Software Development Updates

Any small error in data processing during a financial operation can lead to significant monetary losses and damage to brand reputation. That is why many financial institutions invest in automating repetitive and mundane tasks to minimize errors, reduce risks, and improve efficiency. 

Partnering with a top financial software development company enables you to implement Robotic Process Automation (RPA) in finance and banking systems. You can either integrate RPA with your existing legacy systems or develop a new system that incorporates it. 

However, before that, you must know how RPA works in finance. Therefore, this blog provides you with a small overview of the concept along with a detailed discussion on its advantages, limitations, use cases, real-life examples, and more.

1. What is RPA in Finance?

RPA or Robotic Process Automation is a technology that imitates human actions to complete predetermined tasks. It is used in the finance sector to automate and handle repetitive tasks, such as report generation, compliance checks, transaction processing, invoice processing, and data entry.

The RPA works with the financial institution’s existing systems and interacts with them just like humans would. The RPA tools must be programmed to mimic human behavior so they are best suited for simple, repetitive, and rules-based tasks. It requires minimal coding to get started. 

Most banks and financial organizations use robotic process automation solutions to streamline financial activities, improve operational efficiency, and reduce human errors. Robotic process automation is often enhanced by AI and ML algorithms, which enable bots to handle complex tasks by adapting to the latest data in real-time. 

Here is what a Quora user says about robotic process automation in finance.

2. Benefits of RPA in Finance

Finance companies can benefit significantly from using RPA to manage their repetitive and mundane tasks. Here are a few advantages of implementing RPA in finance.

2.1 Increased Efficiency

Implementing RPA helps businesses increase accuracy and reduce human errors, giving them better control over both the process and its results. Robots perform computations and analyses faster and more reliably than humans. So, there is no need for manual analysis or wasting time in double-checking for errors. This saves time and improves operational efficiency. 

2.2 Scalability

Using RPA allows your system to handle large volumes of data at reduced costs. This gives you the flexibility to scale your system as needed. With smart automation, scaling your system up or down is straightforward. It can easily adapt to fluctuating data volumes and operates most efficiently and cost-effectively without disrupting your system. This responsive scalability will give your business a clear advantage over the competition. 

2.3 Cost-effective Solution

Gartner reports suggest that RPA costs only one-third of an offshore employee and one-fifth of an onshore finance professional. 

Some may think that the initial cost of RPA is high, but it pays off in the long term. Compared to employees, it can operate longer and faster, with a much lower margin of error. With the increased accuracy and efficiency, sales and revenues are likely to increase while the operational costs remain low, thanks to RPA. 

2.4 Reduces Errors

Finance processes that follow specific patterns or standard rules are automated, allowing bots to perform the same task repeatedly. This ensures consistency and reduces the risk of errors by eliminating human intervention. Humans are prone to making mistakes, ranging from typos to missed verifications. However, the bots can perform repetitive tasks with fewer errors and automatically verify their work from multiple sources. 

2.5 Improved Customer Experience

Robotic process automation quickly addresses customer queries. This minimizes the waiting period, and considering the previous benefits, such as increased efficiency and reduced errors, if financial institutions can effectively use RPA tools with their systems, it becomes easy to deliver an enhanced customer experience.

3. How Does RPA Work in Finance?

The benefits discussed above are available only if you implement RPA appropriately in your finance process. For that, you must follow a considerate and complex path. But we are here to simplify that for you. Here, we offer a step-by-step process for adopting RPA in your business workflow. 

3.1 Define Your Goals

First, you need to be clear about why you want to use RPA. The objective behind its implementation can vary, such as cost savings, improving efficiency, or better accuracy. Ensure the purpose of using RPA in your financial operations aligns with your company’s long-term goals. Defining your goals enables you to define the extent of automation and ensure measurable benefits. 

3.2 Identify Automation Use Cases

After identifying your goals, assess your existing financial processes to identify which would benefit most from automation. Develop technical criteria such as scalability, cost, complexity, and more to evaluate each process effectively.

Next, calculate how RPA implementation would impact the costs, speed, and accuracy of these processes. Analyze the data to identify where RPA is more useful, providing a wide variety of benefits. Using RPA for them should make these processes more resource-efficient and help minimize overall manual labor. 

3.3 Designing Automation Solutions

Now that the processes requiring automation have been identified, you need to define the inputs, outputs, process flow, and technological requirements for creating RPA solutions. Ensure your concept complies with relevant regulations and industry standards by validating it with a compliance officer. 

Designing RPA solutions is easy. Most of the RPA tools come with built-in features, so even if you have a unique process to automate, you will need only minimal programming to create an automation solution. Ensure that the solution you design is compatible with your systems and can easily integrate into your existing workflow. Working with a financial software development company can be beneficial in this context. They can help tailor and deploy RPA solutions within your on-premise software environment, ensuring seamless integration and optimized performance.

