The Rise of RPA In Banking & Finance: A New Era of Automation

The banking industry is experiencing a significant transformation with the rise of RPA in banking finance, marking the beginning of a new era of automation. No longer just a buzzword, RPA is rapidly becoming a vital tool to replace manual processes and mountains of paperwork with automated workflows.

Allied Market Research estimated that the global RPA and hyper-automation market in banking was valued at $745.4 million in 2021 and is expected to rise to $7.1 billion by 2031. This growth shows how RPA has become an essential tool for banks to streamline operations and increase efficiency.

The COVID-19 pandemic further accelerated the adoption of RPA, as remote work pressures forced financial firms to turn to automation to maintain business continuity. Adopting RPA in banking was still nascent a few years ago, but today, it is indispensable for streamlining operations and boosting efficiency.

During the lockdowns, financial firms experienced difficulties; for example, their workload pressures altered with slower and longer account receivables due to most of the people working from home. RPA in the financial sector helped keep companies operational while working from home.

Robotic Process Automation in Financial Services helped keep companies operational while working remotely.

(Image Source: https://www.thebusinessresearchcompany.com/report/digital-process-automation-global-market-report)

As of 2024, the banking market for RPA has an estimated value of approximately $1.12 billion by 2025, driven by the need for cost reduction and process efficiency in financial operations.

Why is automation needed in banking?

In the banking industry, employees often handle large amounts of customer data, and relying on manual processes can lead to mistakes. These big or small errors can cause serious problems like fraud or money laundering. Given the stakes, it’s clear that more reliable and efficient data management methods are urgently needed.

One solution to these problems is Robotics Process Automation in Finance & Banking, which can help streamline such tasks.

For instance, verifying customer information from two different systems can take seconds with a bot compared to several minutes when done by hand. This speed reduces errors and makes the whole process more efficient.

Automated Bank solutions powered by RPA transform the banking industry by automating every repetitive task, enhancing operational efficiency, and improving customers' experiences.

By automating tasks, banks can lower processing costs by up to 70%. Robotic Process Automation in banking streamlines repetitive tasks such as transaction processing, customer onboarding, and fraud detection, enhancing efficiency and reducing operational costs.

Take the account opening process as an example. Normally, this would involve collecting customer details, verifying documents, and inputting data into several systems. With RPA, a bot can automatically pull data from forms, verify it with official documents, and enter everything into the bank’s system.

This makes the process faster and reduces the chance of mistakes, which boosts customer satisfaction and trust.

Understanding the use cases of Robotic Process Automation in Banking would give you a better understanding of different processes that can be automated in firms in the BFSI sector.

Top 13 Use Cases of Robotic Process Automation in Finance

Customer Service

Banks face daily queries ranging from account information to application status to balance information. Banks find it challenging to respond to queries with a low turnaround time. 

Fact: More than 80% of customers who have used chatbots for product inquiries in the last 12 months wouldn't want to use them again—and 46% said they'd prefer to use branches (Deloitte). 

With RPA, rule-based queries can be processed instantly, reducing turnaround time to seconds. AI-powered chatbots with Natural Language Processing (NLP) can provide human-like responses and free up human agents for complex tasks. 

Compliance

Banking is heavily regulated, requiring institutions to adhere to strict compliance measures. According to an Accenture survey, 73% of respondents believe RPA can significantly enhance compliance management. RPA ensures 24/7 accuracy, reducing errors and improving audit readiness. 

Accounts Payable

Processing invoices and payments manually can lead to delays and errors. RPA, integrated with Optical Character Recognition (OCR), can extract vendor details from digital or scanned documents, validate them, and automate payment processing. If discrepancies arise, RPA alerts executives for corrective action. 

Credit Card Processing

Previously, credit card approvals took weeks due to multiple background checks. RPA accelerates the process by communicating with multiple systems simultaneously to verify information, conduct risk assessments, and approve or reject applications within hours. 

Mortgage Loan

It takes around 50 to 53 days to process a mortgage loan in the United States. Approving a mortgage loan involves various checks such as credit checks, repayment history, employment verification, and inspection.  

