This proof of concept bot has a spreadsheet of client names. The bot logs into Xero to download reports and upload the reports to Jetpack workflow. The video is split into 2 sections. The first part is the bot completing the task for four uploads in 1 minute and 20 seconds. The second part is a human completing the same task in 7 minutes.
In this use case, the bot receives a webhook payload from Safesend that an 8879 has been signed by the client. The bot logs into a computer on the accountant's network. The bot proceeds to download the 8879 to the local computer and then send an API call to archive the return.
A client of an accountant owns and manages multiple properties that needs to go into the client's Schedule E. The client uses a property management software that can export accounting information into a spreadsheet. After the information has been reviewed for accuracy, the accountant wants to input the data using automation.
Manual data entry is estimated to be 15 hours, assuming the accountant works with no breaks or distractions and in perfect conditions. If the numbers do not tie, reviewer has to check for incorrect inputs across 7,808 points of input.
An RPA was built to read from the spreadsheet and enter data into tax preparation software. The RPA finished the job in 42 minutes. All totals tied to the spreadsheet.
An accounting firm had a pain point where 50+ K-1s for a client are received very late into the season. Since the tax preparation software only allows one person in a return at a time, one person has to rush to enter all the k-1 information into the tax return.
This solution is in two parts:
The video sample shows 34 rows in the spreadsheet where each row is a K-1. Each row has 12 data points. All data was inputted in 1 minute and 23 seconds.
A firm needs to make determination for clients if a 3115 letter needs to be filed with a return based on specific criteria. This is decided upon completion of the return. The firm communicated the parts of the software that needed to be checked. After parts of the return are checked, if the return fall under the criteria, inputs in the tax software are changed and footnotes are added to the return.
These would require accountants to always check all the inputs and make decisions based on the rules. Then the accountants would need to copy and paste footnotes into various part of the return.
An RPA was built to navigate the return and read the inputs within the tax software. The rules in the RPA would decide if the return required a letter, then RPA would navigate and input the footnotes into the return. Consistent returns were generated for this letter and accountants did not have to manually check the need for the 3115 letter.
A firm wants to email invoices from their time and billing system but did not want to use the system's built-in tools due to certain features that were lacking. The sending of the invoices would be done on a monthly basis. The firm needs were:
All firm requirements were met with an RPA. The firm sends all email invoices in 5 minutes per batch. Each batch contains more than a hundred emails.
A firm receives email notifications from an online products and services that the firm uses. Emails were sent to a shared email account that multiple staff monitored. Client wished to automatically process incoming emails based on contents of the email.
An RPA was built to mark the email as read and archived. The notification was logged into a spreadsheet on the local file system. System is fully automated with no interaction required.
A firm was transitioning from one tax preparation software to a different tax preparation software. When the returns were reviewed after conversion, it was noticed that multi-state depreciation and book depreciation was not properly converted. The prior software has the ability to export depreciation information to a spreadsheet.
After some reformatting of the spreadsheet, an RPA navigates the new tax software and enters the depreciation data from the spreadsheet into the converted return. This relieved the stress of the transition to the new software and alleviated concerns over the accuracy of manually inputting the depreciation data. This was applied to a number of clients that had multi-state and book depreciation data.
A firm enters staff hours into payroll manually. They want to use the hours from their time and billing system export to build a report that can be imported into their payroll. Unfortunately, the export did not have all the information that is needed by the payroll processor.
An RPA was built that would streamline the process. A CSV file is exported from the time and billing software. Additional information that is not part of the CSV file is pulled from the time and billing database and merged into the CSV file. The CSV file is then formatted to be imported into the payroll software. The resulting semi-monthly payroll is more efficient with lower chance of error.