Every company has found itself in this situation: a customer falls behind in payments 30 days, then 60 days, then 90 days. After reaching out multiple times without success, the collections team flags the company as a credit risk.

The trouble is that figuring out that an account is a credit risk during the collections process is too late. It needs to happen much sooner in the process.

Automated accounts receivables platforms can assist in this process, but they aren’t all equally effective. For example, some AR automation providers advertise that they can score a customer’s credit worthiness for you. But if you’re accessing that information in your collections tool, you’ve already missed a critical opportunity to identify and manage risk.

Leading AR teams take advantage of credit data as early as possible so that you can reduce risk later on. Ideally, it should happen before the sales closes and the invoice has been approved. If you know in advance that a potential customer poses a credit risk, you can adjust payment terms, plan effective collections approaches, or you might even decide not to approve the sale.

Performing a thorough credit analysis on potential customers is crucial. Credit and Collections leaders from Veeva, Slack, and Snowflake that we’ve worked with on a regular basis recommend using an established and reputable firm like Dun & Bradstreet to help you evaluate risk. You have the option of checking an individual customer’s credit or purchasing a subscription so that you can monitor as many of your customers as you want.

“We do utilize Dun & Bradstreet,” says Steven Odell, Senior Manager for Credit, Collections, and Accounts Receivable at Slack. Odell was part of a recent webinar on collections sponsored by Tesorio. “We are now looking earlier, and identifying with more granularity in the analysis, the risk in our portfolios.”

At Tesorio, our best practice recommendation would be to enter the credit information that you have from Dun & Bradstreet or another credit firm into a custom field in an ERP like NetSuite, Workday, or Sage Intacct. As a part of your sales order approval process and invoicing approval process, your billing team can check the credit score to see if the customer is credit worthy enough to sell them the product. If they're not, you may want to implement a procedure where your sales team would have to gather more information about the customer’s finances.

“We use a highly rated credit company and dial them into our sales opportunity software,” says James Wallace, Credit and Collections Manager at Snowflake. “Our sales ops team pushes a button, pulls a credit score, and gives them a pass or fail.”All of this will happen well before the AR team gets involved.

If you have your own system for determining the creditworthiness of a customer, you can rate them using Tesorio’s tagging system. That way, you can sort, report, and create campaigns based on the ratings. For example, high-risk customers might get more touches and low-risk customers might get fewer touches (which can all be automated inside Tesorio’s campaign manager.

One more thing: Don’t forget to take a close look at their payment history with your own company. Tesorio uses machine learning to analyze customers’ payment history and predict whether they’re likely to require collections activity. That can help you identify at-risk customers and reach out to them before there’s a problem.

Tesorio understands the difficulties companies face as they struggle to smooth out their collections process. That’s why we work with the world’s best accounts receivable teams to provide software that helps them identify problems with customers as soon as possible. Built by collectors, for collectors, we invite you to check out our weekly demo day to learn more.