A minor error can slow down the process. As the process is based on a specific set of rules and checks, RPA can accelerate the process and clear the bottleneck to reduce the processing time to minutes from days. 

Fraud Detection

One of the major concerns of banks regarding digital systems is fraud. It is very difficult for banks to track all the transactions and flag possible fraudulent transactions. RPA can track transactions and raise flags for possible fraudulent transaction patterns in real time, reducing delays in response. In many cases, RPA can inhibit fraud by blocking accounts and halting transactions.

KYC Process

Know Your Customer, or KYC, is an obligatory process banks undertake with every customer. This process has 500 to 1000+ FTEs performing all the necessary customer checks. According to Thomson Reuters, banks spend over $384 million annually in compliance with the KYC process. 

However, considering the cost of such a manual process, banks have now started using RPA to validate their customer data. As this process attains more precision, the FTEs are not seen as a concern, and the work can be done with fewer errors and staff. 

General Ledger

Banks must maintain an up-to-date general ledger with financial statements, assets, liabilities, and revenues. A single error can damage the bank's reputation. RPA consolidates data from multiple legacy systems, ensuring accurate and timely financial reporting.

Hint: A PwC survey found that 30% of financial organizations are not just experimenting with RPA but are implementing it organization-wide to drive efficiency. 

Report Automation

Like all other public companies, banks must prepare reports and present them to their stakeholders to show their performance. The report is highly significant, and hence, the bank must be cautious.  

RPA systems can deliver data in various formats and can complete report formats. This assists in generating reports with fewer errors and in less time.  

Account Closure Process

With so many customers, it is bound to receive some account closure requests every month. There could be a lot of reasons for account closures, one of which is when a client fails to provide the required documents. 

It can track all such accounts easily via RPA, which also offers automatic notification and scheduling of calls for required documentation submission. When a customer fails to give KYC documents, the RPA can help a bank close their accounts. 

Underwriter Support

Underwriting is the process of analyzing the risk of financial transactions like issues of bonds, bank loans, and insurance policies. Collecting and analyzing data from multiple systems before putting it in the system requires huge manual effort and efficiency; processing manually is very tiring and time-consuming. Here, RPA can play a more significant role in automating the underwriting process. 

Automated underwriting processes in banking enable loan-related decisions to be taken based on algorithms rather than relying on inhuman beings. RPA in underwriting removes the risk of manual error and misinterpretation of loan risks and takes care of biases while making decisions. 

Cash Collection and Deposits

Collecting cash and deposits is an issue that financial institutions and banks frequently encounter. Collecting cash from various points of sale and transporting it to other branches properly is difficult. Rather than having individuals monitor everything, banking RPA can monitor all the data from various sources and consolidate it into one system for easy sharing and access.  

Account Origination Process

The account opening process consumes a lot of time, from applying for an account to dispensing funds. Bank employees at the service desk have to go through a lot of steps in the process, from verifying documents, processing applications, making credit decisions, performing quality checks, and initiating loan funding. 

Utilizing RPA in the process eliminates the requirement for data gathering and reduces errors. It makes the loan process faster and ensures that rules and regulations are complied with.

Banks can accomplish more with fewer employees and reap financial benefits through the use of RPA. A Price Waterhouse Coopers' survey of the finance sector revealed that 30% of the respondents were experimenting with RPA and using it across their entire organization.

Real-life Banking Automation Case Studies

Use cases show what’s possible with RPA. Understanding how your competitors are automating processes in their banking firms gives you a clearer picture of its impact and benefits.

Postbank (Bulgaria): Streamlining Loan Administration

Postbank faced inefficiencies in its loan administration processes, particularly in payment distribution for credit card debts. This task required seven employees to spend four hours daily, leading to delays and errors. 

To address this, Postbank implemented an RPA solution using the UiPath platform. The automation streamlined 20 loan administration processes, reducing the time required for payment distribution by 2.5 times. Human intervention was cut to just 5% of cases, and the bank also automated customer data collection and report creation. 

