RPA integrated with ML and AI can take up the tedious and monotonous task of performing repetitive tasks of generating invoices and POs. This will keep track of comparing the raised invoices against POs, keeping the audit in place on a real-time basis. KYC is a necessary and time-consuming process that the BFSI market has to perform for every customer.

rpa in finance use cases

This overview covers the major robotic process automation use cases in different industries and highlights some RPA service implementation tips and best practices. For example, RPA bots can transfer patient data to third-party healthcare analytics services to deliver accurate diagnoses and improved patient care without restricting any confidentiality regulations. Bots can be used to find all the customer’s accounts year-end balances, and return the audit to the audit clerk in the form of a Word document. Moreover, entries will be automated, fast, and accurate..Learn more about expense management automation. While modern payroll software provides a good solution for this process, some companies rely too much on legacy systems to be able to make the switch to modern payroll software. RPA bots can monitor network and server usage data and send the reports to employees.

#1 Accounts payable and receivable automation

Global retail companies need to harmonize SKU (stock keeping unit) data from multiple markets to be able to look beyond numbers to insights such as, “What is our toothpaste market share in Eastern Europe? The bot can also automatically adjust the hotel’s room prices, based pre-determined rules, to match the competitors with minimal human intervention. RPA bots, on school portals, can automatically create meeting time slots between the student and the relevant advisor based on the student’s current status. Inventory management typically involves reconciliation across multiple systems as companies find it challenging to bring all inventory management features under one system. Inefficient absence management costs companies ~ $4K/year and $3K/year for each hourly and salaried employee, respectively. Payroll requires repetitive payroll processing, taking into account myriad regulations and company rules.

rpa in finance use cases

RPA can be used to automate repetitive tasks in the front office and back office. Professional software development companies are aware of the mentioned challenges and know how to address them in the most efficient and cost-effective manner. RPA gathers market data, performs data analysis, and generates financial forecasts based on predefined algorithms and models. This allows finance professionals to make data-driven decisions instead of relying on guesswork.

Market Perspectives

While a lot of F&A organizations are now looking at intelligent automation for their finance functions, not everyone knows just what it can do to drive value. Some organizations bring RPA in to automate a few repetitive, high-volume tasks and leave it there. But with advances in AI and machine learning, intelligent automation has massive potential across the board. Digital workers are the software robots deployed within IA, designed with decision-making capabilities to mimic human actions.

rpa in finance use cases

For example, suborganizations within HPE have different templates, processes and approval flows. Some might involve audit and compliance requirements of identifiability for transactions, along with all the respective business requirements on approval flows and amount thresholds. For years, organizations have been trying to find financial improvements through enterprise systems, reporting tools and stopgap measures that attempted to eliminate repetitive manual actions. IA offers the clearest path towards a true digital transformation for businesses.


RPA can automate the process to maintain billing records of customers, invoicing, and reconciliation across its multiple channels and departments. RPA not only handles tedious tasks but also helps in elevating the level of services that can help save time and money. RPA bots are capable of handling rule-based functions the way humans are unable to.

In this article, we are specifically focusing on RPA use cases in finance, such as automated recording keeping and finance control. 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.

Industry-specific processes

However, they do it faster and more consistently than people, without coffee and smoke breaks. RPA solutions allow businesses to collect customer information by accessing databases, gathering data from documents, and social media. Analysts spend a lot of time searching for information on complex government resources, the FBI, Interpol, and more. Robotic Process Automation in finance industry can deal with these tasks and give analytics more time for other tasks.

rpa in finance use cases

The solution helped to automate 80 customer-facing, back-office, and middle-office processes and 90% of the data mining transactions when generating living expense reports. The document is highly labor-intensive and contains a high risk for human errors. RPA bots can track logistics systems and once the delivery occurs, link the shipping data into the warehouse management system. But if your company doesn’t prefer to use one, RPA bots can  partially automate the KYC process. And for edge cases that require human intervention, they can be forwarded to an employee. 81% of companies are already investing in robotic process automation technology to achieve their financial saving goals.

Why is RPA important in finance?

For example, an Indian bank5 leveraged RPA bots to automate different KYC tasks. This led to a 50% reduction in human work hours, and a 60% increase in productivity. While dedicated KYC solutions are emerging, an alternative is using RPA bots to automate portions of the KYC process. For edge cases that require human intervention, they can be forwarded to an employee. For regular cases, RPA bots can speed up processing times, improve security and compliance, and reduce error rates for these customer-facing processes.

  • However, technologies can offer an alternative — Robotic Process Automation, also known as RPA.
  • This funding is on top of the £525 million schools will already be receiving this year to support them with the 2023 teachers’ pay award.
  • As with invoice processing, OCR can help read paper documents, and machine learning can help map data from the documents into the system of record.
  • These and other implications of RPA and AI in banking continue to spur the technological growth of the sector.
  • After all the sprints are completed, the final stage begins, namely, the polishing and implementation of RPA into your business processes.

RPA can extract each meter’s usage amount from the meter’s cloud database, put it on the bill, and automatically calculate its cost/watt. RPA bots can automatically fill out the billing information on each user’s bill and send it to them. The benefit is that, especially in inflationary times, restaurants can adjust their meal prices with respect to ingredients’ costs. RPA-IoT integration can notify whether the production equipment is functioning correctly by transferring its real-time status data, such as pistons’ RPM, heat data, vibration level, etc. The top-10 American colleges, in terms of number of applications, received between 65K-109K applications in 2021. Schools and universities can use RPA for initial screening of applications to eliminate those that do not meet the basic requirement criteria, such as missing documents, spam applications, and the such.

Updating Customer Data

For instance, bots can address routine requests, while more sophisticated queries will be transferred to appropriate human specialists. As the technology continues to advance, RPA acquires embedded system definition more and more applications in the banking industry. People immerse themselves into digital banking, mobile payments, cryptocurrencies, and the other opportunities of Web 3.0.

Once bad data enters the enterprise data ecosystem, it can quickly spread to multiple systems and data repositories. This can result in significant downstream data cleaning and correction work. “RPA can automate and speed this process up, as well as reduce human errors,” Dean said. Instead, you will want to continuously analyze the results that you achieve while considering how to improve even further. By “minding the gaps” in your automation with the use of advanced tools such as Kofax RPA, you can nurture a better means of doing business. Automation gaps often exist when certain activities must take place across different computer systems.

#7 Customer onboarding and KYC processes

Bots can update accounting records,  prepare, and deliver invoices from the right email accounts to ensure data consistency between systems. For example, legacy billing systems need to interface with other systems, which may not have the capability to pull relevant data from APIs. According to Gartner, 80% of leaders in the financial sector are already using some form of RPA for various banking and financial purposes. As we all know, RPA saves time, cost and effort; it also bridges the gap in skilled resource requirements. Here are some significant benefits of RPA in banking that are building futuristic banking and financial powerhouses.

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