Why Reactive Collections Quietly Drains Your Cash Flow (and How to Stop It)

Collections has traditionally been a numbers game. When invoices go overdue, collectors get busy: emailing, calling, and negotiating payments with as many customers as they can. When your next round of invoices goes overdue, it gets added to your to-do list. 

When working off spreadsheets and data dispersed across emails and notes, it’s hard to get a clear view of your entire payment ecosystem until someone misses a due date, and there’s no way of prioritizing follow-ups once they do. This makes for a process that’s inefficient and largely reactive. Collections teams are left chasing payments while still missing out on key opportunities to move the needle on cash flow. 

Yet in an environment where business margins are shrinking, customers are taking longer to pay, and working capital is becoming increasingly strained, agility is more important than ever. 

A proactive collections environment is key to achieving that. And to understand exactly what it looks like in practice, we spoke with Jodi Bergman, Senior Director of Product Management at Versapay, who has spent years working alongside collections teams as they’ve made the shift. The insights that follow come directly from that conversation.

81% of finance leaders say collecting outstanding receivables is a significant challenge. That’s because the processes they have traditionally relied on are reactive. Collectors spend their time chasing payments, digging through data, and prioritizing follow-up based on blunt metrics like the largest dollar amount or the longest days overdue. A reactive day looks like: 

• Monitoring accounts receivable aging reports 
• Sending emails and making calls when accounts go overdue 
• Digging through spreadsheets, emails, and notes to track information like promised payments 
• Communicating back-and-forth with customers hoping to encourage payments without fracturing the relationship—whether that’s irritating them with repeated reminders or showing you don’t understand their payment habits 

It’s hard work with limited gains. Cash flow becomes less predictable and forecasting less precise, impacting business decisions and leading to higher borrowing costs.

More proactive collections lets teams get ahead of the payments that are due, without wasting time chasing customers with little risk of not paying on their own. It pairs real-time insights with predictive recommendations to improve visibility into your payment landscape and let you better target your efforts. 

Proactive collections changes the way teams approach collections in two critical ways. Here’s what those changes look like, straight from Jodi.

In a reactive collections environment, payment data isn’t available in real-time, meaning collections teams are always lagging behind on the accounts that need attention—often realizing a customer’s situation has changed only after the missed payment. A real-time view of account activity helps you understand the working capital you have available and forecast more accurately, to build more confidence in your cash flow.

To track cash flow, collectors manually monitor accounts receivable aging reports, track promises-to-pay, and maintain spreadsheets and notes documenting open invoices, expected payment dates, customer commitments, and follow-up history. And without a clear view of each customer’s payment history, forecasting falls back on portfolio-wide averages—a blunt tool when individual customer behavior varies so widely. 

This adds inefficiencies into the collections process. For example, if a customer promises-to-pay in 30 days, you may add that to your notes. But you also need to remember to go back to those notes to review your comments 30 days later, or you won’t realize they never met their promise. 

“No one is telling me that this is now overdue,” Jodi says. “I have to interpret that information based on past comments that I've left for myself.”

In a platform like Versapay, dashboards and dynamic insights cards replace the spreadsheet patchwork—connecting collections data in one place and surfacing it in real time. You can customize the view to show only the signals relevant to your accounts. For example, you can surface promise-to-pay forecasts, unapplied payments, and payments under dispute. Or track invoices due, amounts collected, current days sales outstanding, and average days delinquent. 

These insights fuel collections activities, letting you see the current state of your cash flow, forecast more accurately, and better understand which accounts need attention.

To understand what that looks like, consider the same promise-to-pay scenario. Now you can capture your customer’s promise-to-pay in your collections platform; it can send out an automated reminder when that promise gets close to the due date. When it does go overdue, you’ll be notified and can choose to get involved. 

“It's much more streamlined,” Jodi says.

Our data shows late B2B customer payments have increased over the past year for 69% of finance leaders—which means collections teams are spending more time chasing them down, in line with the 74% we cited earlier. Yet without an effective way to focus their efforts, they end up wasting their time following up with accounts that don’t represent a real risk of non-payment. To change that, they need a way to make sure they’re putting their attention in the right place.

In a manual collections environment, collectors are expected to chase late payments without any data-driven insights to guide them. You may prioritize based on total amount owed or longest days overdue as a result, or just let your gut feelings lead the way. But this puts collectors at a disadvantage. 

You may be wasting time following up on accounts that pay just a few days late every month, simply because they owe a large dollar amount. Or you could be missing accounts with a long history of late payment because they’re still only a few days overdue. And if payment behaviors change—for instance, a customer who used to pay on time suddenly starts paying a month or two late—you have no way of flagging the shift. 

“If you wanted to do it manually, you could source how many payments are coming in through autopay or a scheduled payment or a payment plan, and you can build that whole narrative yourself manually,” Jodi says. “But what you can't do is make assumptions on likelihood to pay based on the past payment behavior of a customer.”

Tools that apply AI to historical payment data can predict future customer behaviors, including likelihood to pay. This lets collectors know who is expected to pay early, on time, or late, and which customer behaviors are shifting in either direction. 

“If someone was a good payer and then there's a shift in payment behavior over the last 30 or 60 days, you can see that and pay more attention to customers that have made a positive or a negative net change,” Jodi adds.

Versapay’s tooling lets collectors segment accounts by likelihood to pay and prioritize their collections activities accordingly. This lets you hone your follow-up efforts without adding hours to your workload. You can send reminders to the customers most at risk of non-payment before they reach their due date, for instance, while deprioritizing those who usually pay on time.

Real-time and predictive insights rebuild your collections environment, turning it from reactive to proactive. Instead of chasing invoices only after they go overdue, collectors can see exactly who’s at risk of not paying, and work with customers to create an environment where they pay more promptly. 

This means collectors work smarter, not harder, using data to make more informed decisions for sharper actions today and clearer expectations tomorrow. The result is a more agile collections environment that puts collectors in the driver’s seat—ready for whatever comes next.