Robotic Process Automation (RPA) in Finance: Driving Efficiency and Productivity

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Banks continue to adopt technologies to facilitate strategic and analytical decision-making. But they still have to deal with tedious and redundant tasks. Robotic Process Automation (RPA) can help manage such tasks wholly or partially, improving the efficiency of financial operations.

What is RPA

McKinsey defines RPA as:

Robotic process automation (RPA): a software automation tool that automates routine tasks such as data extraction and cleaning through existing user interfaces.

It is, technically, ‘ a suite of business-process improvements and next-generation tools that assist the knowledge worker by removing repetitive, replicable, and routine tasks. And it can radically improve customer journeys by simplifying interactions and speeding up processes.”

RPA has a critical role to play in almost all sectors and certainly all processes. But, some sectors have started reaping the full benefit of its efficiencies.

What is RPA in Finance?

RPA in finance refers to using bots to automate manual and repetitive tasks, increasing productivity and reducing operational costs. Its adoption can save time and resources from manual processes and allow them to focus more on priority tasks.

How RPA Has Refined the Financial Landscape?

RPA uses low-code bots to perform tedious tasks like data entry or invoice processing. In finance, RPA has become a part of “Hyperautomation.” It mimics human action and uses the captured data to optimize the end processes. It offers rapid data processing times and helps achieve compliance with financial rules.

The Benefits of Combining RPA, ML, and AI

Banks combine RPA, ML, and AI to unlock more value and expand the capabilities of their tools. These will cover Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Supply Chain Management (SCM) systems.

Together, they can manipulate data and communicate across systems. Despite data rule changes, RPA, ML, and AI ensure that the bots are operational. They can then assess data and predict outcomes to make informed decisions. It also helps detect data patterns and efficiently extracts the most relevant data for stakeholders.

How Does RPA Drive Efficiency and Productivity?

1. Helps Address Workflow Challenges

Many factors of financial services are redundant but critical for analyzing a firm’s financial health. For instance, transaction and auditing require dedicated preparations, making the process prone to inefficiencies and complexities.

This affects the time of delivery, resulting in missed deadlines. Efficiently identifying bottlenecks and delegating tasks through RPA helps accelerate the financial process and meet delivery deadlines.

2. Reduces IT Burden

With proper training, it becomes simple for regular employees to set up RPA bots themselves. This reduces the burden of reconfiguring infrastructure from IT departments, freeing time for other essential activities.

3. Assists in Optimization of Metrics

Banks often do not have any key metrics to understand where employees spend their time and efforts. With RPA, companies can delve into how teams are managing their time.

There are inefficiencies in manual banking processes. Hence, using the extracted information to reengineer the process for automation makes the operations run more efficiently and effectively.

4. Less Operational Costs and Reduces Human Error

As RPA lowers operational costs, it enables banks to reinvest these funds into more strategic initiatives. This is a great strategy to drive greater results in the long term. By reducing human effort, banks can also prevent costly human errors. Since human errors rank high as a risk factor, this will minimize operational disruption.

5. Better Compliance

RPA helps banks to adhere to regulatory rules, enabling them to track and monitor activities easily. For instance, it helps automate audit generation, audit findings distribution, and audit trail maintenance.

6. Enhanced Security and Scalability

RPA provides solid data security by eliminating human errors, enabling banks to secure sensitive customer data. At the same time, the technology is highly scalable. It is ideal for banks because this sector has to meet constantly evolving market demands. This flexibility helps banks to optimize their processes to meet customer demands easily.

What Steps Must Banks Take to Implement RPA in Finance?

1. Assess the Existing Processes

Before RPA implementation, banks must analyze the current state of all the internal operations and manual activities. This will help understand and bring visibility into areas where RPA can be the most beneficial.

Moreover, evaluating the current processes’ costs, speed, and accuracy can help make more valuable decisions regarding RPA implementation.

2. Determine Use Cases

Check the existing process maps to determine the potential use cases for RPA in finance. It will help identify candidate processes that would benefit from RPA. Carefully check each process against technical feasibility, cost, and scalability.

Also, involve other factors- cost savings, speed of execution, and accuracy gains- that RPA can offer. Furthermore, use the existing data to know where the tech reduces manual labor and fulfills any financial or resource constraints.

3. Regulate Standard Processes

RPA demands well-defined processes and a consistent structure. Hence, it is vital to regulate the standard processes to ensure they are reliable enough to automate. Regulation must include defined data sources, set workflows, task sequences, and a defined documentation practice.

Also Read: How RPA can Revolutionize Financial Organizations

4. Set Process for Implementation

Banks must set clear rules to ensure the correct execution of every automation initiative. They must ensure-

  • The placement of necessary resources is the right
  • The scope of the automation project is defined
  • The anticipated benefits are quantified

Banks can always consult a competent RPA vendor to ensure the adoption roadmap handles all the complexities of RPA implementation.

Conclusion

As per a recent report by Grand View Research, “Robotic Process Automation in BFSI (2023 – 2030),

the global RPA in BFSI is anticipated to grow at a CAGR of 39.4% from 2023 to 2030.

As RPA continues to bloom in finance, it is more likely for the banks to integrate it into their operations.

Besides cost reduction, RPA in finance increases business process efficiency, enabling employees to engage in strategic functions.

In the coming years, banks will seek access to better insights and opportunities as the tech evolves. RPA presents a solid option for financial organizations to elevate their operations and gain unprecedented insight into their activities.

Apoorva Kasam
Apoorva Kasam
Apoorva Kasam is a Global News Correspondent with TalkCMO. She has done her master's in Bioinformatics and has 18 months of experience in clinical and preclinical data management. She is a content-writing enthusiast, and this is her first stint writing articles on business technology. She specializes in marketing technology, data-driven marketing. Her ideal and digestible writing style displays the current trends, efficiencies, challenges, and relevant mitigation strategies businesses can look forward to. She is looking forward to exploring more technology insights in-depth.

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