Cash APplication Machine Learning: A C-Suite Perspective
Cash Application Machine Learning
Before beginning to leverage CAML technology, it is important to have clear understanding of the requirements pertaining to the Order to Cash process. This can be done by drafting comprehensive list of necessary features relative to the functionality of the solution.
Step 2:Prioritize the list and identify the key features that are essential in order to recieve the most value from CAML-based automation in the Order to Cash process.
Step 3:Conduct an evaluation of the features offered by the CAML-based solution and compare them against the requirements that were identified. Any discrepancies must be addressed with the relevant stakeholders and discussions should be held to determine whether to pursue lack of available features or find alternative and more specialized solutions for more comprehensive setup.
Step 4:Verify that the CAML-based solution is properly licensed and maintained to ensure optimal performance. Additionally, the solution should adhere to the applicable laws and regulations prevailing in the jurisdiction and industry.
Step 5:Once the solution is secured, review how to activate the automation process. This is done by selecting the appropriate payment ledgers and respective party records for the system to utilize in its learning process.
Step 6:Create unique rules for the system, based on specific criteria and standards, that will permit it to make informed decisions when carrying out its activities.
Step 7:Train the system by providing it with sample data sets, to enable it to appraise and classify payments correctly. Furthermore, examine the generated results, adjust the system?s parameters accordingly and if required, properly re-train the system.
Step 8: With the system trained, test and evaluate it on larger data set to ascertain its accuracy, detect any effects of data accuracy on the automation process, and further enhance the system to increase productivity.
Step 9:Once the system is properly configured, launch it for full scale operations. Use metrics and analytics to track the system?s performance.
Step 10:Regularly audit and monitor the system to identify mistakes, optimize processes, and ensure minimal errors.
Given that Order to Cash processes involve multitude of payment data, manually processing it can prove to be an arduous, prolonged task. Hence, CAML solutions offer the necessary technology to unravel this drawback and liberate executives from cumbersome financial activities by providing automated cash application operations. By following the step-by-step guide provided in this article, finance personnel can deploy the power of Machine Learning to expedite the Order to Cash process and enable efficient decisions that provide lasting results.
