The Non-Nerdy Guide to Artificial Intelligence in Order to Cash
The importance of data for decision making by a software can be observed when you try searching for directions on Google Maps in offline mode. In the absence of live data, it only proposes a list of possible routes but can’t tell you which is your best option now.
The importance of data for decision making by a software can be observed when you try searching for directions on Google Maps in offline mode. In the absence of live data, it only proposes a list of possible routes but can’t tell you which is your best option now. The AI-engine of Google Maps uses live information collected through internet to make decisions which simplify your life
Can Artificial Intelligence (AI) in Order to Cash (OTC) also make such useful predictions when equipped with the right data?
After all, there is no dearth of data on customer behaviour, payment patterns and ordering history, etc. Could ML start making sense of all this information to make useful predictions such as likely delay in payments, validity of customer claims, missing remittance values or increased customer risk? The answer is YES.
To discover more, we invite Credit Managers to this webinar where they could gain a comprehensive yet fundamental understanding of:
- Why data is a must for automation and which data do you need for it?
- Which everyday OTC decisions could machine learning make for your teams?
- The cleverness behind the logics used to arrive at all these decisions
- How the OTC landscape could benefit from this autonomous decision making!