3.4 Test the Output

RPA solutions must undergo a comprehensive series of tests before deployment. These tests should verify that all necessary data is complete and accurately provided to the RPA system. Members of the development team should also participate in the testing process to offer proper feedback, confirming whether the solution is working as expected. If the solution meets all requirements, it can be deployed into the production environment and can be expanded in the future. 

3.5 Monitor and Optimize

Your work is not complete after releasing the RPA solutions into the production environment. Robotic systems require continuous monitoring to ensure they meet predetermined objectives and deliver the expected outcomes. 

Monitor the bots using key performance metrics, gather user feedback, and identify the areas for improvement. Optimize the necessary functionalities and address the issues promptly. Continuous monitoring and optimization ensure that your RPA solutions remain relevant, efficient, and continue to deliver value to your evolving business.

4. Common Use Cases of RPA in Finance

While providing numerous benefits, robotic process automation is certainly useful in various financial domains. This section explores the key tasks that can be automated to improve outcomes. 

4.1 Automatic Report Generation

Banks and financial institutions are required to create Suspicious Activity Reports or SARs whenever they detect potentially fraudulent transactions. Previously, compliance officers had to prepare these reports manually, filling out the forms and providing every detail about the transaction available to them. 

Despite being a basic task, report generation often takes a significant amount of time and effort. However, automating this process can change that, allowing bots to quickly scan digital files and information to prepare comprehensive reports. It can also extract specific information from lengthy compliance documents that need to be filled out in the forms. 

This not only reduces your operational costs but also saves a significant amount of time for your finance team.

4.2 Fraud Detection

The finance industry faces a lot of issues regarding money laundering, banking fraud, and identity theft. Security analysts often spend most of their time collecting and processing data. To improve efficiency, they need tools that can automatically gather information from multiple sources and handle large volumes of data repeatedly with better accuracy. 

Moreover, the RPA bots are also assigned the task of checking whether the given data complies with relevant rules and regulations. If they detect any pattern of fraud or other financial crime, they must report it. 

Therefore, RPA uses artificial intelligence technologies to analyze the transaction records and other data deeply, identifying patterns that human analysts might miss. If any suspicious activity is detected, the bot immediately flags it and reports to the analysts.

4.3 Compliance Reporting

Banks and financial organizations must comply with numerous rules and regulations to protect customers’ private information and prevent fraud. These laws are complex and frequently change to adapt to the evolving market and customer needs. 

Finance companies are required to regularly report their performance to promote transparency and ensure their operations comply with applicable laws. 

RPA bots are used to gather and aggregate data, such as customer information and financial records, from multiple sources and generate reports that comply with regulatory standards. These bots monitor every transaction and data processing activity, alerting the relevant authorities if any compliance laws are violated. 

4.4 Drive Sustainable Growth

The market is becoming increasingly competitive. Moreover, in the age of digitalization, attracting and retaining customers has become more challenging. Therefore, banks and financial institutions need to proactively identify the preferences and needs of their targeted customers and provide appropriate financial products and services. 

This is where robotic process automation comes in. The effective implementation of RPA allows you to assess customer data to create different categories of customer segments according to their behavior and preferences. Now that you know what customers need, which kind of service or product, you can serve them well, increasing your revenues in the process. 

4.5 Managing Customer Onboarding and Account Opening

Customer onboarding is a repetitive and time-consuming process, but if not done properly, it can lead to several issues, including security risks. Moreover, it’s overwhelming because it often requires submitting numerous documents for manual verification. 

However, this process can be easily simplified by implementing RPA to automatically extract data from KYC documents using Optical Character Recognition (OCR). The customer’s data is automatically entered if the OCR doesn’t find any discrepancies. This saves a lot of time and effort for your finance departments. 

Hence, account opening becomes fast and easy with RPA. When bots handle data reading and entry, the rate of errors and delay decreases, and data quality improves. 

4.6 Data Management

Most financial organizations work with data gathered from multiple systems. They can use robotic automation to transfer data between systems, transforming its format when necessary, and processing it to generate insightful reports. 

Data is useless for the company if it cannot be securely accessed or effectively managed. RPA can help with both. Proper data management enables informed business decisions. 

4.7 Order to Cash (O2C)

O2C consists of a wide range of financial activities, such as order management and payment collection. Automating repetitive tasks like order entry, invoice generation, payment tracking, etc, would help optimize O2C processes. Automation increases the speed and efficiency of these tasks, reduces errors, and ensures real-time communication with customers. 

Optimizing the order-to-cash workflow with RPA enhances a company’s cash flow and improves customer satisfaction. RPA also provides financial professionals with better insights into the revenue generation pipeline and helps identify potential bottlenecks. Using RPA for O2C supports maintaining good customer relationships and ensures the organization’s financial health. 

