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Old Jan 7, 12, 10:08 pm
  #12  
redtop43
 
Join Date: May 2008
Location: PHL (kinda, no airport is really close)
Programs: AA Exp (2020 is first and last year). Enterprise Platinum woo-hoo!
Posts: 3,267
Originally Posted by weave View Post
I've always figured if I was employed to write code to track who to target for a FR due to possible higher risk, it'd be pretty easy (beyond the known measures, like credit score and declining available credit).

Declining account activity isn't always a good measure because one could be charging on a different card due to dissatisfaction of the product, and don't want to piss them right out the door, but other activity could indicate a problem. Like:
  • Track tipping amounts in restaurants. If a card holder normally tips generously and then starts getting stingy with tips, that could be a sign.
  • Where one charges. If months ago charges to Nordstroms were common but now Wal-Mart shows up weekly.....
  • Payment activity. An obvious one. If payment gets later and later in billing cycle, possible red flag.
  • Dollar coin purchases (ok, old news now, but had to slip that one in!)

There's a Wal-Mart next door to my work and I occasionally pop in there to get a few things because it's convenient, but I always pay with cash
There is a regional department store chain based in Reading, PA called Boscov's. Many years ago I saw a credit scoring algorithm that added points for having accounts with many providers, but deducted points if you had a Boscov's account.

More to the point, algorithms to flag potentially defaulting accounts are by their nature agnostic. They don't try to "guess" what qualities will predict default (or fraud, or anything else, good or bad, you are trying to predict). They simply track the past data that, singly or in combination, are most predictive of what they are trying to predict. If people who make purchases of exactly $13.22 had statistically higher defaults than those who don't, then you would be more likely to get an FR if you bought something for $13.22. It's not about logic, it's about the data. These systems cost millions to implement and maintain. (I work for a company that develops them.)
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