The result? Improved operational efficiency, fewer errors, and more time for employees to focus on strategic tasks. 

CGD (Portugal): Overcoming Legacy System Challenges

As Portugal’s oldest and largest financial institution, CGD struggled with outdated legacy systems that made digital transformation difficult. Manual back-office tasks were time-consuming and inefficient.

CGD established a Robotic Process Automation Center of Excellence (CoE) to tackle this issue. Starting with simple processes, the bank automated over 110 workflows within two years. This initiative saved approximately 370,000 employee hours, proving that even large organizations with legacy systems can achieve significant efficiency gains through RPA. 

KAS Bank (Netherlands): Reducing Operational Costs

KAS Bank faced high operational costs due to manual financial processes, such as treasury operations and internal invoicing. These tasks were not only expensive but also prone to errors.

The bank carefully analyzed its processes and deployed five RPA bots to automate 20 financial workflows. The bots handled tasks like transaction processing and invoicing, ensuring accuracy and consistency.

The outcome? Reduced operational costs, improved process quality, and more resources available for strategic initiatives.

UBS (Switzerland): Rapid Loan Processing During the Pandemic

During the COVID-19 pandemic, UBS experienced a surge in loan applications, overwhelming its manual processing capabilities. Each loan request took 30-40 minutes to process, leading to delays and customer dissatisfaction. 

To address this, UBS partnered with Automation Anywhere to implement RPA within just six days. The bots automated loan request processing, reducing the time per application to 5-6 minutes. 

This quick implementation allowed UBS to handle the increased workload efficiently, ensuring timely customer service during a critical period.

Benefits of RPA in Banking & Finance

Here are some of the most prominent benefits of RPA in Banking & how it simplifies Banking Process automation:

1. RPA automates time-consuming manual tasks such as data entry, transaction processing, and report generation. This reduces the time required to complete these tasks, allowing employees to focus on higher-value activities. 

2. By automating repetitive tasks, RPA reduces the need for manual labor and minimizes operational costs. Banks can reallocate resources to strategic initiatives, improving overall profitability. 

3. Manual processes are prone to human errors, leading to financial losses and compliance issues. RPA minimizes errors by ensuring activities are executed accurately and consistently. 

4. RPA bots can work 24/7 without breaks, significantly speeding up processes like loan approvals, transaction processing, and customer onboarding. 

5. By automating back-office and customer-facing processes, RPA enables faster response times and smoother service delivery. Higher levels of client pleasure and loyalty result from this. 

6. RPA allows banks to scale operations quickly without hiring additional staff. Bots can handle increased workloads during peak times, such as tax season or holiday periods. 

7. RPA ensures that processes are executed consistently and in compliance with regulatory requirements. It also provides detailed audit trails, making it easier to monitor and report on activities 

8. By automating mundane and repetitive tasks, RPA frees up employees to focus on more meaningful and strategic work. This boosts employee morale and productivity. 

9. RPA solutions can be implemented quickly, often within weeks, and deliver a rapid return on investment (ROI) through cost savings and efficiency gains. 

10. RPA bots can handle sensitive data with strict adherence to security protocols, reducing the risk of data breaches and ensuring compliance with data protection regulations.

Challenges of Implementing Robotic Process Automation in Banking & Finance

Although RPA has numerous advantages and is not difficult to begin to implement, it is still difficult to implement. The following are the three largest issues that banks and financial institutions encounter when they attempt to implement RPA in their business and how we can assist in resolving them:

