Cash flow is the lifeblood of any business, but managing it can be challenging when there are multiple factors in play, especially when dealing with high volumes of transactions and various types of customers. One of the biggest contributors to cash flow disruption is delayed payments, but what if you could predict which of your customers are most likely to delay?
Buyer risk segmentation is the key to not only managing cash flow but also improving it. By leveraging technology to assess the risk each customer poses, finance teams can strategically prioritize their efforts, streamline collections, and optimize payment terms for each segment. The result? Faster payments, reduced outstanding receivables, and improved cash flow.
But how does it work, and why is it so effective?
Understanding Buyer Risk Segmentation
At its core, buyer risk segmentation involves categorizing customers based on factors like their payment history, credit score, and behavior patterns. This enables businesses to pinpoint which customers are more likely to pay late, default, or cause disputes. By identifying these customers early, finance teams can tailor their credit policies, implement more stringent follow-up processes, or even adjust pricing terms to mitigate risk.
Here’s how it breaks down:
- Segmentation by Payment Behavior
One of the most straightforward ways to segment customers is by analyzing their past payment behavior. Customers who consistently pay late should be flagged and handled with closer attention, while those who pay on time or early can be prioritized for favorable terms or discounts. - Credit Risk Assessment
Traditional credit scoring methods can only take you so far. Many finance teams rely on reports from credit agencies like NACM, Dun & Bradstreet, or tax reports to gauge the risk level of new and existing customers. However, using only these reports may leave gaps in truly understanding customer behavior and risk. - Combining Market Intelligence with Payment History
The true power of buyer risk segmentation comes from combining external market intelligence with internal payment behavior. By merging insights from credit agencies with data on how a customer has interacted with your company in the past, businesses can obtain a far more accurate picture of the risk each buyer represents.
For example, a customer might have a solid credit score but frequently engages in payment disputes. Another customer might score lower on credit reports but has a strong history of paying your invoices on time. By capturing both external and internal data, you can create a more nuanced and reliable credit risk profile.
Why Is Buyer Risk Segmentation Crucial for Accounts Receivables?
The challenge with accounts receivable is that it’s often reactive. Finance teams chase unpaid invoices after the due date, trying to manage cash flow retroactively. Buyer risk segmentation shifts this dynamic by enabling teams to predict potential issues before they arise. When businesses know who is likely to pay late, they can allocate resources more effectively, deploy automated workflows, and apply more pressure where it’s needed.
Here’s how buyer risk segmentation transforms AR performance:
- Prioritized Collections: Collections teams can focus on high-risk accounts first, ensuring timely follow-ups and escalation when needed. This prevents small issues from turning into big problems.
- Improved Credit Decisioning: By having a clearer picture of the risk associated with each customer, finance teams can make faster, more informed decisions about credit limits, payment terms, and other contract conditions.
- Personalized Payment Strategies: Not all customers are the same, so treating them as such can lead to missed opportunities. With segmentation, businesses can offer incentives to low-risk customers to pay faster while negotiating tougher terms for higher-risk customers.
The CRM Integration Challenge
While the benefits of buyer risk segmentation are clear, many businesses face challenges in executing this strategy due to difficulties in accessing customer data. For companies storing customer data in disconnected CRMs, integrating that information into AR workflows can slow down the entire credit risk assessment process, making it difficult to get a full view of customer behavior.
That’s where FinFloh comes in. Our platform seamlessly integrates with major CRMs, such as Salesforce, ensuring that customer data is readily available for real-time credit scoring. This not only speeds up the credit decision process but also eliminates the data silos that often hold finance teams back. With FinFloh, customer risk assessments become faster, more accurate, and more comprehensive.
Moving Beyond Basic Credit Scores
Traditional credit scoring methods have their limitations. While they offer valuable insights, they don’t provide the full picture, especially when it comes to a customer’s ongoing relationship with your business. This is where FinFloh’s unique credit scoring algorithm comes into play.
FinFloh uses a combination of market intelligence (such as tax reports, NACM, and D&B scores) and internal payment history to develop a more reliable and trustworthy measure of customer credit risk. By integrating these two data sources, the algorithm provides a more holistic view of risk.
FinFloh’s AI-driven algorithm doesn’t just assess risk once. It continuously updates customer credit profiles based on new data, making it a dynamic tool for both customer onboarding and ongoing account management. This system helps businesses:
- Speed Up Credit Decisions: By automating the credit scoring process, businesses can make faster decisions on credit limits, payment terms, and contract conditions.
- Improve Contract & Pricing Decisions: With more accurate risk assessments, finance teams can negotiate better terms or adjust pricing to protect against late payments or defaults.
- Enhance Customer Onboarding: FinFloh’s system helps ensure that high-risk customers are flagged early in the onboarding process, allowing businesses to tailor credit limits or require more secure payment methods from the start.
Start Improving Your Cash Flow Today
Buyer risk segmentation is an essential strategy for businesses looking to take control of their cash flow. By leveraging FinFloh’s advanced credit scoring algorithm, companies can better assess customer risk, optimize their accounts receivable processes, and make faster, smarter decisions that impact the bottom line.
Want to learn how FinFloh’s unique credit scoring algorithm can help your business? Discover how we use market intelligence combined with internal payment behavior to help businesses like yours segment customers with precision and reduce risk.