Invoices automatically matched to complex drug development projects that enables even finer grain control over expensive research activities.
This high growth pharmaceutical company wished to replace an existing Accounts Payable application as it was deemed not to meet their needs. The customer had outsourced their AP processing to a Top Tier accounting firm, who found the extraction of information from invoices to be frequently inaccurate, thus incurring time consuming and expensive corrections.
The challenge was to provide a system that could extract data from complex invoices with accuracy and automatically match this data to the underlying master record data without creating exceptions. The invoices described drug development projects including manhours, chemicals and scientific equipment.
The company also wanted to complement its AI based R&D capability with an AI based back office.
Kanbina’s real time AI machine learning platform was deemed a strong fit for the client’s exacting requirements. The ability to benefit from out of the box Machine Learning Process Automation for standard AP processing tasks, combined with the option to commission tailored Machine Learning models for bespoke workflows, off the one platform, underpinned the business case.
MLPA for AP was quickly provisioned on the Kanbina AI platform.
The customer additionally required that manhour data recorded as line items on project invoices were extracted so they could be compared to budgets. To achieve this custom Machine Learning models were built and trained, enabling an upshift in accuracy and productivity, far outstripping the efficiency offered by the previous AP software provider.
Impact of Solution
The transition to a native AI platform for Finance, has enabled the customer and their outsourced accounting partner, to fully gain the benefits of AP and invoice processing automation.
The service is able to capture drug development projects which include manhours, chemicals and scientific equipment and automatically match this data to master records and internal projects. The direct cost of AP services significantly fell as a result.
In addition, the move to an AI based back office has increased the value of this AI based R&D company, and also enables its accountants to expand its AP services to other clients.