Challenges	Solutions
1. IT support: Many banks still operate on outdated legacy systems that were not designed to support automation. Integrating RPA with these systems can be complex and may require additional middleware or modifications.	1. Provide API-based integration solutions to bridge the gap between legacy systems and modern RPA tools.  2. Offer customized automation frameworks that can work with screen scraping and OCR to extract data from non-API-friendly systems.  3. Ensure minimal disruption by using hybrid automation approaches that blend AI and RPA.
2. Regulatory Compliance: Banking and financial institutions are heavily regulated, and automated processes must comply with strict legal and security standards. Any failure in compliance can result in fines or reputational damage.	1. Develop RPA workflows that include built-in compliance checks and audit trails.  2. Implement AI-driven monitoring to ensure real-time fraud detection and regulatory adherence.  3 . Ensure end-to-end encryption and secure data handling in all automated processes.
3. Resistance to change: Employees may resist automation due to fear of job loss or lack of understanding about how RPA can enhance their work. Additionally, implementing RPA requires training and cultural shifts within the organization.	1. Offer workshops and training sessions to upskill employees, helping them transition to higher-value roles.  2 . Position RPA as a tool for eliminating repetitive tasks, allowing employees to focus on strategic and customer-centric activities.  3. Provide a change management framework that helps leadership drive RPA adoption with minimal resistance.

As a company, we help banks and financial institutions overcome RPA implementation challenges by offering end-to-end support. Our consulting services and strategy define the best processes to automate and create a clear implementation plan that allows for smooth integration without interfering with ongoing processes. 

We create customized RPA solutions that integrate with the bank's existing systems, allowing easy interaction with legacy systems while increasing efficiency. Our solutions can support complex workflows, meet regulatory requirements, and solve security requirements, making automation effective and secure. 

We also provide continuous support and improvements to keep performance high. This includes constant monitoring, compliance management, and system updates to enhance automation accuracy and efficiency over time. Our proactive approach allows banks to scale their RPA programs confidently while remaining compliant with industry regulations.

How We Implement RPA for Banking?

Step 1: Assessment & Strategy Development

We begin with a detailed evaluation of the bank's existing processes to identify high-impact automation opportunities. Our team collaborates with stakeholders to set clear objectives and define an RPA adoption strategy that aligns with business goals. 

Step 2: Selecting the Right Use Cases 

Not all processes are suitable for automation. We analyze workflows based on complexity, volume, and rule-based execution to determine the most viable RPA candidates. The goal is to maximize efficiency and cost savings. 

Banking automation software ensures that only the most impactful processes are automated, helping financial institutions optimize operations while maintaining compliance and security 

Step 3: Choosing the Right RPA Platform 

Selecting the right RPA vendor is critical. We assess vendors based on intelligent automation capabilities, user-friendliness, scalability, and compatibility with the bank's IT ecosystem. Our approach ensures seamless integration without disrupting core banking operations. 

Step 4: Custom Solution Design & Development 

Once the framework is set, we design and develop customized RPA bots tailored to the bank’s needs. This includes configuring automation scripts, integrating them with banking systems, and ensuring compliance with industry regulations. 

Step 5: Pilot Testing & Validation 

Before full-scale deployment, we conduct pilot projects to test RPA bots in real-world scenarios. Performance is evaluated against key metrics, and necessary refinements are made to ensure accuracy, efficiency, and security. 

Step 6: Deployment & Implementation 

After successful testing, RPA solutions are deployed across selected banking processes. Our team ensures a smooth transition by supporting system integration, employee training, and knowledge transfer. 

Step 7: Continuous Monitoring & Optimization 

RPA implementation is an ongoing process. We provide continuous monitoring, compliance management, and system optimization to enhance performance and address evolving business needs. 

Step 8: Scaling Automation 

Once initial RPA deployments prove successful, we help banks scale automation across multiple departments. By leveraging AI and advanced analytics, we drive continuous operational efficiency and customer experience improvements. 

Following this structured implementation process empowers banks to achieve seamless automation, cost reduction, and improved service delivery.

Estimated Cost of RPA Implementation in Your Banking Firm

The cost of RPA implementation depends on the process complexity, automation size, and integration with current systems.  

Major cost considerations:

Software Licensing – $5,000 to $60,000 per bot annually, depending on the vendor and extent of automation features. 

Implementation & Development – One-time RPA development costs around $10,000 to $100,000, including process evaluation, customization, and integration. 

