As part of a larger datamining study (described here and here) we transformed about 1 million Credit Bureau records of households with marginal credit scores (650 to 680) by filtering out many of the 200+ items per record and by expanding each household's revolving credit balance into 12 categories, based on the account's age and credit limit. A data mining program then divided these households into 36 groups using these new categories.

Clicking this Demo link brings up a separate display* of these groups in a rectangular grid, as shown below;

Colored by Score...

...and by Subsequent Bankruptcies

On the left, the color of each rectangle reflects the average credit rating of each group, pink being lower and blue being higher. The top 3 credit categories of each group are also shown. Not much of a pattern is visible when the rectangles are colored by their credit score.

But click the "Color By" menu in the demo and select "Bankruptcies" and you'll get the coloration shown on the right above. Now the color of each rectangle indicates the fraction of households in that group that went bankrupt in the following year, and a pattern does appear, showing that the datamining program clustered the higher bankruptcy risks into the lower right corner of the grid. In group 30, for example, the bankruptcy rate is 3.8%, which is 13 times higher than average. Note that many of the other groups in this marginal-credit pool in fact have lower-than-average bankruptcy rates.

Now click the "BB Signatures" menu to see the pattern of the 12 categories we described above, and note the characteristic "bankruptcy signature" visible for group 30. Here's how an analyst interprets group 30's signature:

The squares marked "1" indicate they once were able to get credit lines over $7500, but not in the last two years. The squares marked "2" show they have a "sweet spot" in credit lines between $2000 and $7500 ... easy to get and they quickly add up tp a lot of money. The squares marked "3" show they have been unable to get new credit in the last 6 months as their "risk" score elevates.

Customers and lenders both benefit when a finer filter like this is used to separate the credit-worthy from those who pose a higher risk.

*If the Demo button fails, try disabling "Ad Blocking" in your firewall, i.e. Norton Internet Security; also, you can see what you missed here.