An October 2018 Blueprints article entitled, “Extending Credit? Know the Score,” discussed the effectiveness of Blue Book scores.
The article cites companies with a score of 800 or greater have less than 1% probability of going out of business owing money within a 12-month period.
Further, research shows companies with a score in the 600 to 699 range were about 3 times as likely to go out of business and 12 times more likely to do so owing money, than those with scores in the 800s.
Maurice Cameron, managing member of The Flavor Tree Fruit Company, LLC BB #:260549 in Hanford, CA, agrees, offering his perspective: “Our experience with scores is that they accurately predict the likelihood of slow or prompt payment.”
Another fact to keep in mind is that score migration is relatively stationary over time.
In other words, a company scored in a particular risk band at present is most likely to be scored in the same band in the near term, while the tendency to be scored in the same risk band over a lengthier period does moderately decline, but migration is generally limited to neighboring risk bands.
So what does all this mean? Although company scores can improve or decline with pay performance, scores and risk tend to act a little like Isaac Newton’s first law of motion: what is at rest tends to stay at rest, and what is in motion tends to stay in motion.
Slow pay adversely affects a score more than any other type of data variable. However, even the industry’s best payers have some slow pay data as a result of delayed seller invoicing, missed paperwork, problem files, or even consignment deals.
Such data, in small quantities, can and will impact a company’s score—but as long as the data pool is sufficient, a score should be of relatively low risk.
The important thing to remember is that scoring models require data, and preferably, a lot of it.
If a company has limited partners, its score has a higher probability of being more volatile and lower than the score of a company with a higher number of trading partners. This is because a few slow, outlier data points have less impact on the overall score.
A newer company that may have a good and higher score than a company with greater tenure also has a higher probability of more score volatility, as it lacks historical data.
New companies often start out with a higher score, as they may initially bend over backwards for vendors. But as they settle in and become more comfortable with supplier relationships, the tendency is often for these companies to keep payment within terms, but slow down, resulting in a score decline.
We receive many inquiries on this subject. Although risk is ranked according to trading performance within our scored population, scores are not necessarily a suggestion that one company is better than another.
When evaluating a new company score, it’s important to understand data depth because data-thin scores do exist and are inherently more at risk of incurring an adverse score change.
This an excerpt from the Credit and Finance department in the May/June 2022 issue of Produce Blueprints Magazine. Click here to read the whole issue.