The Importance of RPA in Accounting and Auditing

Robotic process automation (RPA) is the use of cutting-edge technology to streamline monotonous, high-volume processes and enhance workflow. A robotic process automation company's apps that integrate AI and machine learning can assist firms in managing, deploying, and optimizing automation to carry out a variety of office duties. More and more industries are using RPA to complete laborious tasks. Auditing and accounting fall under this category. A company's foundation is its accounting department. Without accurate financial reporting, businesses would struggle to monitor their productivity and expansion.

The job of internal staff is made easier by RPA's fast update of the accounting process. It carries out a variety of duties, including financial statement audits, credit card processing, account opening or closing, customer onboarding, and processing loans for mortgages.

Account Payable (AP) and Accounts Receivable are among the duties performed by financial institutions (AR). Both of these tasks entail a great deal of repetitive manual labor. Losses and human error are now more likely. To put it another way, paper-based financial processes are inefficient and time-consuming. The answer is robotic process automation (RPA). A robotic workforce can collect, analyze, and produce results based on the data. It automates the creation of financial reports and gets rid of mistakes and contradictions.

Let's examine the particular advantages of RPA in accounting and auditing.

RPA in the Practice of Public Accounting

Public accounting firms have already expressed interest in RPA, notably with regard to taxes, advising, and assurance services. RPA software robots, for instance, have been used to successfully automate a sizable portion of tax-related tasks, including the preparation of tax returns and the calculation of book-tax differences

RPA is additionally made available to clients as an advice good and service. Due to the heavily regulated nature of audit services for public businesses, RPA for auditing services is still in its early stages, even if RPA software has been widely adopted for tax and advising tasks (Wood et al. 2018). However, it is crucial to talk about RPA applications for auditing services. Revenue audits can be automated by software robots that carry out rules-based tasks to carry out reconciliations, analytical operations, and dual-purpose procedures, as demonstrated in Exhibit 1. (e.g., internal control tests and tests of details).

Revenue is often a high-risk sector in audit engagements. Automating tasks that do not need auditor judgment has the potential to increase audit quality by transferring auditors' effort to examining the differences caused by RPA software.

RPA for Analytical and Reconciliation Procedures

By entering into a client's secure file transfer protocol (FTP) site, RPA can help auditors with the audit of revenue by retrieving relevant audit evidence, such as the listings for current and prior year sales and the trial balance. The total sales according to the listing can then be calculated by RPA and compared to the total according to the trial balance. Assuming the figures are reconciled, RPA may then determine whether the overall revenue amount from the current and previous year listings is considerably different, and create an alert if the difference exceeds a certain threshold.

Dual-Purpose Audit Tests Using RPA

RPA can be programmed to determine whether the price and quantity differ across sales invoices, sales orders, and shipping documents. It can also be programmed to warn users when there are price and quantity discrepancies in a transaction. Automating these processes allows auditors to redistribute their time to higher-value tasks, improving the audit's overall quality. RPA software enables auditors to understand the client's business operations better and, as a result, more accurately determine the risk of material misstatement.

Three-Step RPA-Based Audit Process

Technology-based process improvement known as RPA is projected to be used in auditing to replace manual and tedious audit duties as well as spur the re-engineering of audit procedures. Public accounting firms can use the RPA implementation pathway to determine whether RPA is a good fit.

The three main phases of RPA implementation are as follows:

● Process comprehension
● Data standardization for audits
● Automatic audit test execution

Process Comprehension

Theoretically, RPA might be an excellent fit for many audit processes. The audit processes with defined audit activities that are time-consuming and repetitive and don't require audit judgment would benefit from RPA the most. By taking into account subject-matter expertise, such as that of revenue audit leaders, and figuring out the actual hours spent executing audit duties, public accounting firms may be able to pinpoint an audit process where RPA might provide value. The frequency with which a company must carry out a specific task, largely based on the volume of audits performed similarly, is another crucial consideration in justifying automation.

Data Standardization for Audits

RPA audit programs require uniformity across data fields in order to function as intended. Data field names in different audit-related reports that include the same information may differ because audit-related data may come from several sources, such as the client's ERP systems or outside asset managers. If so, the planned audit test cannot be carried out by RPA software. As a result, public accounting firms are required to develop an audit data standard for each operation that RPA will replace as part of the second stage of the deployment process.

Execution of Audit Tests

The software must be programmed to automatically carry out audit tests before being used on actual audit engagements. This is the last phase in the RPA audit implementation architecture. Public accounting firms can use a variety of RPA software solutions, but two of the more well-known ones are BluePrism and UiPath ( and, respectively). Adopting ready-to-use RPA software packages has the benefit that little to no new programming is needed. However, even though they demand additional programming abilities, programming languages like Python and R can help with the deployment of RPA-based audit tasks. However, libraries that are highly helpful for RPA functions already exist in Python and R.

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