processing of 6000 invoices monthly, which accounts for 45% of the total number of invoices.

In repetitive routine work, a person always makes some mistakes, but the robot can be expected to follow the rules without exceptions.

Jenna Rahunen

Jenna Rahunen

Finance Manager, Fleet Innovation

Micro Focus

Micro Focus is a British multinational software development company with more than 11,000 employees worldwide. The company manually controlled their general ledger activities, which involved a lot of copy-pasting, validating data, and generating reports.  First, Micro Focus used RPA to automate the validation of central bank rates, which now takes 85% less time to complete. Second, the team automated the revelation process for open foreign currency balances. Currently, the RPA bot can navigate Micro Focus’ financial application, identify the right accounting book, check status values for all entries, and automatically handle any exceptions.

RPA makes automation quick and easy. When you select the right business process, start small, and scale, RPA can add immense value.

Sridhar Srinivasan

Sridhar Srinivasan

Strategic development IT project manager at Micro Focus

A step-by-step guide to RPA implementation in finance

1

Analyze the current state

Before automating processes, it's important to assess the current state of business operations. Careful examination of all the existing processes and manual activities related to them will bring visibility into areas where RPA may have a positive impact. In addition, evaluating the current state in terms of cost, speed and accuracy allows for more informed decisions on processes best suited for RPA automation.

2

Identify automation use cases

To identify potential use cases for RPA in finance, examine existing process maps to determine candidate processes that could benefit from automation. Assess each process using a combination of technical feasibility criteria such as complexity, cost, and scalability. Consider the cost savings, speed of execution, and accuracy gains that RPA can provide. Utilize existing data to understand where automation could help reduce manual labor and define any financial or resource constraints.

3

Standardize existing processes

RPA works best when processes are well-defined and follow a consistent structure. As such, it's important to standardize existing processes, ensuring they are reliable and repeatable, to make them easier to automate. Standardization should include defining data sources, setting up standard workflows and task sequences, and establishing defined documentation practices.

4

Establish processes for implementation

Define clear guidelines to ensure each automation project is appropriately planned and executed: the necessary resources are in place, the scope of the automation project is defined, and the expected benefits are quantified. We highly recommend consulting an experienced RPA vendor to ensure your adoption roadmap accounts for all the intricacies associated with RPA implementation in finance.

8 benefits of RPA in finance

RPA is transforming the world of finance. By automating mundane, repetitive tasks, RPA enables financial institutions and insurance companies to free up valuable resources, gain insight into their operations, and streamline decision making. Here are eight benefits companies can reap by integrating RPA into their finance processes.

Reduced operational costs

RPA can automate manual processes and eliminate redundant, labor-intensive tasks, leading to significant cost savings. Without the need for costly human resources, companies can reinvest these funds into more strategic initiatives that drive greater returns in the long term.

Eliminated human error

By removing humans from certain processes, companies can avoid costly human errors and reduce the risk of operational disruption. This is especially important in the world of finance, where the cost of human errors can be astronomically high.

Improved customer experience

RPA helps banks provide better customer service by automating mundane updates and quickly responding to inquiries. It also reduces waiting time for customers by speeding up the processing of data.

Streamlined compliance

RPA technology simplifies adherence to regulatory requirements, enabling financial institutions to track and monitor activities easily. RPA-enabled audit trails are invaluable in such a highly regulated industry as finance.

Reduced IT burden

With sufficient training, it becomes possible for regular employees to set up RPA bots themselves. Citizen RPA development alleviates the burden of reconfiguring infrastructure from IT departments, freeing up time for other essential activities.

Increased security

RPA helps to ensure regulatory compliance and provides enhanced data security by eliminating manual errors and reducing the risk of human-based threats. This enables financial organizations to protect sensitive customer information.

Non-disruptive implementation

RPA bots can be integrated into existing systems with minimal disruption, making them an ideal solution for institutions looking to improve their processes quickly.

Enhanced scalability

RPA can be easily scaled up or down as needed, making it an ideal solution for banks dealing with ever-changing needs. Increased flexibility would allow financial institutions to quickly adjust their processes in order to meet customer demand.

Challenges of implementing RPA in finance

Challenges

Solutions

Lack of coordination between departments

Financial processes are complex. Therefore, it is essential to ensure that all departments work together and are in sync when implementing RPA. Consider establishing a governance structure that defines roles, responsibilities, and procedures. Also, improve communication between teams by re-engineering and optimizing processes and ensuring cross-functional collaboration.  

Lack of process standardization

To ensure process standardization, which is crucial for RPA development, organizations should invest in a thorough documentation process, business intelligence, and analytics capabilities. By taking the time to document each stage of the process, businesses can establish clear definitions and requirements for each task, making it easier to identify discrepancies and errors before they occur.

Intricate legacy system architecture

Complicated legacy systems are not always flexible in integrating other necessary systems or introducing new processes. Therefore, organizations should consider engaging professional consulting services to understand their system architecture better and determine the changes needed for applying robotic process automation most effectively.

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As organizations continue to realize the many benefits of RPA in finance, we'll likely see more financial institutions integrating this technology into their operations. We also expect improvements and increasing accessibility of AI and machine learning services to make RPA even more powerful in the near future. As a result, banks will have access to even greater insights and opportunities as the technology evolves. Overall, RPA presents a viable option for financial institutions to transform their operations and gain unprecedented insight into their activities.

At Itransition, we provide experienced teams that specialize in deploying RPA solutions to enable digital transformation in the finance industry. Contact us today to find out how we can help you unlock the power of robotics process automation and improve your operations.

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FAQs about RPA in finance

How much does RPA implementation cost?

The cost of implementing RPA technology in finance depends on various factors such as the project's scope, vendor expertise, IT infrastructure and RPA platform expenses, and employee training programs. Generally speaking, it is estimated to range between $20,000 and $50,000 per bot.

What are the most popular RPA platforms for the financial sector?

The most popular RPA platforms for the financial sector include UiPath, Automation Anywhere, and Blue Prism. Each of these platforms has a range of features and capabilities that make it suitable for different types of businesses in the finance sector. Meanwhile, professional software providers like Itransition can offer custom platform-based solutions explicitly tailored to individual customer needs.

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