Open Access

Luana Siegel

• This thesis is a study examining the potential of implementing automation solutions in the financial month-end close of TomTom Business Unit Automotive Finance. The aim of this study is to identify processes with potential for the implementation of Robotic Process Automation and/or Artificial Intelligence, to improve month-end close in the selected case company. The theoretical framework delimits Digital Business Transformation from Digitalization and Digitization. It provides background knowledge on Robotic Process Automation and Artificial Intelligence and points out how digitalization impacts the finance function of the future. Furthermore, factors for successful implementation of automation are discussed. The study applies the strategy of action research performed in a two-staged research examination, including the performance of interviews and the analysis of the interview results. The interview’s goal was to examine month-end close processes, gathering information about the process itself and its characteristics, to have a solid understanding on the processes for the subsequent analysis. The data analysis was conducted applying two different approaches, varying depending on which automation tool best suited the process. The research result showed that half of the processes in month-end close of Automotive Finance have the automation potential. This automation is more related to the implementation of processes into SAP Analytics Cloud and the use of included Artificial Intelligence features than to the use of Robotic Process Automation. This result confirms the theoretical findings on the high potential of automation in reporting and endorses the automation potential of month-end close in TomTom Business Unit Automotive Finance.