How AI-Powered Credit Management Software Stops Revenue Leaks

In finance, credit managers live with constant tension: the need to make faster credit decisions to keep sales coming in, and the pressure to protect the business from credit risk. When approval and review processes remain manual, this tension manifests as revenue leaks — slow drips of lost profit and mounting financial risk that hide in the depths of daily operations.

These leaks aren’t always obvious in credit management. They often disguise themselves as “just how things work.” Here are three signs that your credit process has sprung a leak, and how AI-powered credit management software plugs each one.

Sign #1: Delayed Credit Allocations are Reducing the Lifetime Value of Your Customers

What it looks like: You frequently get urgent emails or calls from sales reps asking for status updates on new credit applications. They see your department as a bottleneck that delays deals and frustrates eager new customers.

Behind the scenes, their frustration may be justified. When an application from a promising customer lands on your desk, the workflow grinds to a halt as you manually request trade references, email the sales team for context, and wait for third-party credit reports to come in.

Why it’s leaking revenue: Manual credit approval for new customers can extend the average decision time and delay revenue generation. More importantly, a slow and cumbersome onboarding process creates a poor first impression, potentially souring the relationship before it even begins and reducing that customer’s lifetime value.

How AI-driven automation plugs this leak: Billtrust’s automated credit application processing allows you to set your own approval criteria once, then automatically process straightforward applications in minutes instead of days. The system pulls credit data, evaluates risk against your parameters, and handles low-risk applications without manual intervention. This frees your team to focus only on complex cases that require expert judgment.

Sign #2: Static Credit Evaluations are Preventing Future Sales

What it looks like: For many businesses, a credit review is a one-time event that happens during onboarding. The credit limit is set, and then it’s rarely looked at again unless a payment issue arises. Your team doesn’t have a systematic workflow for re-evaluating credit lines based on positive payment history or changing risk signals. This turns your credit policy management into a purely reactive function, managing based on a static, outdated snapshot of the customer.

Why it’s leaking revenue: This “set it and forget it” approach leaks revenue in two ways. First, you miss opportunities to increase credit limits for your best, most reliable customers, preventing them from buying more. Second, you fail to identify growing risks in accounts whose payment behavior has worsened over time, exposing you to potential bad debt.

How AI-driven automation plugs this leak: Instead of relying on static, one-time credit evaluations, our AI-powered system continuously monitors customer payment behavior to prevent risk. Billtrust Credit Review provides a complete, 360-degree view of your customer’s creditworthiness, including their credit line utilization. Building on that foundation, Billtrust Agentic Credit Lines dynamically analyzes this data to recommend intelligent adjustments to their credit limits.

This allows you to optimize your credit allocation across all accounts. You can confidently reward your best customers with increased credit limits while keeping a closer watch on riskier accounts with a level of visibility only AI can provide. The result is a smarter, faster way to manage credit risk, leading to better decisions and stronger financial control.

“Agentic AI is the new generation of intelligent automation, acting as a virtual assistant with a certain degree of autonomy to perform specific operational tasks. This will take credit management to a whole new level.”

Sjoerd Janssen, VP and General Manager Europe, Billtrust

Sign #3: Inaccurate Assessments Lead to Misallocations

What it looks like: Your team lacks a centralized, data-rich view for making decisions. As a result, assessments of a customer’s creditworthiness are inconsistent. A new customer might be given too much credit, increasing risk, while a long-term, reliable customer is denied a credit limit increase that would have unlocked a larger sale.

Why it’s leaking revenue: Every inaccurate assessment is a revenue leak. Setting a credit limit too high leads to a greater risk of write-offs and costly collections efforts. Setting it too low directly caps revenue and can frustrate loyal customers, potentially driving them to competitors with more flexible terms.

“An incorrect assessment can lead to customers receiving a limit that is either too low or too high. In the first case, you can miss out on sales opportunities; in the second, you face an increased risk of late payments or worse.”

Sjoerd Janssen, VP and General Manager Europe, Billtrust

How AI-driven automation plugs this leak: Billtrust’s platform centralizes all relevant data, such as payment history, credit bureau information, risk signals, and current balances, in a unified view. With AI-powered cash flow predictions, you gain visibility into not just current risk, but future payment patterns. This allows your team to make more accurate, data-informed credit decisions rather than relying on outdated snapshots or gut instinct.

The AI analyzes payment behaviors across your entire portfolio, identifying patterns that signal both opportunity and risk. When combined with automated workflows, this means consistent, accurate credit assessments that optimize revenue while managing risk effectively.

