All About RPA in Finance and Banking

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Human errors are causing 25,000 hours of avoidable rework for enterprises in the financial sector, amounting to an estimated $3.1 trillion in wasted cash annually—something that can easily be rectified with robotic process automation (RPA) in finance.

Given these statistics it’s easy to understand why 80% of finance leaders have already implemented or are planning to implement RPA, according to Gartner Research. By using robotics to automate manual tasks, RPA helps financial institutions, including banks, cut out manual work so they can boost productivity and reduce errors and costs.

In fact, a 2017 McKinsey study found that general accounting operations have the biggest potential for automation, while in the coming years RPA will complete up to 25% of banking tasks. This will free up staff in the field from mundane activities so they can focus on higher-value work.

RPA in Finance and Banking

Despite the potential, automation has been more difficult to implement in banking and finance than other industries because a high amount of human intervention has been required to secure accounts and transfers. Digital solutions were not robust or intelligent enough to replace manual human activity. With the evolution of RPA, that is fast becoming a problem of the past.

As this article will demonstrate that, the benefits of RPA in finance and banking are myriad, and on the flip side, failing to invest in RPA and staying encumbered with manual data entry will likely see businesses fall behind competitors and lose staff who’d rather be doing more strategic tasks.

Contrary to popular belief, robotic process automation in banking is not about reducing headcount, but rather reallocating staff working on manual tasks to more engaging work that unlocks new value for the company.

It’s this value-added work that can help companies in the banking and finance sectors gain a competitive edge. These companies become more efficient and scalable while improving the customer experience through faster, less error-prone, more cost-effective services.



What’s Unique About Robotic Process Automation in Banking and Finance?

Ultimate Guide to RPA in Finance and Banking

Robotic process automation in finance can be traced back to the 1990s with optical character recognition (OCR) technology, which reads handwritten checks accurately and quickly.

From there, RPA was developed into enterprise resource planning (ERP) and customer relationship management (CRM) platforms. It is being used to analyze data, trigger response-based actions, automate intersystem communications, and more.

RPA requires considerable training, governance and implementation know-how. However, when it’s up and running, robotics can provide immense long-term value that continues increasing as companies scale. In the banking and finance industries, the benefits come in the form of reduced manual work, improved compliance and risk management, and a better customer experience.

Furthermore, thanks to its “low-code” nature, robotic process automation in finance and banking does not require these institutions to overhaul their complex technology infrastructures. Instead, it can be installed on top of existing systems, making it a lower-hanging fruit option than other digital enhancements.

How RPA Works

At its most basic level, RPA is a rule-driven method that is limited in its application. It follows set rules, similar to how an Excel macro works, to do things like move files or log into accounts.

Robotic process automation and Artificial Intelligence (AI) in financial services and banking pair machine learning algorithms with rule-based robotic processes. For example, this could add value when you use RPA with AI to read and process PDF invoices or check wire transfers. Used together, they can “review” documents, flag issues, and learn from repetition to operate flawlessly.



What You Need to Operate Robotic Process Automation in Finance and Banking

Running robotic process automation financial services requires a virtual machine to power the robot and the same access to associated systems, as well as licensing, that a human user would need, including:

  • Caseware
  • CCH
  • Email
  • File shares
  • Security (eg. Microsoft AD)

Here’s one way to look at it: Robots only differ from employees in that they don’t need a badge to enter the building, they don’t require a salary and benefits, and they aren’t powered by coffee. 

We’ll look deeper into the “how” later, but first let’s cover how robotic process automation in financial services can be used in more detail.

Insights Into RPA in Finance and Banking 

The global RPA market in financial services is set to grow to $4.8 billion by 2030, according to Allied Market Research, up from just $340 million in 2020. This is a clear sign of the major appetite for the technology, and it has been adapted by many leading players in the space, such as BNY Mellon.

7 Ways to Use Robotic Process Automation in the Financial Industry

Robotic Process Automation in Banking and Finance?

1. Handling Mortgage and Loan Processing

Processing mortgages and loans is among the most common uses of RPA in banking and finance. Closing a mortgage loan can take up to 60 days, according to The Mortgage Reports, with loan officers required to go through steps including employment verification, credit checks, and inspections.

One error at any part of the process can cause delays to an already time-consuming process.

RPA can reduce the time taken to process mortgages and other loans by 80%. This is thanks to automating critical steps, including:

  • Loan initiation
  • Document processing
  • Financial comparisons
  • Quality control

This results in lower costs and happier customers and staff.

