Robotic Process Automation (RPA) – automation
SAP Robotic Process Automation (RPA) is about tools for accelerating and automating manual business processes executed with SAP. Robotic Process Automation allows you to automate repetitive tasks performed manually by system users.
Artificial intelligence (AI) – reliable analyses
Thanks to the mechanisms of Artificial Intelligence (AI) built into the SAP S/4 HANA Cloud system, it is possible to predict and auto-fill large amounts of data in order to process complex analyses and provide the best answers on this basis.
Machine learning (ML) – accurate decisions
Machine Learning is nothing more than a set of algorithms that, based on the gathered experience, introduce corrections and updates in their functioning. ML can work on sample or historical data and help in making predictions or decisions. The features available in SAP S/4HANA Cloud combine the power of machine learning, artificial intelligence, and RPA to provide intelligent process automation for enterprises. Machine learning and artificial intelligence are based on cognitive reasoning, allowing the so-called bots to analyze, make decisions, react, and continue learning.
Using SAP S/4HANA Cloud in accounting and finance
One example use of artificial intelligence algorithms in SAP S/4 HANA Cloud is the SAP Cash Application financial process.
The number of customer and bank files increases as every company grows, which increases the need for an accounts receivables team, which must be able to handle high volumes of payments. While solutions based on the available rules have been developed, there is still a percentage of payments and invoices that require some manual interventions. This includes sending a payment advice received via email or manually settling invoices and payments suspended due to missing or incorrect data entries.
The model is trained on the basis of historical billing information that is sent from SAP S/4HANA to the SAP Cash Application cloud service, providing you with the matching criteria. Training can be scheduled on a regular basis to ensure that changing behavior is recorded, so that the model can continuously adapt.
Once the model is trained, when new bank statements are received (usually daily), they are sent to the service along with open receivables – on this basis the machine learning model can infer matching proposals. The proposals are returned to SAP S/4HANA and those that meet the configurable trust threshold are automatically cleared for full automation. If there are multiple payment proposals, they are presented to an AR accountant as part of the standard Fiori application.
With this type of machine learning service, you can achieve tremendous gains in productivity and reduce errors in the financial department.
If you want to learn more about other applications of Machine Learning in SAP S/4 HANA Cloud, please contact us using the form. Our experts can demonstrate the RPA algorithms built into SAP S/4 HANA Cloud.
