CFOs face rising costs from fragmented payment systems, Tungsten Automation says
Tungsten Automation Head of Payments and Embedded Finance Andrew Ng said in September that fragmented payment systems are driving up costs for CFOs. He noted that payment execution has become commoditized, leaving the real value in making the right payment decisions.
Ng explained that governments worldwide are expanding electronic invoicing rules, forcing businesses to replace PDFs with standardized transaction data to enable better data sharing. He said this structured data creates the largest involuntary data‑cleansing exercise for B2B payments in commercial history. Ng added that AI can be used to decide which parts of the payment stack no longer need separate controls, reducing operating expense. He also said he continues to see large companies rely on email or Teams messages for payment approvals.
“What e‑invoicing gives us that is really exciting for payments is a structured schema, validated counterparty identified set of transaction data at genuine scale arriving over a network instead of in a PDF,” Andrew Ng, Head of Payments and Embedded Finance, Tungsten Automation said.
“Payment execution alone is increasingly commoditized. The durable value as I see it today is in making the right payment decisions,” Andrew Ng, Head of Payments and Embedded Finance, Tungsten Automation said.
Historically, organizations have accumulated payment infrastructure one decision at a time, resulting in separate controls, approval processes, data models and reconciliation workflows. This fragmentation makes basic financial questions surprisingly difficult to answer across an enterprise.
What we know
Andrew Ng is Head of Payments and Embedded Finance at Tungsten Automation.
The interview was for the September edition of the “What’s Next in Payments Series: The Fall Draft.”
Governments around the world are expanding electronic invoicing requirements, requiring businesses to replace PDFs and other loosely structured documents with standardized transaction data.