Cloaking Devices

On March 27th, 2012, D&B offered a one-hour webinar called “Bankruptcy: Why the Surprise? Avoid the Cloaking Effect of Timely Payments Webcast”. Webinars are ubiquitous these days, and there is one measure for how good the webinar is: whether or not you alt-tab off the page to do something else! That was not the case during this session!

Before getting into the meat of the presentation, it is important to note just how well this presentation was done. The topic was interesting, there were recent and interesting statistics used to support their arguments, the presenters did not just read us the slides, and they did not try to teach basic credit skills to the viewers.

What was really jazzed the presentation was the fact they asked the question we all have asked: why does D&B’s information sometimes not predict a major problem with a customer?

The answer they propose is that it comes down to “cloaking”, which they define as behaviour by both the customer and the creditor that masks the true risk in a customer.

  • Customer Cloaking: they their bills on time to avoid credit problems and to take advantage of early payment discounts.
  • Creditor Cloaking: business processes look mostly to payment history to determine risky new customers or produce the exception-based reports that trigger reviews for existing customers.

For the most part the webinar focused on the internal processes of creditors which can mask a problem customer. Whether you are automated or not, the webinar presenters urged credit managers to critically examine their processes to ensure that payment history is not weighted so heavily in the scoring process that other factors disappear from view.

Specifically, for automated scoring processes they suggest that the weights not be reallocated when data elements for the scorecard are missing. That can happen with a high risk customer, since when the risks increase significantly D&B removes all the scores from the customer’s report. So an automated credit scoring process that reallocated weights for missing data would factor out the most important information!

They also suggest paying closer attention to the alerts they issue (they say that they have clients that have more than a thousand unread alerts), and check out the special events section of the report. In addition, they suggest that you use their filtering tools to look for customers with good payment history, but who have poor FSS and Credit percentile scores (their definition of cloaked customers).

They caution that most customers with good payment histories are usually, well, good customers and there is nothing major to worry about. The techniques that they suggest speak to your internal processes, and are just another way to generate exception reports to help you identify customers who may surprise you with a bankruptcy or receivership where normal exception reporting would not have flagged them.

Check out D&B’s white paper on the subject.

This seminar was worth the time, and it presented something new, interesting and useful for credit managers.


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