What are the Use Cases and Benefits of RPA in Finance?

By automating onboarding and offboarding processes, companies can maintain a clear view of all customers and their information. It becomes easy to add customers automatically when a new one joins and also easy to remove them automatically when they leave. According to a recent report the RPA market until 2024, during which period, telecom and IT appear to be leading the automation trend in business processes, with a phenomenal growth rate (CAGR) of 60%.

examples of rpa in finance

With a widespread presence in different countries across the globe, the major challenge before Zurich Insurance was to follow geography-specific regulations. With the help of the implementation of RPA, they could segregate the standard and general policies; and save a vast amount of time. The outcome was surprising as they could save approximately 50% of the processing cost and time.

Turn finance and accounting into The Foundation of Innovation. We’ll show you how.

HPE’s accounts payable team processes a considerable volume of paper invoices each month and is responsible for recording vendor invoices for subsequent payment processing. Issues come in the form of multiple invoice formats, a range in the quality of scanned image invoices and the use of multiple languages. The company used a combination of OCR and machine learning modules from WorkFusion to mitigate image format and quality challenges. The robots used in RPA are ideal for handling a high volume of recurring tasks without human intervention. Robotic process automation brings out a lot of benefits in different industry niches as it supports high-frequency manual, repetitive, rules-based processes, which are critical for an appropriate service.

RPA can greatly reduce the quantity of manual, repetitive and time-consuming tasks performed by finance experts so they can focus on more valuable activities, such as P&L reporting, Chawla said. Many firms cut processing time significantly and provide earlier access to reports with examples of rpa in finance much higher accuracy. It is no secret that the banking industry has battled to evolve with the times and stay up with technological advances. Adopting technologies has helped banks provide the best customer experience while remaining competitive in the saturated banking market.

Top 15 RPA Use Cases & Examples in Banking in 2023

Outside of these cases, you can dramatically reduce the number of “touches” each invoice requires. As an example, HPE’s contract compliance team is using RPA to help automate many processes involved in ensuring adherence to vendor contracts. One challenge is enabling finance departments to easily create new bots while also providing guardrails.

  • IT process optimization and automation resulted in increased IT performance, cost reduction, and personalized user support.
  • Many firms cut processing time significantly and provide earlier access to reports with much higher accuracy.
  • In addition, the peculiar combination of data in one system purveys better reporting and insights for business growth.
  • RPA has a lot of potential that can revolutionize the entire HR industry bringing in a ton of efficiency and a faster return on investment.
  • Once bad data enters the enterprise data ecosystem, it can quickly spread to multiple systems and data repositories.

Analyze your company operations and functions and determine which of them would benefit most from RPA implementation. Discover the issues that your organization faces and which of them could be solved with the help of automation. Prioritize the issues according to the degree of their impact on the business processes and the potential effect of the RPA implementation. The currently available technologies empower the automation of multiple jobs in different spheres. Noteworthy, only a few occupations can be entirely replaced by technology solutions, while most jobs have a specific array of activities that can be automated.

Robotic Process Automation (RPA) in Finance

IBM is building the industry’s most comprehensive suite of AI-powered Automation capabilities. With IBM Robotic Process Automation, financial services firms like Credigy Solutions can automate more business and IT tasks at scale with the ease and speed of traditional RPA. Software robots, or bots, can act on AI insights to complete tasks with no lag time and accelerate digital transformation. To limit the risks of regulatory fines and reputational damage, financial institutions can use RPA to strengthen governance of financial processes. RPA helps consolidate data from specific systems or documents to reduce the manual business processes involved with compliance reporting. ML goes further by deciding what data an auditor might need to review, finding it and storing it in a convenient location for faster decision-making.

examples of rpa in finance

RPA uses bots to execute complex business processes using the same interfaces people use. Finance departments and institutions are full of operations and processes that are perfectly suited for robotic process automation. It’s up to you as a CFO to deploy robotic process automation in finance to reap the benefits. Try out tools like SolveXia for free to see how you can maximise your team’s productivity and reduce costs. Robotic process automation (RPA) can help finance leaders tasked with modernizing and streamlining processes automate the jobs that accountants perform every day. By implementing RPA, businesses can free up to 30% of a full-time employee’s overall time and save 25,000 hours of rework for an accounting team of 40, according to Gartner research.

The evolution of RPA in finance

Tools that deliver full-cycle accounts payable automation provide a more tailored approach to these tasks. For modernizing finance departments, a full consideration of all these solutions will reveal the best approach for your organization. Applying the right payments to the right accounts and invoices is a process that includes multiple ways to introduce errors. The bot platform helps simplify bot deployment and allows bot modeling, use tracking and error reporting.

The team also created an internal governance framework to provide a complete view for stakeholders across audit, business compliance, IT and finance teams. With an RPA implementation, your financial institution can have customer behavior data automatically sent to specific people in the organization. ML models help group customers into categories based on their behavior, so the most appealing products or services can be recommended to them. For example, banks know which customers might be most interested in opening a new line of credit.

Benefits of RPA in Manufacturing Industries:

A McKinsey research report analyzed all finance operations processes to identify their automation potential as seen below. Averaging automation potential across all functions, they claim that ±42% of finance operations can be fully automated. All organizations require reporting to gain clear insights about their finances, growth, workforce, and clients. Many bank processes involve unstructured data formats (invoice PDFs, bank statements images, etc.) which machines are incapable of understanding.

examples of rpa in finance

But, they are not the only solution that’s worthwhile when it comes to finance. But, finance departments require access to deep insights and real-time analytics, which a solution like SolveXia can provide. While important and necessary work, AP and AR management requires countless repetitive, rules-based tasks. The tasks also demand consistency, accuracy, and adherence to timeline, as they are primarily the subject of financial audits. Thus, for RPA systems to work with your desired efficiency, it’s vital to involve people who are well-versed in accounting and understand your business processes.

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By applying automation, companies cut turnaround times and optimize their internal workflows. Making purchase orders is a mundane yet indispensable activity that takes a large amount of staff’s time. AI-powered software robots can be trained to scan orders for critical data, make the respective inputs in the system, and establish approval requests. Financial services embrace a vast range of functions, from routine number crunching to high-value, goal-oriented business thinking. RPA in finance is applicable in all of these processes since it allows for saving the most precious resource—time.

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