Infrastructure & IT Support – Cloud or on-premise deployment, depending on current banking automation software and system compatibility. 

Training & Maintenance – Ongoing support, compliance management, and employee training, generally 20-30% of the total investment annually. 

Total Cost Estimate:

For small and mid-sized organizations, RPA implementation typically ranges from $50,000 – $200,000, while enterprise-level automation can be over $500,000, depending on complexity and the number of processes automated.

(Note: These costs are taken from the industry standard data; we would suggest you get in touch with us to get a customized plan and cost estimation.)

How to Check If Your Banking Firm Is Automation-Ready?

Banks must measure their automation readiness before deploying RPA for banking to make the transition seamless and achieve optimal efficiency. Here's how to measure your company's readiness: 

1. Process Standardization & Documentation

Are your processes well-documented and standardized? 

Do most of your processes have rule-based, repetitive patterns? 

Are there any inconsistencies in the way tasks are executed across teams? 

Automation Readiness Tip: Standardized and structured processes are the most suitable for banking automation software. If your processes are not consistent, process mapping should be your first project. 

2. Data Availability & Digital Maturity

Does your company employ structured digital data, or are key processes still manual and paper-based? 

Are your core banking systems, CRM, and databases easily integrated with automation tools? 

Is your data clean, accurate, and well-structured? 

Automation Readiness Tip: RPA demands structured and accessible digital data. If your banking company is still employing manual data entry or legacy systems, digitization should be your first project before deploying RPA. 

3. IT Infrastructure & Security Compliance

Is your current IT infrastructure RPA solution integration-ready? 

Are your systems cloud-based or on-premise, and are they API connection-friendly? 

Does your company have compliance with banking regulations such as GDPR, PCI-DSS, or RBI guidelines? 

Automation Readiness Tip: Banks require secure, scalable, and compliant IT infrastructure to support automation. An IT audit will reveal the gaps in system compatibility. 

4. Employee Readiness & Change Management

Are employees knowledgeable about automation benefits, or is there resistance to change? 

Does your company have an automation task force or RPA Center of Excellence (CoE)? 

Are employees ready to move their focus from repetitive tasks to higher-value activities? 

Automation Readiness Tip: The organization needs to support efficient automation. Invest in change management techniques and employee training to ease the transition. 

5. Cost-Benefit Analysis

Did you find the potential return on investment (ROI) of deploying RPA? 

Will automation lower costs, lower errors, or improve customer satisfaction? 

Do you have budget lines for RPA implementation, upkeep, and upgrades? 

Automation Readiness Tip: Conduct a feasibility study to establish the financial impact of automation and prioritize processes with the best return on investment (ROI). 

Final Verdict: Are You Ready?

If your banking company covers most of these areas, you are ready for automation and can start planning an RPA strategy. Otherwise, standardize processes, upgrade IT, and manage change before going ahead.

Top 5 RPA Platforms Transforming Banking Operations

The August 7, 2024, release of the 2024 Gartner Magic Quadrant for Robotic Process Automation reflects seismic shifts in the RPA market, particularly because of advances in artificial intelligence.

1. UiPath

Key Features: 

• UiPath is an end-to-end RPA platform with a Studio for development, an Orchestrator for governance, and Robots for execution. 
• The platform provides a vast library of pre-existing components and activities and a strong community and marketplace for shared resources. 
• Its AI and machine learning capabilities enable intelligent automation, making it a strong solution for RPA and AI in banking. 

Optimal For: 

UiPath is an optimal choice for organizations seeking a versatile RPA solution that supports attended and unattended automation across the finance, healthcare, and manufacturing industries. 

2.  Automation Anywhere

Key Features: 

• With a cloud-native architecture, this platform offers scalable and secure deployment options for automated financial solutions. 
• Low-code development enables citizen developers to create automation easily, while comprehensive analytics tools support effective performance monitoring. 
• AI-powered automation enhances efficiency through cognitive automation and natural language processing. 

Optimal For: 

Best suited for businesses in sectors like banking, telecommunications, and retail that require intelligent automation solutions with strong integration capabilities. 