2. Conducting Know Your Customer and Fraud Detection

Robotic Process Automation in Finance and Banking

Know your customer (KYC) is a laborious but crucial requirement for banking and financial service providers. Each customer needs to be examined to ensure they are who they say they are, and that they’re not attempting to conduct fraudulent activity.

Unfortunately, the nature of KYC means that 85% of alerts are false positives, while 25% need to be escalated to senior analysts.

Even with these efforts, banks are still losing over $50 million per year on KYC compliance sanctions. RPA can cut out this manual work and save time and money by eliminating the tendency for human error and uncertainty associated with KYC processes.

In terms of fraud detection, it’s been estimated that analysts are spending 90% of their time collecting and entering fraud-related data into the system. RPA can automate this work, as well further enhancing anti-money laundering (AML) tasks by using “if-then” rulesets to identify potential fraud activity, such as many transaction attempts in a short time period.


Case Study: Antares Capital

In this robotic process automation in banking case study, 1Rivet implemented an Azure PaaS-based solution along with self-learning RPA using UiPath and Azure machine learning to perform activities related to the cash-matching process.

This project uses a self-learning model, so if the system does not have the appropriate information to identify a customer from a wire instruction, it allows the back office user to identify the customer. The system learns from this user intervention, allowing it to automatically detect the customer in the future.

For more robotic process automation examples in banking, see all our case studies.


3. Managing Customer Onboarding and Account Opening

Onboarding customers can be time-consuming, repetitive and prone to issues. It can also be a frustrating process, as customers are required to submit several documents that then have to be manually verified by staff.

Finance robotic process automation simplifies the onboarding process by automatically reading data from KYC documents using optical character recognition (OCR). If OCR finds no discrepancies, the customer’s data is automatically entered, saving significant amounts of time and effort for staff.

Closely related to customer onboarding, RPA accounting can make your opening processes easier and faster. . Having robots enter data by reading documents cuts out errors to improve data quality, while minimizing issues and delays.

4. Performing Intercompany Reconciliations

Robotic process automation in the financial industry can help companies balance their accounts and provide accurate financial statements. 

Currently, this work requires significant manual data entry and painstaking cross-checks, leaving it open to errors and missing information.

By automating the acquisition and checking of transactional data, approval of matching records, and notification of discrepancies, RPA can solve the headache of intercompany reconciliations once and for all.

5. Getting Documents and Sending Follow-Ups

RPA in banking and finance

One of the most frustrating problems for banks is the number of accounts they are forced to close because customers fail to send the required documents to verify their identities and standing.

Robotic process automation in finance can be used to track account status and send out automated follow-ups and reminders to ensure customers know what they need to send and remember to do it. RPA insurance for setting up new user accounts and processing transactions is a great example of Robotic Processing Automation.

6. Generating Reports

In order to remain compliant with regulation, banks are required to prepare reports regarding their performance and activities. These reports contain vast amounts of data, making them time-consuming to produce and (potentially) filled with errors.

Robotic process automation and banking can remove these issues by automatically gathering data from the necessary sources, arranging it into a coherent format, and producing the reports with no mistakes. This saves both time and money.

In addition to performance reports, RPA can be used to automate suspicious activity reports (SAR). This can ease the burden on compliance officers having to read long documents by giving them access to technology that can extract the required info and enter it into a SAR form.


Case Study: UHY

1Rivet helped UHY automate generation of their EFS (tax) and workstream reports on configurable scheduled dates. Once these reports were generated, a robot created and sent individualized reports to each employee.

The robot is scheduled to run at predefined times and generate reports from Access Workstream. The reports can also be triggered outside the pre-defined dates by sending an email to the robot.

Read the full case study to learn more about this robotic process automation banking use case.


7. Processing Accounts Payable and Receivable

Accounts payable (AP) is a time-intensive process that requires time and labor to hand over over the company’s money. RPA, enhanced with OCR, can be used to accurately read invoice information and pass it to robots for validation and payment processing. Employees tasked with this work can then be reallocated to perform more value-added work.

On the accounts receivable (AR) side, RPA can help to improve the day’s sales outstanding (DSO) metric, which has traditionally relied on payee and recipient humans to cooperate. If a payee forgets to send an invoice, a cash gap opens up, which can affect liquidity if it happens too often. RPA cuts out the problem by automatically sending out invoices.

Case Study: Segal McCambridge Singer & Mahoney

1Rivet helped Segal McCambridge Singer & Mahoney automate the invoice generation and uploading process for their e-billing team.

