The CFO’s Treasury Stack Is Learning to Move Money, Not Just Monitor It
PYMNTS | ·
Corporate treasury technology has perennially been a visibility game. Banks, treasury management systems and FinTechs promised CFOs a better view of balances, payments, liquidity and forecasts. And the provider landscape did indeed provide that view. But better dashboards are becoming table stakes just as artificial intelligence gets better at interpreting the financial data behind them. […] The post The CFO’s Treasury Stack Is Learning to Move Money, Not Just Monitor It appeared first on PYMNTS.com .
Corporate treasury technology has perennially been a visibility game. Banks, treasury management systems and FinTechs promised CFOs a better view of balances, payments, liquidity and forecasts. And the provider landscape did indeed provide that view.
But better dashboards are becoming table stakes just as artificial intelligence gets better at interpreting the financial data behind them.
Bank of America’s latest AI push illustrates where the market is heading. The bank expanded Ask Global Payments Solutions (AskGPS) with an Intelligence Hub designed to bring together client, account and relationship information and use AI to surface treasury insights. Initial capabilities, shared via a press release with PYMNTS on Tuesday (Sept. 29) include intelligent treasury management reviews, account schematics showing liquidity structures and fund flows, and relationship intelligence intended to identify changing client needs.
Separately, American Express on Wednesday (Sept. 30) announced a new corporate card and expensive management platform with AI features; while Citi on Tuesday launched a new service that enables its bank clients to access multiple cross-border instant payment markets through a single account structure
The next generation of treasury infrastructure is being built to connect APIs, SWIFT, host-to-host connections, ERPs, treasury management systems and increasingly real-time payment networks. Layer AI over that connectivity, and software can potentially progress from seeing where money is, to understanding where it needs to be, to helping put it there.
Read more: Fed Finds B2B Payments Went Digital, but the Paperwork Didn’t
Artificial intelligence is beginning to turn treasury software from a system that organizes financial information into one capable of interpreting it. At the same time, instant-payment infrastructure is making it possible to move money around the clock.
Treasury teams have historically operated with a gap between recognizing a financial condition and acting on it. The important shift today isn’t from manual treasury to AI treasury. It is from observation to execution. Financial software spent years aggregating information that previously lived across bank portals, spreadsheets and enterprise systems. The next generation is being asked to interpret those signals.
After all, once software can understand that a company has $30 million sitting in one account, a large obligation approaching somewhere else and receivables expected later in the day, the obvious question becomes. Why stop at generating an alert?
The PYMNTS Intelligence report “ SMB Growth Monitor: How Firms Use and Choose Credit Cards ” found that when small and medium-sized businesses were asked about factors that influence their choice of a primary corporate card, 15.7% mentioned “better card and spending analytics” and 13.8% cited “allows for better expense management.”
“Payment execution alone is increasingly commoditized. The durable value as I see it today is in making the right payment decisions,” Tungsten Automation Head of Payments and Embedded Finance Andrew Ng told PYMNTS for the September edition of the “What’s Next in Payments Series: The Fall Draft.”
Instead of maintaining infrastructure around individual payment rails, Ng argued that companies can increasingly concentrate investment in what he describes as an overarching control plane: shared data, policy and approval controls, AI-driven recommendations and access to multiple payment rails.
“Multi-rail in one place,” Ng said, contrasts with a legacy environment where “so much legacy payments is infrastructure per rail.”
The PYMNTS Intelligence report “ Smart Spending: How AI Is Transforming Financial Decision Making ” found more than 80% of CFOs at large companies are either already using AI or considering adopting it.
See also: The Finance Stack’s Great Unbundling Has CFOs Asking What They Need to Own
Perhaps the biggest change in treasury management is that cash no longer needs to wait for the banking day. Bank of America said Tuesday (Sept. 29) that corporate RTP transaction volume had increased 48%, while transactions above $1 million jumped 351%. The bank highlighted liquidity management and intercompany transfers among emerging applications for the network.
“What real-time transaction data is doing is enabling us to have a forward-looking assessment,” Boost Payment Solutions Chief Technology Officer Rinku Sharma told PYMNTS in April. “The question used to be what happened. Now the question is, what should we do about it right now?”
Instead of finance teams periodically determining where liquidity needs to move, software could increasingly monitor conditions continuously and recommend, or even under defined circumstances, execute, the appropriate response. Those capabilities move the competition below the dashboard and into the financial plumbing.
And the competitive landscape could be more turbulent abroad than at home for treasury providers.
The PYMNTS Intelligence report “ The Cross-Border Opportunity: How Payments Innovation Can Help SMBs Go Global ” found in May that while traditional banks remain the dominant provider for international payments, FinTech companies are expanding their role by turning infrastructure that once required dedicated systems into services that can be purchased as needed.
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The post The CFO’s Treasury Stack Is Learning to Move Money, Not Just Monitor It appeared first on PYMNTS.com .