A Day in the Life with an AI-Powered Credit Assistant

Imagine how a credit manager’s day could be transformed with intelligent credit and collections tools from Billtrust, designed for their workflow:

• Morning: You start your day with a clear, prioritized task list in your Billtrust smart dashboard. You see all credit applications in one place. Several applications that met your pre-set criteria were auto-approved overnight, so your team can focus on the exceptions that require human expertise. Your AI-powered cash flow predictions show you which accounts might face payment challenges in the coming weeks, allowing you to proactively adjust credit decisions.

• Mid-Day: Billtrust’s agentic email capabilities have automatically organized dispute-related emails and flagged urgent cases requiring your attention. Instead of sorting through hundreds of messages, you focus on the handful that need expert judgment.

• Afternoon: An automated alert flags a key account for credit review—the customer’s payment behavior has been excellent. Based on an AI analysis of their payment patterns, virtual credit agents inside the Billtrust Collections solution recommend a credit limit increase. All the data you need is displayed on a single screen. You approve the increase in minutes, empowering sales to pursue a larger deal.

• End-of-Day: With daily approvals and dispute triage handled efficiently through automation, you use the Billtrust Credit Analytics dashboard to get a holistic view of your team’s performance. It gives insight into how balanced your credit policy is and how much revenue should be generated from approved credit applications. You’re also tracking key metrics like average days-to-decision for your credit approvals and the Collections Effectiveness Index (CEI), which measures how much money was actually recovered during a specific period—making month-over-month comparisons much easier.
  
  When you spot a bottleneck in the trade reference request stage, you can make targeted process improvements that move the needle on these critical KPIs.
  
  Plus, you can leverage cross-product data, including cash application and payment transactions, to uncover bad debt risk and new opportunities to offset it. (For a deeper dive into which credit and collections metrics matter most, check out our guide to the best AR KPIs.)

Addressing the Real Hurdle: Getting Your Team on Board

Here’s the truth about AI implementation that most vendors won’t tell you: technology isn’t the hardest part. People are.

Your credit team has built their expertise through years of experience. They’ve developed instincts about which customers to trust, and which applications need extra scrutiny. When you introduce AI-powered automation, you’re asking them to trust a system that might contradict those instincts—or worse, make them feel expendable.

This resistance is natural. Industry research consistently shows that employee resistance and change management rank among the top barriers to successful AI adoption in finance operations, sometimes even outweighing technical implementation challenges.

What You Can Do to Gain Buy-in

Reframe AI as augmentation, not replacement. Your credit managers aren’t being automated away—they’re being freed from data entry and status update emails. Automation handles straightforward decisions that don’t need human judgment, so your experts can focus on the complex cases where their experience actually matters.

Start with training, not transformation. Before rolling out auto-decisioning, involve your team in setting the approval criteria. Let them see how the system follows their rules, just faster and more consistently. When they understand that they are teaching the system their expertise (not being replaced by it), adoption becomes collaboration.

Measure what matters to them. Don’t just track business metrics like DSO reduction. Show your team how AI-powered automation reduces their personal pain points: fewer after-hours escalations, less time chasing down information, more time for the analytical work they were hired to do. At 84 Lumber, AR clerks used to spend full days sorting and applying check payments before transitioning to collections work. With Billtrust’s streamlined processes, those tasks take about an hour—freeing up time for higher-value work. Today, a core team of 7-8 collectors handles the workload that would have required 10 people under the old system. When credit managers see their workday improving, not just the company’s bottom line, they become your AI advocates.

Address the fear directly. When Billtrust customer 84 Lumber began leveraging AI automation, their credit professionals initially worried about becoming “too automated.” Instead, they discovered the technology gave them more data to make more informed decisions and ultimately became the strongest proponents.

“Technology, processes, and people can reinforce one another. If you deploy AI tools with the right mindset and AI training programs to demonstrate the value, such as automating repetitive and administrative tasks, it promotes adoption. AI must be positioned as an opportunity to better utilize employee talents, benefitting personal career growth, customer relationships, and business results.”

Sjoerd Janssen, VP and General Manager Europe, Billtrust

The goal isn’t to replace your credit team’s judgment. It is to give them back the time and bandwidth to actually use it.

By modernizing your credit approval and review process with AI-powered automation, you’re not just plugging revenue leaks, you’re investing in your team’s potential to manage risk more effectively and become a true engine for growth.