The automation process starts when the e-billing team sends an email to the robot with the client’s name. The robot extracts and prepares invoices, then uploads the invoices to a client-specific e-billing platform. Once this entire process is completed, the robot sends a status email to the billing team.

Read the full case study to learn more about this robotic process automation finance use case.


To summarize, you may have noticed that most of the robotic process automation use cases in banking and finance are related to saving time, reducing effort, cutting out unnecessary costs, and freeing up your staff to do more valuable work.

As we like to say, RPA is about automating all the “stupid little things” that distract from the core business.

Benefits of Robotic Process Automation in Banking and Finance

The business models for banking and financial services companies rely heavily on repetitive manual data processing, making the industry a natural fit for RPA.

Thus, this space is where some of the most profound benefits of robotic process automation in banking  have been achieved. In this section, we’ll take a closer look at some of these benefits and what they could mean for your business.

8 Benefits of RPA in Finance

1. Scalability

Robots can handle much higher volumes than humans at a fraction of the cost, meaning scalability is far easier. Robotic process automation in the banking sector allows you to scale up and down to adapt to fluctuating volumes in the most cost-efficient possible way, and they can work 24/7 without breaks.

The scalability enabled by RPA opens banks and finance firms up to whole new worlds of sustainable growth, allowing them to gain competitive advantages in this fierce market.

2. Customer Experience and Employee Engagement

Consumers have a wealth of options in today’s banking and financial services markets, and have come to expect seamless, fast, and personalized services with top-class support. RPA enhances the customer experience by making everything from onboarding to transfers faster, error-free and trouble-free.

On the employee side, staff engagement improves because they’re given more interesting work to do after repetitive tasks are automated. In our experience, it’s rare that companies fire people after implementing RPA, but instead focus them on working with clients, upselling services, and providing intelligence and insights.

3. Agility

Deploying RPA on the cloud can be done in around four weeks for smaller projects if the proper pre-planning has been done. Then you can quickly switch robots on and off depending on your needs. Unlike human staffing, robots are highly agile, and drag-and-drop tools for robotic process automation for financial services allow you to easily manage workflows with minimal coding requirements.

4. Operational Efficiency

One of the most highly praised benefits of RPA is that it can hugely improve the efficiency of performing the manual, labor-intensive tasks that are the bread and butter of banks and finance firms. These tasks can be automated away completely in some cases, or reduced by up to 90%.

If you consider that some processes in banking and financial services, like setting up and transferring a loan, require dozens of steps, the compound effects of automating even a few of those steps are enormous when they are being performed at a high volume.

5. Cost Savings

Robotic Process Automation in Banking and Finance

According to Deloitte, banks and finance companies can reduce their expenses by 30% through RPA, largely because of the reduction in errors and manual work.

That is the most basic way of looking at it, but you can also think about the cost efficiencies that come from refocusing employees on more value-added work.

6. Risk and Compliance Reporting

Robotic process automation in retail and commercial banking helps banks create full audit trails for all processes, reducing risk and improving compliance. 

By consolidating data from disparate systems and documents, robotic process automation for the finance department makes it easier to complete accurate compliance reports, reducing the chance of regulatory fines or reputational damage caused by poor compliance.

Adding machine learning can take it a step further by helping an auditor decide what to review and make faster decisions.

In terms of combating fraud, RPA automates due diligence checks, sanctions screening and transaction monitoring and investigations, greatly improving the speed and accuracy of detecting and dealing with fraud.

Finance robotic process automation can verify whether data is in line with AML guidance, and machine learning helps to analyze variances and automatically raise red flags.

7. Availability

Benefits of RPA in Finance

This benefit is direct and simple: one of the main benefits of robotic process automation in banking is that they bring 24/7 availability, meaning you can process enormous volumes of data around the clock with extreme accuracy at low cost.

This is what banks and finance companies have always dreamed of.

8. Zero Infrastructure Cost

Cloud-based RPA doesn’t come with a major upfront investment, making its long-term ROI even more enticing. All you need to pay for on an ongoing basis is the RPA software license, the virtual machine, and your RPA-managed service.

Furthermore, when using a managed service, the robots sit on the client side of the firewall and don’t send any data outside, alleviating the security concerns that are always front of mind for banking and finance companies.

