RPA is an enterprise automation solution that automates repetitive processes by combining human behavior with attended and unsupervised bots. Simple to sophisticated activities can be completed through robotic process automation in every department of an organization.
Examples include data entry/data processing, payroll processing, employee hiring and onboarding, inventory management, help desk, customer operations, and many more. RPA has been around for more than four decades but found its sweet spot in the 2000s, and it became even more popular after the pandemic.
What is Robotic Process Automation in Banking?
When it comes to back-end processes, banks are on the bulky side. As the processes are heavy with statistics and vital data, any slip-ups can prove extremely dangerous.
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Robotic process automation helps banks to automate all such routine, rule-based or repetitive, and back-end tasks. For example, data entry and customer service tasks include updating customer information, answering their basic questions, etc. RPA augments human behavior and performs actions without human intervention. Automating such manual tasks can significantly increase productivity and streamline operations.
Benefits of RPA in Banking & Finance
There are many benefits of RPA in the banking and financial services industry. Some of the prominent ones are described below –
1. Scalability: Robots are highly scalable allowing you to handle higher volumes during peak business hours by adding more robots and responding to any situation in record time.
Additionally, the implementation of RPA allows banks to free up employees from mundane tasks to focus more on innovative strategies to grow their business.
2. Increased operational efficiency: Once set up properly, banks and financial institutions can make their processes much faster, more productive, and more efficient.
3. Cost-effectiveness: Like any other industry, cost-saving is key for the banking industry. Banks and financial institutions can save around 25-50% in processing time and cost.
4. Risk and compliance reporting: RPA in banking helps create complete audit trails for each & every process, thereby reducing business risk and maintaining high process compliance.
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5. Availability: Whether you are looking to reduce manual errors or achieve higher accuracy at a lower cost, robots work 24×7 to complete their assigned tasks. Thus, we reiterate the ever-present availability.
6. Zero infrastructure cost: One of the advantages of RPA in financial services is that it does not require any significant changes in infrastructure due to its UI automation capabilities. In the case of cloud-based RPA, hardware, and maintenance costs are further reduced.
7. Speedy implementation: As RPA tools provide drag-and-drop technology to automate banking processes, it is easy to implement and manage automation workflows with no (or minimal) coding requirements.
8. Business growth with legacy data: With the implementation of RPA, banks and the financial services industry are using legacy as well as new data to bridge the gap between processes. This type of initiative and availability of required data in one system enables banks to generate faster and better reports for business growth.
RPA use cases in banking
While end-to-end automation is often the ultimate goal, targeted automation using RPA, applied to the right use cases in banking operations, can deliver significant value quickly and at a low cost.
There are many use cases for RPA in banking besides those mentioned in the infographic. The list below highlights some of the most rewarding RPA use cases in the banking industry.
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1. Contact Center Optimization
Banks are facing huge inbound calls at their contact centers as most of the physical interactions with customers are non-operational or working in a limited capacity during this COVID-19 crisis. RPA tools and chatbots help handle a significant portion of this traffic.
For example, bots can handle simple queries related to account statements and transactions, while queries requiring human decision-making are assigned to appropriate knowledge workers.
2. Trade finance activities
Banks can use RPA solutions to enhance their trade finance operations and improve their presence in the financial supply chain. A leading bank in India uses Navidus RPA to automate processes related to issuing, managing, and closing letters of credit – the most preferred trade finance instrument.
3. Customer Onboarding
The customer onboarding process for banks can be daunting mainly due to manual verifications of multiple identity documents. Know-your-customer (KYC), an integral part of the onboarding process, involves significant operational efforts for such document verifications.
4. Anti Money Laundering (AML)
One of the best examples of RPA in banking is the automation of the entire AML investigation process. The process is highly manual and takes between 30 to 40 minutes to investigate a single case depending on the complexity and availability of information in various systems.
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5. Loan Application Processing
The loan application process is a very good automation candidate for banks and financial institutions. Typically, documents for loan and appraisal requests are received in bundled PDFs via email. Extraction of data from applications and its verification against multiple identity documents and assessment of creditworthiness are some of the key manual tasks.
In summary
Advanced technology solutions have become an integral part of the financial sector. Modern organizations cannot remain competitive without implementing appropriate software tools. Robotic process automation in the banking industry can optimize multiple operations and improve both businesses and their customers.
With the help of a trusted software engineering partner, you can streamline your journey toward automation excellence and celebrate incredible results for your business.
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