RPA in Banking and Finance Services: 3 Real-life Use Cases

If you're still struggling with paper forms and manual data entry in the banking industry, this article is for you. It will show you how Robotic Process Automation (RPA) is revolutionizing banking, why it is significant now, and what transformative possibilities it holds for your financial future.

By considering real-life use cases across loan processing, customer service, and more, we'll unveil the magic behind RPA's robotic touch. You'll gain practical insights into:

• How RPA in banking automates repetitive tasks and allows bankers to focus on complex, strategic endeavors.
• The tangible benefits, from boosted efficiency and reduced costs to enhanced customer satisfaction and risk mitigation.
• Challenges and considerations of the RPA adoption journey, ensuring a seamless transition for your financial institution, and discover how Binariks can assist you throughout the process.

Let's explore the world of RPA in banking and say goodbye to spreadsheets!

The state of RPA in banking

The banking industry is undergoing a major shift as RPA banking transforms tedious tasks into automated workflows, replacing the mountains of paperwork and human-powered processes.

It isn't just a futuristic buzzword; it's a reality rapidly taking root. According to Allied Market Research, the global RPA and hyperautomation in the banking market was valued at $745.4 million in 2021 and is projected to reach $7.1 billion by 2031, growing at a CAGR of 25.7% from 2022 to 2031 (Source ).

A few years ago, adoption of RPA in banking was nascent, but now it is indispensable for streamlining operations and boosting efficiency.

The COVID-19 pandemic increased the need for RPA and hyperautomation. During the lockdowns, financial firms faced challenges, such as a shift in workload pressures and delays in processes like accounts receivables due to remote working. With people working from home, RPA in the financial sector helped companies stay operational.

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RPA in the banking industry holds the potential to enhance various functions. This includes processes like payable accounts, credit card processing, customer service, account closure, account opening, receivables, and mortgage processing. As the industry seeks to enhance operational efficiency and embrace advanced technologies, the demand for RPA is anticipated to rise significantly.

Popular use cases of RPA in finance and banking

The term "RPA" isn't just hype but a potent force transforming the banking industry. Here are some examples of RPA use cases in everyday banking operations .

1. Customer onboarding

One of the critical aspects of financial institutions is the onboarding process for new customers. RPA can automate the collection and verification of customer data, reducing the time and effort required for account setup.

From document verification to data entry, RPA ensures a swift and error-free onboarding experience, enhancing customer satisfaction and operational efficiency.

2. Regulatory compliance

Staying compliant with ever-evolving regulations is a constant challenge for financial institutions. RPA plays a pivotal role in automating compliance checks and ensuring that all processes adhere to the latest regulatory standards.

This includes automating Anti-Money Laundering (AML) checks, Know Your Customer (KYC) processes, and other compliance-related tasks, thereby minimizing the risk of penalties and legal issues.

3. Loan processing

RPA in banking operations streamlines the loan processing lifecycle, from application submission to approval. It can automatically gather and validate information, perform credit checks, and generate loan agreements. By automating these steps, financial institutions can significantly reduce processing times, enhance accuracy, and improve overall customer satisfaction.

4. Customer service

Enhancing customer service is a top priority for financial institutions. RPA can be employed to automate routine customer inquiries, account balance checks, and transaction history requests. This allows human agents to focus on more complex queries, providing a more personalized and efficient customer service experience.

5. Accounts payable

Managing accounts payable involves handling a multitude of invoices, verifying details, and processing payments. RPA can automate invoice processing, matching purchase orders, and reconciling accounts. This not only reduces the chances of errors but also accelerates the entire accounts payable process, leading to improved financial management.

6. Credit card processing

RPA in banking and finance can streamline credit card application processing, from data input to credit scoring. Automation ensures a faster and more accurate evaluation of creditworthiness, expediting the approval or rejection process. This not only benefits customers but also enables financial institutions to make data-driven decisions efficiently.

7. Fraud detection

The financial sector is susceptible to various forms of fraud. RPA can continuously monitor transactions, identify suspicious patterns, and trigger alerts for further investigation.

By automating fraud detection processes, financial institutions can respond swiftly to potential threats, mitigating risks and safeguarding both customer assets and institutional integrity.

8. Account closure

Closing accounts often involves a series of manual steps, including verification and communication with the account holder. RPA can automate the account closure process, ensuring that all necessary steps are completed accurately and efficiently.

This contributes to a smoother account closure experience for customers and reduces the workload on bank staff.

9. General ledger

RPA for banks can be applied to automate general ledger entries, journal entries, and reconciliations. By automating these routine accounting tasks, financial institutions can reduce errors, improve data accuracy, and free up valuable time for finance professionals to focus on strategic financial planning and analysis.