Implementing RPA in Finance for Your Organization

Broadly speaking,  the steps required for banks and financial institutions to implement effective and secure RPA services include:

  • Education: Figuring out what you need (How many robots do you need?)
  • Discovery: Understanding where and how you can automate
  • Estimates: Defining costs and what fits in your budget
  • Prioritization/planning: Creating a roadmap to implement and maintain RPA
  • Design, build, test, deploy: Engaging a partner to design, build, test and install your solutions, procure licenses, manage robots, manage and monitor processes 24/7
  • Post-implementation support: Setting and adjusting robot task prioritization

To be RPA-ready, you will be required to invest in:

  • Virtual machine(s) to run your robots
  • RPA software (we recommend UiPath)
  • RPA solution design and implementation services (such as 1Rivet)
  • Software licenses for robots (the same as you would need licenses for humans)


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Perceived Challenges of Getting Started With RPA in Finance and Easy Solutions

Some of the most common pain points for banks and finance companies implementing robotic process automation in the financial sector are:

  • Deciding which RPA product to use (again, we recommend UiPath)
  • Finding someone with the expertise to apply that product to your processes
  • Hiring, training and retaining services to manage and maintain your RPA solution
  • Finding a reliable certified RPA partner (again, like 1Rivet)
  • Applying RPA in a sustainable, affordable and efficient way

Here are some steps you can take to overcome these challenges:

1. Make a Solid Plan and Budget Accordingly

By carefully crunching the numbers and determining the cost- and time-saving return on your investment in the robotic process automation and banking solutions, you can accurately assess the feasibility and value of your plans.

Furthermore, by planning properly, you avoid ending up with roboticized chaos, because your processes will be well thought out, rules-based and standardized.

2. Choose Your RPA Platform Wisely

As we’ve mentioned, UiPath is our robotic process automation software of choice for finance and banking because it’s the most effective RPA software for streamlining processes, driving efficiency and providing insights in a cost-effective way. But we encourage you to do your due diligence and do additional research.

Some platforms are more suited to basic levels of automation that do not require pairing with machine learning. Others are more advanced and provide powerful computer vision and machine learning capabilities that can be used for the likes of payment validation and AML.


Learn more about robotic process automation:


3. Seek Out the Right Partner

Finding the right partner is best done by understanding their industry experience, assessing their credentials and level of knowledge, and seeing what they’ve achieved for other companies in your space.

Get a sense of how well-versed the partner is in deploying robotic process automation in the banking sector to automate processes.

4. Be Patient With Legacy Systems

Many banks still use COBOL-based systems, a programming language from the 1950s that is often incompatible with modern technologies. Automated solutions need to be foolproof and available round-the-clock, so make sure you have robust failover and backup procedures.

Layering RPA onto legacy systems with complex processes is a task that can take up to a year to complete. It will require some intensive work, a lot of collaboration, and extensive training for some users. When the solution goes live, all the effort will have been worth it.

5. Take it Step-by-Step

With the massive benefits that RPA can bring, it can be tempting to rush in and try to automate all of your processes at once, instead get a quote from RPA consultants.

By moving too fast, you run the risk of breaking things – the worst nightmare of highly complex banking and finance organizations. Instead, take it step by step, and pause to allow human eyes to monitor and analyze the activities of an RPA solution before moving onto the next.

Robotic process automation in finance is a long-term process that is best done piecemeal.

robotic process automation in the financial sector

RPA in banking and finance is an ongoing process, and not something you can implement in one day and then forget about. Typically, it’s a good idea to focus on automating processes that are bottlenecking productivity or taking up large amounts of time.

Another way of approaching robotic process automation in the banking industry is starting small with more manageable and less complex automations, and then advancing to more ambitious processes.

Over time, your operations will become gradually more automated and the repetitive manual work will begin to fade away. This will result in improved efficiency, fewer errors and a smoother, faster customer experience.

Starting on the path to RPA means connecting with a partner that can provide expertise in automating complex banking and finance industry processes. An experienced partner will help you understand where to focus and how to start applying RPA solutions to your manual tasks.

Trust the Experts With Robotic Process Automation in Trade and Finance

Robotic Process Automation in Trade and Finance

1Rivet has helped a wide range of companies, including those in the banking and finance sectors, to build RPA into their systems and processes. We have helped customers to define RPA roadmaps, choose the best tools, create proofs-of-concept, test solutions and go live.

We partner with leading RPA software UiPath to deliver best-in-class solutions and employ certified specialists who deliver on time, on budget and at the most competitive price point.

To learn more about 1Rivet and our industry-leading robotic process automation in investment and banking, check out our free education sessions, analysis, and speaking engagements.

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Eric Middleton

Embodying the 1Rivet culture, Eric asks himself and others daily: "What have you done for the client today?" He’s a passionate leader who brings an innovative approach and a burst of energy to every client organization.