Robotic process automation, or RPA for short, has been hailed as one of the most important advances in business technology in recent years.

But what is RPA, and why is it so valuable? In this article, we'll take a look at five key uses for RPA in the banking industry.

Current Challenges for the Banking Industry

The banking industry is currently facing a number of challenges, including the following:

• Rising competition from online-only banks and other financial institutions

• The need to comply with new regulations and compliance standards

• The challenge of developing innovative new products and services to attract customers

• High pressure to lower costs and boost productivity

• Talent shortage in critical areas

Robotic process automation can help banks overcome these challenges by automating processes that are time-consuming and error-prone. It can also help banks streamline their operations, improve compliance, and reduce costs. And these are just some top-of-mind benefit examples.

Benefits of RPA in banking: Why should banking leverage RPA?

Robotic process automation (RPA) is a valuable tool for banks and financial service providers because it can automate a wide range of tasks that are tedious and complex. RPA can help banks improve compliance, streamline operations, and reduce costs. It can also help providers develop innovative new products and services. In short, RPA has a range of applications in the banking and financial sector segment that can make businesses more efficient and productive.

Let's take a more detailed look at the main benefits of using RPA in banking:

1. Cost-effectiveness

RPA can help banks speed up their processes, saving up to 50% on certain operations as well as processing time and cost. Research indicates that RPA can also improve productivity and quality.

Some projects may result in reduced headcount, but many leading banks see RPA as a way to make their employees more effective as opposed to decreasing team numbers.

2. Improved customer service and satisfaction

RPA technology can help banks improve their customer experience by automating many common tasks that customers would traditionally rely on staff for assistance with. This allows staff to focus on more complicated customer inquiries and issues, while robots are available 24/7 to handle customer needs. This significantly improves customer satisfaction.

3. Scalability

RPA implementation in banking allows banks to manage big volumes during peak business hours by adding more bots and reacting to any scenario in record time. Furthermore, this implementation allows banks to focus more on innovative ways to develop their business by freeing workers from time-consuming activities.

4. Increased operational efficiency

Robotic process automation can help banks and financial institutions automate their processes, making their operations quicker, more productive, and more efficient. By automating their processes, these organizations can save time and money, while also increasing their output.

5. Risk and compliance reporting

RPA in banking helps create comprehensive audit trails for all activities, reducing business risk and ensuring high process compliance. By automating the auditing process, RPA can help banks more easily track and review all activity, identify issues and correct them quickly. This leads to a more secure and efficient banking system for both the customer and the institution.

6. Availability

Robots can work around the clock to ensure that all transactions are completed in a timely manner. As a result, businesses can enjoy peace of mind knowing that their financial data is processed securely and efficiently. Moreover, through RPA banks can minimize the potential for human error positively impacting many areas of the business.

7. Lower infrastructure cost

RPA in banking can be implemented without requiring significant new infrastructure. Existing IT systems can be leveraged to start reaping the benefits of RPA. It is a minimally invasive solution that builds on existing infrastructure and uses the native user interfaces of existing legacy systems.

8. Faster implementation

RPA tools offer a drag-and-drop interface that makes it easy to implement and maintain automation workflows without coding required. This makes it easy for any bank or financial institution to get started with automating their processes. Additionally, the RPA tools are constantly updated with new features, so you can be sure your automation workflows will keep up with the latest changes in your industry.

RPA use cases in banking

Data overload has become the norm, leading many banks to turn to RPA in order to minimize errors and increase efficiency. The average processing time for a request has gone from days down to hours or even minutes, with some processes seeing cost reductions of up 70%. Automation through RPA technology has been particularly beneficial within banks, allowing teams more freedom to focus on engaging with clients and expanding business.

1. Customer and employee onboarding

The onboarding procedures are usually extremely difficult in the banking industry, due to the numerous identity documents that must be manually validated. Document verification is an essential part of Know-Your-Customer (KYC), but it is highly time-consuming and requires significant operational work.

The KYC process usually integrates RPA, computer vision (CV), and intelligent optical character recognition (OCR) to gather data and confirm the identification provided by the customer on the application form. Automation helps reduce human error and saves a massive amount of time for back-office operation teams.

2. Credit card and loan processing

Banks are now able to speed up the process of dispatching credit cards. With the help of RPA software, it takes just a few hours to gather documents of the customer, make credit checks and background checks, and take a decision based on set parameters on whether or not the customer is eligible for a credit card or a loan. The entire process has been streamlined perfectly by using RPA. This has resulted in customer satisfaction and an increase in the number of customers applying for credit cards or loans.

3. Fraud detection: Know your customer (KYC) and Anti-Money laundering (AML)

Rising numbers of fraud cases are a major concern for banks. With the advent of technology, the instances of fraud have only multiplied and it has become impossible for banks to check every transaction and identify fraud patterns manually.

RPA in the banking industry uses an ‘if-then' method to identify potential frauds and flag them to the concerned department. For example, if there are multiple transactions made within a short time, then the RPA identifies the account and flags it for a potential threat. This helps the bank to scrutinize the account and investigate for fraud.

