In this use case we automate the reconciliation process by extracting financial balance sheets from SAP with our RPA technology. We make use of Pandas to perform data transformations at a rapid speed to reduce employee idle times, increasing work satisfaction while ensuring all SLA's are met.
Every month employees at the finance and accounting department of a global car manufacturer have to export last month’s balance sheet and banking statement from SAP. Then, these two exported files have to be reconciled into different account categories split over 30 Excel sheets. These final Excel sheets serve as a check whether all financial data adds up and is correctly filled out in SAP.
The creation of this complete template happens every month and is done by hand. Think about long-running Excel calculations including V-Lookup and if-statements. This is a very mundane and repetitive task which is prone to errors. The employees only have a single day to complete this process next to other end-of-the month related processes. Therefore SLA’s are not always met. Building an RPA solution which automates the reconciliation process helps the employees to focus on work that matters, decrease throughput times and reduce errors.
Months to ROI
Of effort automated
Hours saved annually
Of SLA's met
We created a digital workforce using RPA technology to automate the complete process of balance sheet reconciliations. Our goal was to significantly increase the speed this process, while reducing idle time and errors. The robot is triggered each month and is build to perform the following steps:
Our robot is able to fully automate this process and save over 500 hours on a yearly basis. Our solution is effective, efficient and reliable. Workers can stop wasting time on manually creating and checking the balance sheets and refocus on work that matters.
Integrated applications for this case