RPA in finance: 10 use cases, benefits & challenges

July 16, 2024

Home
RPA
RPA in finance

RPA Business Analyst

RPA in finance refers to the use of software bots to automate manual, repetitive tasks, such as financial data entry or payment processing. Besides common rule-based activities, RPA bots complemented with AI can execute more sophisticated tasks like client onboarding and fraud detection.

Accounting and finance departments manage an immense amount of daily paperwork and handle various clerical tasks such as accounts reconciliation and financial statements preparation. Therefore, implementing robotic process automation solutions helps businesses reduce the cost of operations, accelerate finance and accounting processes, and ensure compliance with strict financial and tax regulations.

RPA in finance: market stats

Scheme title: The average level of automation in finance offices
Data source: auditoria.ai — 2023 State of Automation in the Finance Office Report: Full Throttle for Finance Automation

$17.6 bn

the expected global RPA in finance market size by the end of 2030

Verified Market Reports

36.81 %

revenue share of the BFSI sector in the global RPA market

Precedence Research

87 %

of SMB financial decision-makers agree that automation is the key to improving business efficiency

SMB Group

10 RPA use cases in finance

P&L reporting

P&L reports, which summarize the revenues and expenses over a given period and involve combining several individual reports, are susceptible to inaccuracies and errors when done manually. RPA solutions can help finance teams automate data collection, validation, integration, and other tasks the creation of P&L reports implies, increasing their accuracy. As revealed by the leading RPA platform provider and our partner UiPath, bot deployment can significantly reduce handling time and help achieve an accuracy rate of 100% in report generation. 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 & asset management

Wealth management companies and other financial institutions can use software bots to streamline investment management activities performed on a daily basis. Investment managers regularly receive estimates from brokers via email. After that, they have to manually merge and enter this data into master spreadsheets to perform financial planning and forecasting and optimize their clients’ portfolios. AI-enabled software robots can accelerate the process by autonomously opening emails, extracting relevant data in any format, and transforming it into reports with valuable insights into the stock market’s trends.

Reconciliation

Bank reconciliation involves matching the actual bank account balance with the balance shown in the latest bank statement. When done manually, reconciling a bank account is prone to human errors, reducing process efficiency and leading to costly mistakes. AI-enabled RPA bots can cross-check the cash flow, search for any inconsistencies between payment details and bank records, and trigger requests for further record validation. If there are no discrepancies, bots compile and send reports for an administrator’s approval.

Accounts payable

Processing multiple invoices from different channels is a challenge for any accounting department. What is more, accountants have to process invoices quickly and accurately to improve invoice turnaround time and accelerate cash flows. Organizations can use intelligent automation to extract data from invoices of different formats and re-enter it in a standardized and easily accessible format. These bots can then route the reworked invoices to accountants and, if necessary, send a reminder in case of a late payment. 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

The accounts receivable team has to generate and distribute invoices, match invoices to purchase orders, process payments, email customers for invoice acknowledgement, as well as create routine AR reports. Companies can use custom accounting applications with integrated RPA capabilities to automate most of these activities, reducing the time required to collect payments and increasing financial data accuracy.

Tax reporting

Tax reporting requires the highest level of precision, as an accurate process facilitates smooth audits and helps businesses avoid legal penalties and fines. Software bots can easily perform most of the tax accounting and financial reporting activities. By automating data collection from multiple sources, tax fillings, tax payments, and other activities, RPA bots reduce manual work, which contributes to the company’s legal compliance and financial stability.

Compliance reporting

Banks and investment companies must comply with an array of regulations that often change over time. On top of this, organizations must regularly report on their performance and activities to ensure they adhere to applicable regulations and laws and stay transparent in how they conduct business to maintain the trust of stakeholders, investors, and the general public. Bots can automate the collection and aggregation of data, including financial transactions and customer information, from different sources to generate reports compliant with regulatory standards. They can also monitor financial transactions and data processing activities and alert compliance officers in case of violation.

Fraud prevention

When it comes to online banking and payments, fraud remains a major issue. Therefore, software bots that can detect suspicious events quickly and accurately are becoming an invaluable asset for businesses. AI-powered RPA-driven bots can cross-check payment details against government and corporate fraud databases, identify unusual payment patterns, and spot inconsistencies between payment details and bank records. Additionally, intelligent software bots can analyze customer behavior to identify suspicious activities based on predefined criteria. This ultimately 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 real-time and historical data extraction and validation, reconciliation, and transaction monitoring, bots can accelerate compiling audit reports and compliance documents. Additionally, RPA bots can quickly detect errors and highlight discrepancies in the reported figures. Intelligent RPA software can also document each step of the audit process creating a comprehensive audit trail, enhancing process credibility and transparency. 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.