‍4.8 Accounts Receivable and Accounts Payable

Automating the accounts payable and accounts receivable functions is certainly beneficial. It helps maintain strong relationships with customers and ensures healthy cash flow. Managing AR and AP processes manually can be challenging. Finance teams often forget or delay sending invoices, and bills are not always clear about the amounts owed by the customer. Automating these processes can effectively address these issues. 

RPA can effectively automate manual tasks such as reconciling accounts, tracking due dates, processing payments, invoice matching, payment notifications, and more. Using them also simplifies the payment approval process. 

RPA bots assess purchase orders, collect and record payments, create and send invoices, and send payment reminders to customers. Integrating AI into this process allows you to analyze the customer’s payment patterns to identify the risks of fraud or non-payment.

5. Real-Life Examples of RPA in Finance

Even after going through the benefits and use cases, if you need more convincing, then let’s discuss some real-life examples of how RPA is helping companies optimize their financial operations. 

5.1 Keybank

KeyBank is one of the leading commercial banks that has adopted RPA solutions to improve operational efficiency. The typical accounts receivable process includes multiple steps, such as generating purchase orders and invoices. Automating these tasks has resulted in a seamless and error-free accounts receivable process. 

5.2 JPMorgan Chase & Co

JP Morgan is one of the largest banks in the world. It is leveraging robotic process automation to enhance various financial activities, including data entry, invoice processing, and account reconciliation. The use of RPA has significantly reduced processing time, improved accuracy, and minimized manual errors. 

5.3 Zurich Insurance

Zurich is a global insurance company that uses AI to replace almost 40% of its commercial underwriter staff. RPA implementation has allowed their finance teams to focus on high-value operations and dedicate more time to managing complex financial policies. During the pilot program only, Zurich witnessed a 50% cost reduction, thanks to robotic automation. 

6. Challenges in RPA Adoption

Although there are numerous use cases of using robotic process automation, integrating it into your workflow is not always easy. To get maximum benefits, you need to overcome the challenges as mentioned below: 

6.1 Intricate Legacy System Architecture

Often, automations are required to streamline the operations of a legacy system. But these systems aren’t flexible. You need to create new workflows to integrate a legacy system with third-party systems or modern technologies with it. Therefore, before implementing RPA, it is essential to conduct a thorough assessment of your existing IT infrastructure. Only then will you be able to accurately define the scope of the project and the possible workarounds. 

6.2 Regulatory Compliance

The finance sector is governed by complex regulations, making it challenging to ensure transparency. Your bots must be familiar with the relevant regulations and ensure that all the operations are in proper compliance. Training the bot for the same demands a huge amount of time, effort, and resources. 

6.3 Lack of Process Standardization

Financial operations are mostly complex, and RPA doesn’t work well in a confused workflow. You need a standardized process for effective automation. If there are too many exceptions or variations in the process, then automating it can be problematic. 

You can start by automating simple tasks and those that involve handling large datasets. Don’t forget to assess and map your existing processes, as this helps in implementing robotic automation effectively. You will need a detailed plan to manage the complexities of finance processes. 

6.4 Data Security and Privacy Concerns

Artificial intelligence-powered bots require training on large amounts of customer data, which is often personal and sensitive. So, it is necessary to ensure its safety by taking appropriate data protection measures and complying with relevant regulations, such as GDPR. 

6.5 Biased AI

If the training data is not diverse or representative of different customer segments and preferences, AI models can become biased and unintentionally perpetuate these biases in their results. This may lead to unfair decisions and increased reputational risks. 

7. Conclusion

The use of RPA in the finance and banking sectors offers many advantages. It can streamline finance operations, increase overall efficiency and productivity, reduce costs, drive growth, and enhance the customer experience. Automating simple and repetitive tasks allows finance teams to focus on core and complex activities. Additionally, RPA supports data analysis and informed decision-making, giving your organization an edge over the competition in the evolving market. 

FAQs

How does RPA work in accounting?

RPA automates the finance function of data entry, where information is collected from multiple sources such as bills, payables, invoices, expense reports, and receipts. In accounting, RPA is also used to automatically generate documents, like financial statements and the general ledger. 

Does RPA require coding?

Robotic process automation doesn’t need coding unless it’s an extreme case. Most of the RPA tools come with built-in functionalities, so even for a unique process, only minimal programming is usually needed. RPA tools come with easy-to-use drag-and-drop editors to build a sensible workflow. 

What is RPA in AML?

RPA is a robust technology that can be used in AML for repetitive compliance tasks, reporting, and more. It helps increase the accuracy and efficiency of these processes, reduces errors, and allows finance professionals to focus on more complex cases. 

What are the three types of RPA?

The three types of RPA are attended, unattended, and hybrid. You should choose the one that best suits your project or finance workflow.