Cancel OK

Extending Credit? Know the Score

Understanding Blue Book Services’ risk management tool

General News

We live in an era of ‘big data’ made possible by the digital age. And, as a society that continues to advance and evolve with this age, we’ve learned how to harness, interpret, and utilize large data sets to our advantage and get a better look into the future. Data combined with high-powered analytics is an effective tool to assess risk and predict future behavior and events.

Credit scores, the output of data variables and designed to predict creditworthiness, have been an invaluable risk management tool in domestic and international commerce for decades. Credit scores give users an inside look at current and future business partners, providing the basis for confident, profitable, decision making.

While credit bureaus have been around since the 1860s, it was Bill Fair, an engineer, and Earl Isaac, a mathematician, who first created an automated credit scoring system. Fair Isaac & Company (FICO) was founded in 1956 on the principle that “data, used intelligently, can improve business decisions.”

For anyone trying to get a mortgage, finance a car, apply for a credit card, or purchase insurance, the interest rate, credit limit, cost, and approval are often tied to the person’s FICO score. Introduced in 1989, the FICO score is a predictor of future risk; that is, the statistical probability that a given individual will be delinquent or default on debt owed over a specified period of time.

Algorithms calculate probability based on data compiled in credit reports, which then offer snapshots of current and past credit behavior. Providing such a snapshot in the lumber industry is what Blue Book Services, Inc. and its credit scoring models are all about.

 

Commercial credit scores

Just as a FICO score measures personal creditworthiness, a commercial credit score is designed to predict the likelihood a company will become delinquent or default over time. Having this type of tool is particularly important for sellers who must make credit decisions quickly in a sector with numerous uncontrollable variables.

Many in the industry rely on Blue Book Scores to help mitigate this risk. “Scores have demonstrated their value by consistently predicting outcomes and events and have proven to be a powerful risk tool for our users,” notes Bill Zentner, Blue Book’s vice president of ratings.

 

What do scores mean?

Blue Book scores range between 500 and 1,000. Though it may seem obvious, Zentner reiterates, “When working with scores, it’s necessary to understand what’s low risk and alternately, what’s high risk.” The lower the score, the more likely a company will be delinquent or default on payment; the higher the score, the less likely such events will occur.

 

How scores are used

Zentner advises companies to make sure customer scores meet established credit policy requirements; simple but solid advice.

“Though the score itself is what’s most predictive,” Zentner adds, “being aware of a company’s score pattern and changes is central to staying a step ahead and appropriately managing risk.”

Chuck Curl, director of sales operations for a Wisconsin-based shipper, agrees. He keeps an eye on customer scores to stay in front of any potential risk. “If the company drops below our tolerance, we discontinue offering credit. If a company has a score over 800 and drops 35 or 40 points in a one-month period, we research to see why there’s been such a drop.”

Initially, Curl says he was skeptical that Blue Book Scores would actually be predictive. But time and again he has found them to accurately reflect a company’s ability to pay on time. In one instance, a new customer was brought in that had a reasonable credit score, though limited trade information. “We elected to start out slow with the caveat that we would be monitoring credit reports,” Curl relates. “We experienced slow payment and found the score had declined below our policies. We stopped doing business with that customer.”

Scores tend to decline more quickly than they rise. According to Shane Pederson, senior data scientist for Open Data Group in Chicago, IL, that’s because “a decline is a significant event for a company when its on-time payment has been good. It stands out.” A business can always improve its score by paying bills on time over several months and maintaining good relationships.

“Though rare, there will be occurrences when a well-scored company will not meet the expectations of an assigned score,” Zentner says. “Whenever you’re dealing with probabilities, misses will happen. Scoring misses are generally the result of insufficient data, or more often an adverse cash flow event such as a significant customer loss, a leadership change, a shift in operational focus, or possibly even an act of fraud.” Further, he notes, “Scores are an excellent standalone tool, but it’s always best to know as much as possible about a customer or prospect to make the most informed decision.”

Any mill or wholesaler seeking an impartial view of the current and potential likelihood a customer will pay on time can take comfort in the historic accuracy of Blue Book Scores. “The predictive accuracy has been quite remarkable,” Zentner confirms. “Our studies have shown that scores speak well to a company’s risk—including what a company’s risk is now and if there’s a high likelihood it will be similar or the same 12 months down the road.”

Irene Lombardo is an award-winning writer/editor with more than 30 years of experience covering a variety of subjects, including the food and financial services industries.