A Comprehensive Guide to Implementing RPA in Banking

The finance industry has seen significant growth in the past years. The main reason behind this is the integration of technological advancements, which resulted in accelerated, reliable, and secure services. Currently, remaining competitive in the market is one of the basic challenges for banks and financial institutions. Most of the finance business have adopted virtual banking to provide the best user experience to customers.

Integration of RPA in banking businesses can allow organizations to automate various manual tasks to allow employees to focus more on critical aspects that help companies stay ahead of competitors. In this write-up let’s talk about RPA implementation in the banking and financial sector.

What is RPA in Banking?

RPA in banking businesses can be utilized for automating various repetitive or time-consuming tasks such as customer service, KYC processing, and so on. By integrating Robotic Process Automation, banks can not only function more efficiently but also reduce costs and ensure faster task completion.

As per the reports, using RPA in banking sector will reach $1.2billion by 2025 as per expectation. Banks or financial institutions can also implement AI along with Robotic Process Automation in complex processes related to decision making like in case of detecting frauds or anti-money laundering.

What are the Benefits of Using RPA in Finance or Banking Sector?

Before we can move on to the implementation of RPA in finance business, let’s have a look at how Robotic Process Automation benefits the working and growth of banking or financial institutions. Robotic Process Automation is now being widely used by various industries like manufacturing, hospitality, healthcare, and more. As per the reports of Gartner, 80% person of the leading financial organizations have already implemented RPA in various business processes. Here are some of the significant benefits of Robotic Process Automation in banking-

• Integrating RPA in banking operations allows businesses to scale processes easily as per the requirement. Unlike humans, robots can work continuously without breaks. Thus, they can handle increased volumes of requests during peak hours.

• Using Robotic Process Automation cuts down a considerable amount of operational cost. For instance, Deloitte is estimating a 30% decrease in cost with deploying Robotic Process Automation.

• Another significant advantage of using RPA is that it saves time. A robotic application can decrease 90%of the time needed for performing tasks.

• Banking RPA systematically performs tasks. It enhances the quality of our by reducing the chances of human errors like not paying enough attention when performing a specific task.

• Integrating RPA in finance businesses does not need infrastructural changes in the business. It can be easily integrated into the existing banking applications and sites as an additional layer to the existing processes.

• In finance or banking institutions, RPA helps in minimizing the involvement of IT departments. Banking employees can be trained in managing robotic assistants.

• Another important advantage of using Robotic Process Automation is that it improves the efficiency of human employees. Robots work 5 times faster in comparison to human employees when performing particular tasks. Thus, employees will not have to invest time in performing routine tasks and focus more on value-added tasks. This further increases the job satisfaction and well-being of the employees.

How to Implement Robotic Process Automation in Banking?

RPA in banking can free up banking employees to do more value-added tasks. The various use cases of Robotic Process Automation in the banking sector are as follows-

1. RPA for Customer Service

Banks handle customer queries starting with account information to balance queries and more. Employees are unable to resolve all these queries in a low turnaround time.

Robotic Process Automation fosters the automation of rule-based tasks for real-time query solving. This not only reduces the turnaround time but also frees up employees to perform critical tasks that need more human attention. By integrating AI with RPA, banking businesses can also resolve customer queries that require decision-making. Banks can use Chatbot Automation or Natural Language Processes to allow robots to understand the language that customers use for chatting or raising queries and respond like humans.

2. RPA for Accounts Payable

Accounts Payable is a banking process that includes extracting the information of the vendor to validate it for processing payment. This process does not require the involvement of human intelligence, thus forming a perfect case to implement RPA.

Robotic Process Automation (RPA) Development Services along with OCR solutions can help in solving this issue. OCR can be used for reading vendor data in physical form or digital copy to provide data to the RPA system. Thereafter, RPA can validate this data with the existing data present in the system for processing the payment. In the case of any errors, RPA can also send a notification to the concerned executive to resolve the issue.

3. RPA for Compliance

Banking and financial institutions are at the center of the country’s economy. These institutions are closely governed and must adhere to various compliances. According to a survey conducted by Accenture in 2016, 73% of respondents believe that RPA in banking can become a significant enabler in compliance. The technology helps in increasing productivity, improving compliance process quality, and ensuring 24/7 availability.

4. RPA for Generating Reports

RPA in finance digitizes various reporting tasks. These tasks include monthly closing, management reports as well as reconciliations. As per the rules of complaint, baking businesses are to develop detailed reports on their performance and present them in front of the directors. These reports include vast data, making it an error-prone and time-consuming task. However, Robotic Process Automation in banking can effectively collect information from various sources and put it in an easy-to-understand format for generating accurate reports.

Other than streamlining the process of report generation, RPA in banking can also help compliance officers process SAR or suspicious activity reports. Officers can depend on software with NLP processing capabilities for extracting important information for filling out the SAR form.

5. RPA in KYC (Know Your Customer)

KYC is a compulsory and time-consuming process. It can take up several work hours and significant yearly costs to conduct the process compliantly. Investigating alerts is also a time-consuming process and almost 85% of them are false positives. 25% of these alerts are to be inspected by level two analysts. Banks are losing a huge sum every year on KYC compliance sanctions. Incorporating RPA in finance’s KYC process will reduce the chances of errors, speed up the process of customer onboarding and improve user experience.

6. RPA for Fraud Detection

Skilled analysts spend 75% of their time on data collection and 15 % in entering the information into the system. These tasks can be digitized, allowing anti-fraud analysts to spend more time on their actual job i.e. fraud detection.

RPA in banking sector can also streamline anti-laundering investigations by using the if-then method to detect potential frauds.

7. RPA for credit card processing

The traditional method of processing credit cards is outdated. It takes several weeks to validate the information on the used and approved cards. The slow process leaves most customers dissatisfied and adds up to the expenses of the banks. With RPA in banks, they can process the credit card application within a few hours. Robotic Process Automation systems can communicate with various systems simultaneously for validating customer information such as background checks, documentation, and credit card check and approve or reject the application based on the rules.

8. RPA for General Ledger

Banks or financial institutions keep a general ledger that contains data such as financial statements, liabilities, revenues, etc which are needed for statements. Financial statements can be defined as public documents that are assessed by stakeholders, the public as well as media once they are made. Statements contain detailed information and manual errors in these documents can hamper the image of the bank.

By using RPA in finance, businesses can integrate information from various legacy systems and present them in an understandable format. This helps in reducing the data handling time.

Conclusion

Hence, implementing RPA in banking has several benefits. It not only automates several processes and reduces the time and cost for the banks but also helps in improving customer satisfaction levels.

If you are a banking business and planning to implement robotic process automation, do not hesitate to get in touch with ConvexSol. We are one of the most reliable RPA service providers in Dubai.