3. Blue Prism

Key Features: 

• It has enterprise-grade security with robust capabilities that ensure compliance, which is crucial for banking automation systems. 
• It is simple to define, with its drag-and-drop feature. 
• It uses a control room in the center to monitor, schedule, and report automation processes. 
• It is scalable, and it handles large-scale automation projects efficiently. 

Optimal For: 

It is particularly effective in banking, healthcare, and government industries, where compliance and security are paramount. 

4. Microsoft Power Automate

Key Features: 

• It facilitates simple integration with Microsoft products like Office 365, SharePoint, and Teams. 
• It facilitates the integration of machine learning models into workflows using AI Builder. 
• Low-code/no-code features allow it to be utilized by users with limited technical knowledge, and cost-effective solutions are especially beneficial for organizations already using Microsoft services. 

Optimal For: 

Ideal for businesses that heavily utilize Microsoft ecosystems and seek to automate workflows across various applications efficiently. 

5.  Pega (Pega Robotics)

Key Features: 

• Pega combines RPA and AI in banking with business process management (BPM) capabilities, enabling seamless automation of financial processes.
• Its AI-driven automation improves decision-making and enhances the performance of automated financial solutions.
• Its cloud-based platform provides flexible solutions, which makes it ideal for different business needs.

Optimal For:

This is ideal for businesses that would prefer a complete strategy to automate processes. It merges robotic process automation (RPA), customer relationship management (CRM), and business process management (BPM).

The Integration of RPA and AI: Intelligent Automation

1. Hyperautomation

Hyper-automation in enterprises involves the integration of RPA with AI, Machine Learning (ML), and process mining to automate business processes instead of discrete tasks. The trend will likely control the automation space by 2025, creating autonomously operating systems with minimal human intervention. Gartner estimates that hyperautomation will affect one-fifth of all business processes, increasing efficiency and agility in operations. 

2. AI-Driven RPA

The future will witness AI-driven capabilities being the focal point of RPA. Bots can process unstructured data, interpret natural language, and make decisions in real-time. The innovation will facilitate the automation of complex tasks like document analysis and customer interactions, opening significant operational efficiencies. 

3. Intelligent Document Processing

AI-driven intelligent document processing will be a key aspect of RPA platforms, allowing organizations to automate data extraction tasks from different types of documents. The feature will automate reading and interpreting document-oriented workflows, reducing manual intervention and improving accuracy14. 

4. Advanced Cybersecurity Measures

With the increasing adoption of automation, integrating AI capabilities in RPA systems for cybersecurity will become inevitable. The systems will scan network traffic, identify anomalies, and respond to threats in real time, providing security for sensitive data and regulatory compliance2. 

5. Democratization of Automation

Low-code and no-code platforms will democratize access to RPA, allowing non-technical users to design and deploy automation solutions easily. The trend will empower small and medium enterprises (SMEs) to harness the power of automation without significant IT resources, fuelling innovation across organizational hierarchies25. 

6. Customer Experience Focus

RPA with AI will improve customer service by automating mundane processes such as data entry and query resolution. Automation will result in quicker turnaround and customized services, thus customer satisfaction56.

7. Robotic Process Intelligence

Future RPA solutions will incorporate robotic process intelligence capabilities that track real-time bot performance. The feature enables organizations to determine optimization potential, avoid problems in advance, and optimize overall automation ROI.

Bottom Line

The swift adoption of RPA in banking and finance transforms the sector, making processes efficient, cost-saving, and customer-oriented. From automating routine tasks to improving compliance and anti-money laundering, RPA is no longer an advantage—it's a requirement. 

As AI and hyper-automation advance, the fusion of RPA with intelligent technologies will unleash even more potential, driving financial institutions toward a more innovative and agile future. Banks adopting automation today will become more efficient, improve customer experience, and be the leaders in the rapidly digitalizing world. 

 The only question is, at what speed can banks implement RPA on a large scale to unlock its full potential? Stay connected to explore more.