With the current economic environment and a surge in defaults and bankruptcies,
there has been greater emphasis on being able to ascertain the risks of
customers. The recent NACM teleconference, "Statistical Tools for Managing
Accounts," presented by Prof. Jack Williams, JD, CIRA, CDBV of Georgia State
University praised the value of using various types of statistical models to aid
credit executives in their decision-making process. The presentation also served
as a primer for the liquidity, debt and performance ratios, the tools used to
weigh the credit risk of customers.
"Use of statistics can be a valuable tool," said Williams. "Statistical
techniques are a way you can allow the data to tell you a story about your
customer. Statistics unlock the doors to all sorts of information and can be
used to compare a customer to the rest of that customer’s industry."
He added, "Any statistical analysis properly framed will answer fundamental
questions in a credit department’s operations."
Modeling and scoring techniques have been hailed as being objective in
assessing the risks of a customer, helping set opening lines of credit, as well
as establishing a baseline for that customer’s historical payment cycle. It’s a
lifecycle tool. There are a number of commercial options available and NACM
affiliates offer such services as well. The upcoming March issue of Business
Credit magazine also explores credit scoring and the use of statistical
"The interesting thing about statistics is that they allow you to look at a
lot of customers simultaneously," said Williams. "If you have a shop like the
ones I grew up in: you’re underfunded, undermanned and overworked. So, any type
of tool that makes you more efficient, particularly if it allows you to manage a
lot of customers, a lot of invoices, is going to be a better tool at the end of
Williams noted that people are often turned off by statistical modeling
because it is routinely seen as being math intensive. The reality is, though
there is math involved, it is not something only accomplished by rocket
"Statistics is less about numbers and more about patterns," said Williams.
"And that’s what we do intuitively as good credit managers. In fact, you’re
already doing statistical analysis." And by turning to an unemotional computing
technique, Williams said credit managers can remove subjectivity from the
process and embrace a tool that is reliable and consistent. Though he added,
"They do not replace personnel and they certainly do not replace discretion.
They augment credit discretion."
Williams’ detailed discussion of statistical modeling covered everything from
aging receivables, to analyzing raw data, to various types of averages, and even
to dreaded terms like standard deviation. But he continued to tout the
importance and efficiency of modeling as well as the ease of use. Even basic
office tools like Microsoft Excel can allow credit managers to start doing their
own statistical modeling. Most have access and are familiar with the software.
Many of the meetings and conferences held by NACM, such as the annual Credit
Congress, are often highlighted by Excel sessions and have proven to be very
popular among attendees.
"Excel gives you access to very amazing, powerful statistical techniques that
are embedded in the Data Analysis Toolpak," said Williams, going into detail
into how simple it was to load from the Tools menu. "It’s very, very easy to
use. Among other things, it’s going to give you summary statistics. It’s going
to give you the averages so you can get an indication of what your particular
payment cycle looks like with a particular customer or customers within a
particular product or service line that you provide. It’s also going to measure
Matthew Carr, NACM staff writer