9 promising use cases for RPA in finance and accounting

If not, be sure that you know exactly where data must be pulled from in order for the RPA solution to do its job. If there are any improvements that can reduce waste, then make note of them. Additionally, document the steps involved as well as the relevant parties so that when you rpa use cases in accounting deploy RPA, everyone can be on board. This is because there are software solutions that can work straight out of the box and begin providing ROI almost immediately. By using RPA, your finance department can easily prepare up-to-date financial statements, even on a daily basis.

• Effective treasury management (particularly with the addition of business automation and AI) helps your company maximize liquidity and enhances your financial performance.
• This frees up employees to focus on more meaningful work, from building strong relationships with customers, to analyzing data to gain a competitive advantage, to turning great ideas into new financial products.
• IA offers the clearest path towards a true digital transformation for businesses.
• However, in a traditional environment, Finance often spends most of its time painfully getting the numbers right with manual, spreadsheet-based processes.
• Cem’s work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
• An accounting firm faced with inconsistent service delivery, outdated technology, recurring staff turnover, high cost, and a rigid solution mode turned to RPA.

Financial statements and data must be properly input and unkempt in order to accurately predict the future. With the use of bots, your data will be properly collected, transformed, and stored for the purpose of forecasting. Here, we will take a look at all the benefits of RPA in finance, as well as the future of RPA in banking.

Order to cash

We hold education sessions regularly and walk you through one-on-one on everything RPA. Too often, the ROI of RPA is compared to the reduction of FTE hours on repetitive tasks and close efficiency. Instead, it should be assessed on the reduction of negative impacts (like preventing mistakes and the knock-on effects of correcting that mistake). The solution substantially reduced the manual effort involved in calculating monthly, quarterly, and yearly amortizations, and proved a big advantage when auditing financial statements. A firm was looking to streamline a resource-intensive invoice generation and uploading process.

By introducing AI-powered technology into the process, finance teams ensure customers receive accurate quotes, orders are fulfilled correctly, and any issues are resolved seamlessly. Not only will this boost customer satisfaction—it could lead to increased sales and revenue for your organization, too. Automate your activities, including purchasing and receiving goods and services, and integrate them with accounts payable to complete the purchase-to-pay cycle. By supplying all the documents necessary to process invoices both quickly and easily, you’ll reduce turnaround times for payment. Highly manual, repetitive tasks and disjointed application environments make for negative experiences.

RPA Use Cases in Finance

Dean implemented one system for a banking and insurance company that wanted to improve various processes involved in master data management and financial account maintenance. For example, they used RPA to automate three back-office processes related to seizure of financial assets for customers based on official legal requests made by executors. This made it easier to kick off one process that could access various databases and freeze relevant amounts across various accounts and two different core banking systems with minimal team member interaction. People could then focus on more judgement-oriented tasks such as reviewing and validating the data being updated.

Utilize robots to report time and create and post payroll for your biggest asset—your employees. When it comes to invoicing your customers, there are a lot of manual steps involved. Generating the invoice, validating it before it goes out, posting receivables, and reporting—the list goes on and on.

Challenges of Implementing RPA in Finance

With precise data extraction and rapid report generation, RPA empowers financial executives to make informed, data-driven decisions. The bank account opening process requires a manual data entry or even a client’s physical presence at the bank branch. If clients make a mistake during data entry, the client support specialists have to reach back to them to clear things up. This action takes time from your employees and slows down the overall process of registration.

RPA in tax accounting is also becoming prevalent for more complex tax activities, such as the preparation of tax returns, and calculating book-tax differences. Read this guide to better navigate today’s fast-changing tech landscape and advance your finance transformation initiatives. It’s essential to have unified policies, procedures, and systems in place before utilizing the power of RPA in your Finance department. Otherwise, it will accelerate the production of waste alongside the automation of valuable activities.

Use cases and applications of RPA in accounting

This can be anything as simple as reconciling data between spreadsheets and parsing out information from invoices, to something more complex such as taking high-level decisions based on performance indicators. 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.

A well-built ID transcribing system grants the data accuracy, so client support employees will have less work to be done. Their task is to monitor the transactions on high-risk accounts and detect suspicious activity. Investigators have to manually check every domestic and international transaction made with this account. It’s a time-consuming process because employees retrieve checks on transactions manually from a database.

Invoice processing

Transform paperwork into robot work, and watch how customer, partner, and employee experiences improve. It can be used to reduce the forgery and other kinds of frauds since the validation of the credit card forms and processing will be done by RPA bots. Many data gathering will be required at the time of mortgage lending, loan processing. By using the OCR, RPA software can feed the client information from documents and reports can be generated if required same can be mailed to the concern management person, where they can give their inputs. The complex calculations of profit and loss report can be done by using RPA computing. Some of the criteria for a work to be identified to be a RPA candidate is it should be highly manual, repetitive and should involve high volume process, should be a rule based, the system should be stable.

It reduces (potentially eliminates) the invariable risks of manually performing tasks and human error, and delivers dependable financial data. Using RPA, the company has been able to reduce human error in repetitive clearing processes, free the team from mundane tasks, and improve integration with clients’ finance departments. By applying automation and analytics, robotic process automation frees individuals to turn to value-adding activities that take advantage of their professional skills, training, and experience.

Automate credit limit request underwriting

With the time saved from the day-to-day mundane tasks, people can use their saved hours on other revenue generating activity. Notification to the customers can be handled by using the BOTs in the month end or the scheduled time. We are receiving the monthly statements of our accounts with the balance statements. For the employee payroll management, we can use RPA effectively, which leverages the time-consuming task like employee timesheet validation, information verification, payments calculations.