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Brian McClair
I
November 24, 2025
11 minutes to read
The email from the CFO lands with a simple, unassuming subject line: "Risk Exposure - Retail Sector."
Inside, the request is anything but simple. In response to a competitor’s recent bankruptcy filing, leadership wants a consolidated risk report on your top 50 retail distributors by end of day. They want to know current credit utilization, payment trends, and, most critically, the date of the last credit review.
You pull the report from the ERP. The numbers populate, but the dates tell a story you were hoping to avoid.
Distributor A: Last Reviewed 14 months ago.
Distributor B: Last Reviewed 22 months ago.
Distributor C: Last Reviewed at Onboarding (3 years ago).
On paper, these customers are "good." They pay within terms, mostly. They don't trigger hold blocks often. But as you stare at the "Last Reviewed" column, the reality sets in: You aren't actually managing risk on these accounts. You are relying on historical data that is effectively obsolete.
You are managing a ghost portfolio. The credit scores, bank references, and financials you have on file represent a company that existed three years ago, not the one placing a $50,000 order today.
This scenario plays out in credit departments daily. The intense focus on speed to onboarding—getting the customer through the door to satisfy Sales—often leaves the existing portfolio exposed to slow, silent decay. When the bomb finally goes off, it’s rarely a new customer who defaults. It’s the "legacy" account everyone stopped watching.
Most credit managers are painfully aware of this gap. You know that a credit limit set in 2021 has no bearing on a customer's liquidity in 2025. Yet, the sheer volume of active customers makes manual periodic reviews mathematically impossible for most teams.
The frustration is that modern business is dynamic, but traditional credit monitoring is static. You vet them once, give them a stamp of approval, and then only look again if they stop paying. By then, it is usually too late.
If every Credit Manager knows that ongoing monitoring is essential, why is "static" credit management still the industry norm? The root causes usually stem from structural limitations rather than a lack of desire.
Most credit departments are resourced to handle the inflow of work, not the maintenance of the asset. KPIs are often tied to "Application Turnaround Time" or "Time to Decision." Because the pressure from Sales is focused on opening new accounts, that is where the manpower goes. Periodic reviews are the first task to be deprioritized when the team gets busy.
Your ERP (whether it’s SAP, Oracle, or a legacy system) is excellent at recording transactions. It is terrible at monitoring external risk. An ERP does not know if your customer just got hit with a federal tax lien. It does not know if their D&B score dropped 20 points yesterday. Unless someone manually updates that field, the ERP assumes the customer is as healthy as they were on Day 1.
Traditional policy dictates that we review accounts annually. However, risk does not operate on a fiscal calendar. A customer can go from healthy to insolvent in the six months between your scheduled reviews. Relying on a calendar-based trigger guarantees that you will be reacting to old news for a significant portion of your portfolio.
Even when teams subscribe to credit bureaus, the data often lives in a separate portal. The Credit Manager gets an email alert: "Rating Change for XYZ Corp." They then have to log into the bureau, read the report, log into the ERP, check the exposure, and make a decision. This manual bridge is too heavy to sustain for thousands of customers, so the alerts often go unread or un-actioned.
To move beyond the ticking time bomb of static checks, credit leaders must shift their philosophy from Periodic Review to Event-Driven Monitoring. This does not require hiring more analysts; it requires changing the triggers that initiate a review.
Here is a framework for modernizing portfolio risk management:
Instead of manually pulling reports every year, your portfolio should be continuously screened against external databases. You need a system that pushes data to you, rather than you pulling it.
The Trigger: A drop in credit score, a new tax lien, a bankruptcy filing, or a change in ownership structure.
The Action: Automatically flags the account for review only when a negative signal is received. If the customer is stable, no human time is wasted reviewing them.
Your own AR ledger often holds the earliest warning signs of trouble, long before the credit bureaus catch wind of it.
The Trigger: A customer who usually pays in 30 days starts slipping to 45. A customer who pays by ACH suddenly switches to paper checks. Partial payments begin appearing.
The Action: An automatic "credit limit freeze" or a "review required" task. This is the difference between reactive collections and proactive risk mitigation.
Combine the two signals.
Low Risk: No external alerts + solid internal payment history = Auto-Renew Credit Limit (No human touch required).
High Risk: External alert received OR internal payment degradation = Immediate Manual Review
This framework allows a small credit team to manage a massive portfolio by only focusing their attention on the exceptions—the 10% of customers who actually pose a risk right now.
Transitioning from static checks to continuous monitoring changes the role of the Credit Manager from a gatekeeper to a risk strategist. The impact is measurable across the organization:
The most obvious benefit is avoiding the "million-dollar surprise." By catching a lien or a score drop six months before a default, you can reduce exposure, demand guarantees, or switch terms to cash-in-advance while the customer still has some liquidity.
Conversely, static checks also hurt revenue. A customer might have grown significantly since they were onboarded three years ago. Their $50k credit limit is now choking their ability to buy from you, forcing them to split orders with competitors. Dynamic monitoring flags positive changes too, prompting you to proactively increase limits for growing customers.
Nothing destroys trust with Sales faster than putting a long-term customer on hold unexpectedly because a manual review suddenly unearthed bad news. Continuous monitoring allows you to have difficult conversations early: "Hey, we saw a dip in their rating, let's watch their next two orders closely." This is a partnership discussion, not a frantic blocked-order fire drill.
The directive is clear for modern credit functions. If your current process relies on your memory, a spreadsheet, or a calendar reminder to catch risk in a volatile economy, you are exposed. The goal is to build a defensive perimeter around your portfolio that works while you sleep, ensuring that the customer you trusted on Day 1 is still worthy of that trust on Day 1,000.
To start shifting away from static checks, audit your current state with these questions:
1. The Data Audit: What percentage of your active customer base has not had a credit file update in the last 12 months? (If it’s over 40%, you are in the danger zone).
2. The Trigger Test: If your second-largest customer was sued today, how would you find out? Would a system tell you, or would you find out when the check bounces?
3. The Integration Check: Does your credit data live in the same screen where you release orders? If you have to toggle tabs to see risk data, you have a workflow gap.
Moving to dynamic monitoring isn't just about safety; it's about scalability. It ensures your credit department can grow with the business without needing to hire an army of analysts to manually re-underwrite the past. If your current setup relies on memory, manual checks, or annual calendar reminders, you're managing risk with blind spots.
If you'd like to see how automated monitoring and behavioral triggers could work for your company, reach out. We're here to help.
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