Customer onboarding

Because of the process complexity, financial services organizations traditionally spend too much time and effort onboarding new clients. With the help of RPA, companies can automate mundane tasks such as verifying customer data accuracy, setting up accounts, and performing background checks. Such automation accelerates the KYC procedures and reduces the onboarding time, allowing organizations to focus on customer service to improve customer satisfaction and increase engagement rates.

RPA + AI at a glance

In this video, Itransition’s experts demonstrate how the UiPath bot integrated with the Open AI model automates invoice processing.

Get a free PoC to assess the business value of RPA for your company

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. Like many financial organizations, the bank faced the problem of its employees spending too much time on daily reporting, preventing them from performing more important and cognitively-demanding tasks. The bank implemented RPA to automate the entire reporting process, which saved 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

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 adopting an UiPath’s RPA bot, 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

Finance Manager, Fleet Innovation

Micro Focus

Micro Focus is a British multinational software development company with more than 11,000 employees worldwide. The company had to control their multiple general ledger activities, which involved a lot of manual copy-pasting, data validation, and report generation. 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

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 can 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 workflows

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 RPA 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.

Benefits of RPA in finance

RPA technology continues to transform the financial sector. These are some of the benefits companies can reap by integrating RPA into their finance operations.

Reduced operational costs

Automation of manual processes and elimination of redundant, labor-intensive tasks leads to significant cost savings.

Eliminated human error

By removing humans from certain processes and enabling consistency in process execution, companies can avoid costly mistakes.

Improved customer experience

RPA implementation helps quickly address customer inquiries and reduce waiting time, enabling superior customer experience.

Streamlined compliance

RPA implementation simplifies adherence to regulatory requirements by facilitating audit trails, data management automation, and business process standardization.

RPA in finance: implementation challenges

Challenges

Solutions

Intricate legacy system architecture

Legacy systems often lack flexibility in terms of integration with third-party systems or introduction of new workflows. Therefore, organizations should start RPA implementation with a careful audit of the existing IT infrastructure. Once the comprehensive assessment of the current environment is conducted, companies can accurately define the project scope and outline possible workarounds.

Lack of process standardization

To ensure process standardization, which is crucial for RPA development, organizations should invest in a thorough documentation process as well as 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.

Improve your operational efficiency with RPA

As organizations continue to realize the benefits of RPA in finance, we'll likely see more businesses integrating this technology into their operations. We also expect improvements and increasing accessibility of artificial intelligence and machine learning services to make RPA even more powerful in the near future.

Contact us today to find out how we can help you unlock the power of robotic process automation and improve your operations.

Automate your processes with professional RPA experts

Get in touch

FAQs about RPA in finance

How much does RPA implementation cost?

The average cost of RPA adoption ranges from $20,000 to $50,000 per bot. The cost of implementing RPA technology varies depending on such factors as:

Chosen RPA tools and licensing types
IT infrastructure costs including costs for servers/cloud resources
Implementation vendor expertise
Change management efforts and employee training costs

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

The most popular RPA platforms for finance are UiPath, Automation Anywhere, and SS&C Blue Prism. Itransition’s RPA experts can help you customize these platforms to tailor them to your unique business needs and objectives.

Insights

Using AI to scale wealth management

Discover how wealth management companies use AI to generate more leads, automate back-office tasks, improve customer relationships, and improve bottom lines

RPA in insurance:
10 use cases & adoption guidelines

Insights

RPA in insurance: 10 use cases & adoption guidelines

Discover RPA’s applications, pay-offs, recommended platforms, best practices, and challenges in the insurance industry.

BPM vs RPA: can they be compared or combined?

Insights

BPM vs RPA: can they be compared or combined?

Let's clarify the divergent nature, scope, and impact of BPM vs RPA, along with the potential synergies between them.

UiPath vs Automation Anywhere: which RPA platform deserves the crown?

Insights

UiPath vs Automation Anywhere: which RPA platform deserves the crown?

The challenge between UiPath vs Automation Anywhere to lead the RPA market is underway. Who is the strongest contender? Let's find out!

RPA in healthcare:
use cases, benefits & challenges

Insights

RPA in healthcare: use cases, benefits & challenges

Learn how robotic process automation streamlines processes in the healthcare industry and improves care delivery. Explore top RPA vendors, use cases, and costs.

Machine learning in banking: 8 use cases and implementation guidelines

Insights

Machine learning in banking: 8 use cases and implementation guidelines

Learn how banks can apply machine learning to improve customer engagement, streamline compliance, and drive more revenue.