Why Carey Kolaja thinks payment behavior is an untapped cash flow forecasting signal
Key takeaways
79% of finance leaders' losing confidence in their cash flow forecasts beyond 60 days, leaving most teams flying blind on anything longer-term.
Payment behavior changes before customers tell you; switching off autopay, moving to slower payment methods, or partial payments are leading indicators of late payments, not lagging ones like aging reports.
47% of finance leaders cite ERP integration complexity as a barrier to connecting customer payment behavior data with the rest of their financial operations; effectively turning a data problem into an infrastructure problem
When it comes to mapping out their strategic direction and predicting what cash flow is available to support their goals, leadership teams spend time tracking what their customers owe. How those customers pay, however, rarely is part of those boardroom discussions.
Versapay CEO, Carey O'Connor Kolaja, considers that a misstep.
Prior to helming Versapay, Carey was the CEO of AU10TIX, the global leader in automated identity intelligence and cyber fraud prevention. She has also held positions at Citi Fintech as the global chief product officer and PayPal as the vice president of global consumer products.
She sees customer payment behaviors (including requests for longer payment terms and late payments) as a forward indicator many leaders ignore; while every CFO watches receivables, most disregard payment choices as operational metrics. In doing so, these finance leaders unwittingly prevent their teams from accessing a critical forward-thinking indicator capable of predicting potential cash flow risks, and unlocking substantial forecasting advantages.
Today (with late payments rising and cash flow forecast confidence waning), that omission is particularly dangerous for building healthy working capital that supports strategic goals.
“How people pay and the signals that surround it have never been a discussion at board meetings,” Carey says. “It’s more a back-office view of what money is still out there that we should collect that can determine our growth rates, not necessarily looking predictively.”
How understanding customer payment behavior improves cash flow confidence
Versapay’s 2026 Cash Flow Clarity Report found that 79% of finance leaders lose confidence in their cash flow forecasts once receivables stretch beyond 30 to 60 days. At that point, collecting invoices becomes increasingly difficult and cash inflows become less predictable.
This growing gap—which Carey refers to as the confidence cliff—makes it more difficult for finance leaders to make definitive decisions around future growth and operational goals; there’s growing uncertainty that they'll have the working capital needed for support. As working capital flexibility tightens, funding becomes more precarious, and that uncertainty causes hiring and investment decisions to slow.
Q&A with Carey:
Q: You say customers’ payment behavior hasn’t traditionally been a conversation in boardrooms. What value do you think it offers at that strategic level?
Carey O'Connor Kolaja: Payment behavior is the earliest business-specific read that you have on the strategic direction of your company. It informs how much cash is coming in and when. Those are two key factors that then drive what you can spend on your own business, what you can anticipate having on your balance sheet, where you want to grow, and where the risks are.
Waning cash flow forecasting confidence also traps finance teams in a self-sabotaging cycle. 81% of finance leaders find collecting open invoices increasingly challenging, meaning teams spend more time chasing payments, leaving them with fewer resources for strategic planning.
To navigate this cliff and escape that loop, finance leaders need ways of anticipating risk earlier in the receivables process to strengthen forecasts and facilitate a more predictable payment cycle. All to ensure there’s enough working capital available to support their goals.
Payment data can help provide that, Carey says. Alongside the financial and operational data accounts receivable teams already use—including open receivables, aging reports, and historical payment habits—payment data can create an early warning system that lets finance teams stay ahead of risk. Building that system, however, means promoting customer payment data out of the back-office and treating it as a strategic input rather than a collections record.
Why payment behavior provides an early warning system for at risk cash flow
It’s the predictive quality of payment data that makes it especially useful for building the early warning system finance teams today need, Carey explains. “Payment behavior isn’t a statement of intent, it’s evidence,” she says. “And evidence is what lets you see the risk before it hits your cash flow.”
To understand how, consider a pattern Carey sees play out with real customers:
“The customer pays by ACH (Automated Clearing House) like clockwork for nine consecutive months. In month 10, they switch to paying by credit card, a costlier method for you, but still on time so no alarm goes off. In month 11, their payment lands three days late. Alone, each change looks minor. Together, they signal a liquidity shift: the customer had cash on hand, then needed a credit card’s float, and now even more time, a sign they’ll likely ask for a payment plan or extended terms next. Catching that shift early is what lets you avoid bad debt later.”
It’s a truth customers won’t always volunteer. “Customers will tell you that they’ll pay you and that they’re fine, particularly if you’ve got them on a call,” Carey says. “But that’s not necessarily what the truth is. Payments data will give you that truth.”
When those signals are aggregated across your customer base and combined with additional data (industry-specific trends that could be adding to financial strain, for instance) finance leaders get an even fuller picture of the challenges ahead.
Q&A with Carey:
Q: What’s the risk of finance leaders not using payment behavioral data as part of their early warning system for cash flow forecasting?
Carey O'Connor Kolaja: If you don't use these signals, you don't avoid the risk; it just means you'll see that risk further down in your business cycles. I think what we're all trying to do as business leaders is minimize and ideally avoid risk, so there are a lot of repercussions in not doing something about it; because other companies will. So, understanding the health and stress of your business, understanding what macro-dynamics are at play, and creating visibility into areas where there wasn't any previously, all helps your business.
How finance leaders can enhance visibility into their customers’ payment behavior
Staying on top of payment behavior (and monitoring payment data) clearly offers a strategic advantage to businesses. And with teams spending more time chasing late payments and cash flow confidence waning, that advantage is becoming increasingly important.
Yet without visibility into all payment patterns (including indicators like aging habits, promise-to-pay timelines, as well as shifts in payments behaviors) it’s impossible to connect that data directly into cash flow forecasting; any advantage payment data could offer is lost.
Which is why effective use of payment data starts with infrastructure. By connecting payment behavioral data with other financial and operational data, you create a single source of truth: one that adds precision to cash flow forecasts, allows you to segment customers by risk, and shows you which customers are good candidates for payment plans or terms.
Yet that type of integrated data environment is still out of reach for many finance teams. That’s evident in our research, where nearly half of finance leaders (47%) see ERP integration complexity as a top barrier to realizing the full capacity of accounts receivable software.
That foundation matters even more with artificial intelligence (AI) entering the picture. “There’s a reason why having clean data that moves between systems is critical,” Carey says. “As you layer in AI, it either amplifies the bad, or it helps you to create an incredible strategic moat around how you better service your customers.”
Get it right, and the posture of your entire receivables operation flips from chasing what has already gone wrong to reaching out before it does. “The companies that sit at the nexus of relationship data, operational data, and payment data are going to emerge as key winners in the fintech space as you look forward,” Carey explains.
Start making customer payment behavioral data a part of your boardroom decisions
“We can truly move to being predictive about how we better service our customers and how we better protect our business,” Carey says. To do so, however, finance leaders must use all the data available to them to understand what cash flow risks lie ahead, and enable better-informed operational and strategic decision-making.
Payment data is an important part of that mix, an untapped forecasting signal that gives businesses an advantage and finance teams a surer footing atop the confidence cliff. But to use that data effectively, you need better visibility into the behaviors that matter. A stronger payment infrastructure can provide that—connecting data into a single source of truth and giving finance leaders a better foundation of insights to work from.