Popular сase studies of using RPA in banking

Zurich Insurance

Zurich, the world's largest insurance firm, achieves success in finance automation with its RPA partner Capgemini. Through Capgemini's RPA implementation, routine tasks like managing boilerplate policies are efficiently handled by robots.

This strategic shift enables commercial underwriters to focus on more intricate aspects of insurance, emphasizing sophistication in their work. Capgemini's comprehensive RPA solution, addressing challenges in policy issuance across five countries, showcases Zurich's innovative contributions to the outsourcing industry.

Bancolombia

Bancolombia, Colombia's largest bank, leverages robotic process automation (RPA) tools to empower customers in managing investment portfolios, highlighting the adaptability of RPA across diverse sectors. Available to investors with holdings exceeding $7000, Bancolombia's RPA tool, Investor, not only suggests modifications based on market conditions but also offers real-time insights into market trends and portfolio performance.

Taking a progressive step, Bancolombia introduces the Rob Advisor, providing Colombian investors with stock market advice and encouraging exploration through online channels. This initiative showcases Bancolombia's commitment to utilizing RPA for enhanced customer engagement in stock market investing.

Heritage Bank

Heritage Bank, Australia's largest mutual bank founded in 1875, embraced digital transformation to stay competitive. They prioritized customer and employee experiences and turned to robotic processing automation (RPA) to streamline workflows.

David Johnston, now the Intelligent Automation and Process Excellence Manager, was initially skeptical but witnessed RPA's transformative power. Heritage successfully implemented RPA in their financial crimes team, automating the retrieval of transaction records and saving significant time.

"The financial crimes use case was very successful," Johnston says. "These requests come through sporadically and are dealt with by the bots, and the process is very scalable."

Heritage extended RPA to improve living expense report management for loans, showcasing the scalability and efficiency of the technology. This transition aligns with Heritage's shift from a physical to a digital bank, ensuring growth and enhanced customer interactions.

Benefits of RPA in banking & finance

The banking industry, once known for its traditional practices and manual processes, is undergoing a significant transformation due to the impact of RPA. In this context, let's explore the key benefits of RPA in banking and its remarkable effect on the industry.

High scalability

RPA in financial services is remarkable, allowing banks to automate tasks with minimal effort and cost. As workloads fluctuate or change, RPA robots seamlessly adapt, ensuring that operations remain agile and responsive to evolving needs. This adaptability is crucial in the dynamic banking environment , where customer demands and market trends constantly shift.

Cost-effectiveness

By automating tasks previously performed manually, banks can achieve significant savings through reduced labor costs and improved process efficiency. Automation minimizes downtime, and frees up human resources to focus on higher-value activities, further driving cost savings and enhancing productivity.

Improved efficiency

RPA in retail banking excels at performing repetitive tasks with unwavering accuracy and speed, far exceeding human capabilities. This automation eliminates manual errors, reduces processing time, and streamlines workflows, dramatically improving overall efficiency.

Imagine loan applications being processed in minutes instead of days, or customer inquiries being resolved within seconds, all thanks to the tireless efficiency of RPA robots.

Better compliance

Robotic process automation in banking enhances compliance by automating regulatory reporting, monitoring transactions, and identifying potential risks.

Automation ensures that banks fully comply with ever-changing regulations, reducing the risk of penalties and fostering a culture of continuous control. RPA safeguards compliance and protects the bank's reputation in such a heavily regulated industry.

Rapid implementation

RPA implementations typically take months or even weeks, far shorter than traditional IT projects. This rapid deployment allows banks to realize the benefits of automation quickly and efficiently, driving immediate improvements in operational efficiency and customer service.

With time being a precious commodity in the banking industry, RPA's swift implementation is a game-changer, allowing banks to stay ahead of the curve and adapt to changing market dynamics.

Increased availability

RPA robots operate 24/7, ensuring critical processes remain operational even during off-peak hours. This enhanced availability gives banks a competitive edge, enabling them to serve customers around the clock and maintain a consistent level of service.

In today's always-on economy, RPA's unwavering availability ensures that banks are never off duty and always ready to meet the demands of their customers.

Implementing RPA: considerations and challenges

Adopting robotic process automation (RPA) has become a strategic imperative for banks seeking to improve efficiency, compliance, and customer experiences. However, successfully implementing RPA requires careful planning, strategic execution, and a deep understanding of the potential challenges.

Identifying the processes to automate

The first step in any RPA implementation is to identify the most suitable processes for automation. These processes should be repetitive, rule-based, and have a clear business value. Some common examples of RPA-friendly processes in the banking industry include:

• Customer onboarding: Automating tasks such as data entry, identity verification, and account setup can streamline onboarding and improve customer satisfaction.
• Loan processing: Automating document verification, creditworthiness assessment, and loan approval can expedite the loan process and reduce processing time.
• Fraud detection: Automating the analysis of transaction data can help banks identify suspicious activity and prevent fraud.
• Accounts payable: Automating invoice processing and payment approvals can reduce costs and improve accuracy.

