Currently the finance teams prepares closing statements on monthly, quarterly and annually. The close process is cumbersome with many data pulls and aggregation exercises across many geographies, divisions, business units and departments. The current semi automated close processes can take weeks to achieve.
Goals and Objectives
Data sets, machine learning, deep learning across a large set of business processes sets up the parameters for the continuous close process. The process becomes fully automated and is closed in real time at any point in time of the organization’s choosing.
Enterprise hardware, personal devices, cloud, Big Data and analytics, mobile, applications, business consulting, cognitive technologies, and IoT
Use Case Summary
Automated consolidation and reporting will occur initially as machine learning is applied to the business close processes and data sets. Currencies will be reconciled across geographies to match closing country requirements. All new intelligent close processes will meet revenue recognition and accounting standard requirements.