The fact that both KYC and AML are extremely data-intensive processes makes them perfect for RPA implementation. Automating the manual processes or catching suspicious banking transactions with RPA has proved to be instrumental in terms of saving both time and cost as compared to traditional banking solutions.

4. Automatic Report Generation

Banks rely on accurate data to produce clean and concise reports for their board and other stakeholders. However, ensuring the accuracy of data can be a daunting task. This is where Robotics Process Automation (RPA) comes in to help. RPA gathers information from different sources, validates it, arranges it in an understandable format, and schedules it to be sent to different sources - thus helping banks to prepare reports with accurate data, quickly and efficiently.

5. Account Closure Process

Banks receive a high volume of requests to close accounts every month. But account closure can also happen if the client does not furnish the proof required for operating the account.

RPA can help banks send automated reminders to customers asking them to provide required proof of identification, and also process account closure requests based on pre-determined rules in a timely, accurate manner. If there are any exceptional scenarios (e.g. an account being closed due to failure in KYC compliance), RPA can handle that too. This leaves the bank free to focus on other tasks that require human attention and intelligence.

What are the Steps to Deploy RPA in the Banking and Financial Sector?

1. Define the RPA Strategy

The first and foremost step is to define an RPA strategy. A defined RPA strategy clarifies how, where, and when it will be implemented. It also helps decide if there is a need for business process re-engineering or augmenting current resources with more efficient resources such as AI/ML. The strategy should include an approach to address the business problem, short and long-term goals, budgets, milestones, and timelines.

RPA can play a big role in helping your business achieve its goals. Defining a clear strategy is the first step in making sure that you're getting the most out of this technology. The strategy should include what problems you're trying to solve, what short and long-term goals you have, what budget you're working with, and when you expect to see results.

2. Prepare the Floor-plan

To successfully implement robotic process automation, preparing a floor plan for the mainframe computer and all other systems involved in the process is a must. This floor plan will depict the scope and extent of automation that needs to be done in order to ensure seamless integration between existing systems and new robots. The floor plan should also include an extensive data mapping exercise, which will enable the bots to be integrated seamlessly without causing any delay in the business process.

3. Set KPIs

Once the strategy and floor plan are in place, you need to set up success metrics. This should include how long it took to deploy the RPA solution and what were the benefits, increased revenue generation, reduced operational costs, and quick ROI, etc.

4. Identify Target Processes

To identify target processes in detail, it is important to understand the business goals and objectives of the organization. Once the target processes are identified, it is important to assess the feasibility of automating those processes using RPA. There are several factors that need to be considered while assessing feasibility, such as regulatory compliances, multiple applications, etc. If the assessment reveals that RPA can be successfully deployed for a particular target process, then a pilot should be implemented to test the feasibility and performance of RPA in that specific context.

5. Prepare the Robots

Once the areas requiring RPA have been identified, it is important to start designing the bots. This will be one of the most critical tasks in a successful automation effort. In order to design the bots, it is important to understand how they will be integrated with existing systems and what type of training they will require for smooth integration.

The ultimate objective during this phase is to develop bots that can function flawlessly without interruption or downtime in the business process.

6. Train Bots

The next step is training the robots thoroughly before integrating them with existing systems. Training should include training the bot in an offline environment for better results and quick ROI.

The bots also need to be tested in a real-time environment, which will help deal with potential challenges during implementation. This will ensure that your bot is ready to handle customer interaction seamlessly.

7. Deploy Robots

After the bots are trained and their parameters are finalized, it is important to test them thoroughly before deploying them. This will ensure that they function as intended without any downtime or delays in the business process. Additionally, it is important to continuously monitor and optimize the RPA process to ensure a smooth transition from a manual process to a robotic one.

8. Monitor RPA Deployment

The next step is to monitor the overall performance of the bots. This can be done using KPIs set up in the earlier stages of implementation. It is a necessary step as it is the only way to clearly understand how bots are performing and take corrective actions if necessary.

9. Optimize RPA in banking

Successful optimization of RPA implementation requires automated evaluation of KPIs with preset triggers, which can be activated based on organizational KPIs. This will help get the desired outcomes without affecting the existing business process flow. By using this approach, you can ensure that your RPA implementation is meeting your desired goals and objectives without impacting the normal operation of your business.

RPA Software + RPA Vendors

About Accesa

Accesa is a Gold Partner of UI Path with significant experience in automating banking and financial processes. We have over 15 ongoing banking clients and can offer you the best costs for RPA licenses in this industry. Our know-how into what and how can be automated can help you reduce manual tasks and improve efficiency.

We have a strong track record of delivering innovative technology solutions and services that help organizations achieve their business goals. Additionally, we offer training and support services to help organizations get the most out of their RPA implementation.

If there is anything RPA related we can help you with, reach out to us at your convenience here: https://www.accesa.eu/services/business-hyperautomation

About UiPath

UiPath is one of the leading companies in the field of robotic process automation or RPA. The company offers a range of RPA software and solutions that can be used to automate business processes across a wide range of industries.

Some of the key benefits of using UiPath RPA software include quick deployment, scalability, and robust security. Additionally, UiPath offers training and support services to help organizations get the most out of their RPA implementation.