Choosing the right RPA software and tech partner

With many RPA vendors and solutions available, choosing the right RPA software and tech partner is crucial for a successful implementation. The ideal RPA software should be scalable, interoperable, and easy to use. The ideal RPA partner should have a proven track record of success and a strong understanding of the banking industry.

At Binariks, we are dedicated to helping banks achieve their automation goals, and even if our clients need services that are new to us, we're open to taking them on with full commitment.

With our expertise and personalized approach to every project, we engage with clients from concept to launch, offering consultation and tailored advice and embracing new challenges to craft innovative solutions.

Change management and employee training

RPA implementation inevitably involves change, and banks must effectively manage this change to ensure employee buy-in and minimize disruption. This involves communicating the benefits of RPA to employees, providing training on how to work alongside RPA robots, and addressing any concerns or resistance.

Security and data privacy issues

Data security and privacy are paramount in the financial industry, and RPA implementation must not compromise these critical aspects. Banks must ensure that RPA robots can access only the data they need to perform their tasks and that robust security measures protect all data.

Implementation challenges to be aware of

There are specific challenges that banks may encounter during implementation:

• Resistance from employees: Some employees may feel threatened by introducing RPA, fearing job losses or role changes. Effective communication and training can help address these concerns.
• Integration with existing systems: RPA must integrate smoothly with the bank's existing IT infrastructure, which may require careful planning and coordination.
• Data quality: The quality of data used by RPA is critical for its success. Banks must ensure that data is accurate, consistent, and up-to-date.
  

Practical tips to consider

• Start small and scale gradually: Begin by automating a few low-hanging fruit processes to demonstrate the value of RPA and build momentum for further implementation.
• Leverage RPA to augment, not replace, human workers: RPA should be seen as a tool to enhance human capabilities, not replace them altogether. Focus on creating a collaborative environment where humans and robots work together to achieve common goals.
• Continuously monitor and improve: RPA is an ongoing process, not a one-time project. Regularly monitor the performance of RPA bots and make adjustments as needed to optimize their effectiveness.

Ready-made RPA vendors & solutions

ServiceNow

ServiceNow, formerly Intellibot.IO, excels in RPA customization, offering a comprehensive suite of automation design tools, including chat and ML architecture for both attended and unattended bots. The platform enhances UI-based interactions, reduces manual efforts, and accelerates automation across diverse industries. Notable features include native integration, over 1,300 tools, and customization options like Flow Designer, a management hub, and a desktop design studio.

Pros include a helpful common service data model and numerous modules for IT service management. However, limitations in change requests, a slow user interface, and the lack of a mobile version are notable cons.

EdgeVerve

EdgeVerve, a subsidiary of Infosys Technologies, excels as a robotic process automation in the banking sector for large enterprises, especially those heavily relying on customer service, particularly in call centers. Offering the flagship RPA solution, AssistEdge Robotic Process Automation, and a suite of machine learning and AI tools under Infosys Nia, EdgeVerve is tailored for major enterprises, particularly in finance. The company emphasizes RPA governance, focusing on the seamless integration of automation and AI.

With a strong graphical user interface, scalability, and enterprise-grade security, EdgeVerve stands out for its expertise in attended customer service and call centers. However, users desire improved reporting on robot performance, and the integration of ML and AI technologies between Nia and EdgeVerve could be clearer.

Kofax

Kofax excels in managing extensive unstructured data, particularly from social media and customer interactions. The RoboServers tool streamlines interfaces into a single container, reducing desktop solutions and cutting costs. Known for handling large data loads, Kofax stands out in optical character recognition (OCR), eliminating the need for additional tools. It targets finance, accounting, customer engagement, and operations, with strengths in logistics and transportation.

Key features include efficient data transport with automated bots, minimized virtual desktop needs, and a REST/SOAP interface for seamless automation embedding. Pros include robust data extraction, API utilization for data mining, and easy automation reuse. However, concerns linger about customer support, prompting users to suggest a focus on improving application debugging.

While ready-made RPA solutions can be a cost-effective and time-efficient way to automate processes, they also may not be as flexible as custom-built solutions and may not be able to meet specific needs.

As a software development company, we acknowledge that ready-made RPA solutions can be a good option for businesses looking for a quick and easy way to automate their processes. However, custom-built RPA solutions can be a better option for companies with unique requirements and those who expect to play a long-term game. And of course, we are ready to help here – just contact us to share your future project idea.

Final thoughts

The age of automation has arrived, with RPA leading the way. By automating repetitive tasks, RPA empowers businesses to free up human talent and drive innovation. Carefully consider the key factors for successful implementation, and embrace the transformational power of automation to elevate your operations and revolutionize your business.