Electronic invoicing and source-to-pay company Basware is deepening the ability for corporate customers to be able to analyze accounts payable data.
The company announced Tuesday (April 16) that it is enhancing its offering to link users to analytics capabilities to manage Key Performance Indicators (KPIs) and accounts payable workloads. The upgrades come in the form of two additional dashboards for users of the Basware Analytics tool, AP Performance and AP Productivity.
The AP Performance dashboard provides benchmarking data for process durations within an enterprise. AP Productivity offers detailed insight into an organization’s invoice backlog, and promotes enhanced invoice flow management. The tool can predict the risk of late payment, enabling companies to prioritize which invoices to address first.
Basware Product Manager Kevin Kamau said the new tools are “all about efficiency and productivity.”
“You can’t achieve it unless you automate AP department and shared service center processes, and know in detail where bottlenecks are and how invoices are being handled,” he said in a statement. “With the help of Basware Analytics, our customers have full process overview and they can drill down to details and get actionable insights to improve their processes.”
He added that the analytics can be key to understanding invoice processing costs and opportunities to improve efficiencies in the accounts payable space.
“Our integrated analytics delivers insights for both shared service centers and customer organizations to improve spend, optimize P2P process, and capture savings from early payment discounts to bottom line,” Kamau added.
Earlier this year Basware launched a machine learning predictive analytics solution, the Approval Confidence Index, to its offering that evaluates the likelihood of an invoice approval based on a range of information. The solution aims to progress towards the ability to automate routine transaction processing so human approvers would only need to address invoice exceptions, the company said at the time.