AR Automation Is a Cash Flow Problem, Not an Operations Problem
Bank of America's research puts $600 billion trapped in U.S. accounts receivable. The real problem isn't slow payers — it's treating aged receivables as inevitable. They're not.
There is $600 billion sitting in U.S. accounts receivable that companies think they have, but cannot actually spend.
That number comes from Bank of America's director of global receivables, Andy Murphy, who described it in a recent PYMNTS interview as capital "trapped in excess working capital in accounts receivable alone in the U.S." Much of it is overdue invoices that drifted past expected payment windows, sitting on balance sheets as theoretical assets while functioning as practical liabilities.
Murphy's framing is worth sitting with: "Outstanding receivables can often appear as a potential asset on a balance sheet, whereas, in reality, they act as a liability until those are ultimately paid and applied."
That sentence describes the core lie embedded in most small business accounting. Revenue is booked. The invoice goes out. The cash — somewhere between 30 and 120 days later — eventually arrives, or doesn't. In the meantime, that money is not available for payroll, supplier payments, or growth. It may require short-term financing to bridge the gap, which Murphy noted "can be very expensive."
The problem is structural, and it gets worse at scale. The Bank of America research also flagged deteriorating DSO (days sales outstanding) across the market — meaning the gap between invoice date and collection is widening, not shrinking, even as payment technology has never been more capable.
Why AR is treated as an operations problem when it's actually a cash flow problem
Most businesses manage AR the same way they did fifteen years ago. The collections team reviews an aging report, prioritizes by invoice age and value, and manually reaches out to customers with outstanding balances. Murphy described this directly: "That reactive approach … means that quite often companies do not necessarily have the capacity to reach out to all of their customers with outstanding invoices."
The word "reactive" is key. Reactive AR management means you respond to late payments after they happen. By the time an invoice shows up on an aging report as 60+ days overdue, the damage is already done. The customer has been trained that late payment is acceptable. Your cash position has already absorbed the hit. The relationship has been implicitly negotiated in their favor.
But the framing of AR as an operations problem — a thing you manage after the fact — obscures the real lever. The moment an invoice is sent, the clock starts on a cash flow event. Whether that event settles in 14 days or 90 days is not random. It is partly determined by the customer's payment culture, but it is also heavily influenced by how aggressively and consistently you follow up.
Companies that treat AR as a cash flow discipline — not a back-office cleanup task — don't wait for invoices to age. They build systematic follow-up into the collection process from day one: automated reminders calibrated to the customer's payment history, escalations triggered by behavioral patterns, payment links in every touchpoint, and real-time visibility into what's actually at risk.
The gap between "on the balance sheet" and "in the bank"
The accounting problem Murphy identified — receivables appearing as assets when they functionally operate as liabilities — is not just a semantic issue. It affects decision-making.
When a business owner looks at their books and sees $150,000 in outstanding receivables, they may feel more comfortable with cash-intensive decisions than they should. A hire. A vendor contract. A marketing spend. The receivables look like a cushion. They're not. They're a prediction — and predictions age poorly.
DSO deterioration means that prediction is becoming less reliable across the market. Extended payment terms are part of the cause. So are the inefficiencies in legacy AR processes: manual outreach that doesn't scale, static aging reports that don't capture payment behavior, and collections workflows that treat every customer the same regardless of history.
The emerging alternative, as Murphy described it, is moving from reactive collections to predictive ones — "evaluating risk holistically, combining aging data with transaction patterns and payment behavior" so that intervention happens before invoices age into risk categories. That requires automation. It requires data. And it requires treating AR not as paperwork but as a managed cash flow function.
What automation actually changes
AR automation is not a feature request. It's a reframing of who controls the payment timeline.
Manual AR hands the collection cadence to the customer. When your follow-up depends on someone on your team having bandwidth to send an email, the customer who ignores the first invoice simply waits. A business running 50 open invoices at any given time cannot manually chase every one of them with the frequency that actually moves payment behavior.
Automation changes the structure of that equation. Systematic reminders go out on schedule regardless of how busy the team is. Payment links are included in every touchpoint. Escalation logic triggers based on days outstanding, not on whether someone happened to pull the aging report that week. The result is not just faster collections — it's a consistent, documented collection process that changes customer behavior over time.
For freelancers and small agencies, the gap between "sent the invoice" and "deposited the payment" is often where cash flow crises live. A two-person agency carrying $80,000 in outstanding AR doesn't have a revenue problem. They have a collection timing problem. And when that timing problem compounds across multiple clients, each with their own payment cycles and follow-up sensitivities, it becomes genuinely difficult to manage without some form of systematic support.
Tools like AgentReceivable exist precisely for this scenario — automating the follow-up cadence, syncing to Xero and QuickBooks so AR data stays current, and removing the manual overhead that causes collection gaps in the first place. The $600 billion figure Bank of America cited is not distributed evenly. Disproportionate amounts of it sit with smaller businesses that lack the dedicated AR staff that larger enterprises have.
The strategic reframe
The Bank of America research positions AR automation as "a strategic shift toward treating cash flow as a managed outcome rather than a residual effect of sales activity." That framing is accurate, and it's useful.
AR has historically been treated as the tail end of the revenue cycle — something that happens after the real work of closing deals and delivering services. The research argues, convincingly, that this is backwards. Cash doesn't land in your account when you complete the work. It lands when a payment is collected. Everything between invoice and collection is a managed process, and the quality of that management directly determines your actual liquidity position.
The deteriorating DSO numbers suggest that, at scale, most businesses are not managing that process well. The $600 billion in trapped working capital is the aggregate consequence.
Treating AR automation as a cash flow discipline rather than an efficiency upgrade changes both the priority assigned to it and the way it gets measured. The question stops being "how much time does this save" and becomes "what is this worth to our cash position." For most businesses running on tight margins and variable collection cycles, the answer is significant.