New invoice matching methods enables complex food stuffs to be matched to retail products, resulting in new levels of control over stock.

Customer Challenge

This manufacturer of meal replacement products has complex manufacturing and supply chains.

The challenge was to enhance and automate the accounts payable process so that complex product and supply chain information could be extracted from the invoices. In addition, the personal knowledge of processing staff about products and supply chain also needed to be captured. The implementation was to be done without disturbing any financial records.

The data automatically flows into the underlying ERP system following a financial control check

Solution Provided

Following a thorough evaluation process, the client selected Kanbina AP, keen to leverage AI and Machine Learning to meet its finance process automation goals.

Kanbina’s AI platform consists of a sophisticated API Management System, which enables the deployment team to swiftly integrate the platform to the customer’s

ERP application, standard and customised ERP workflows, and seamlesslyalign to specific accounting processes.

To meet the client’s requirements that key product and supply chain data was captured and processed by the new automated solution, Kanbina built and trained custom Machine learning models. This also had the benefit of enhancing knowledge retention and removing key man risk, as much of this work was previously executed by senior AP staff.

Impact of Solution

Adoption of the Kanbina MLPA platform has enabled the client to achieve their automation goals in AP and thus deriving the significant improvements they desired in stock control.

The service is able to capture complex product and supply chain information from invoices and match these to the underlying master record data. It has captured the knowledge of processing staff and transferred that to the master record data.

The AP process is now at level 5 process maturity, which is the highest that can be achieved.  This client also wishes to use machine learning in Bank Reconciliation.

Technologies Used

Kanbina Machine Learning Process Automation