Date: Wed, 8 Nov 2006 10:27:30 -0500
Reply-To: "Wainwright, Andrea" <andrea.wainwright@CAPITALONE.COM>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: "Wainwright, Andrea" <andrea.wainwright@CAPITALONE.COM>
Subject: Re: Optimization Challenge
In-Reply-To: A<1162937050.578000.32910@m7g2000cwm.googlegroups.com>
Content-Type: text/plain; charset="us-ascii"
Multiply the value of the transaction by the probability of it being
fraud, sort by that value from highest to lowest, and take the top 3K
records. Change 3K to be whatever the real limit is.
-----Original Message-----
From: SAS(r) Discussion [mailto:SAS-L@LISTSERV.UGA.EDU] On Behalf Of Rob
Sent: Tuesday, November 07, 2006 5:04 PM
To: SAS-L@LISTSERV.UGA.EDU
Subject: Re: Optimization Challenge
Thanks for the input so far. Here is an example in case it helps
clarify what I am after: Pretend today our stores had one million
transactions, some of which are fraudulent. Each transaction has its
own dollar amount. Each transaction is assigned a risk score indicating
its likelihood of being fraudulent. The fraud department can review a
maximum of 3,000 transactions per day. The goal now is to identify
which 3,000 transactions being reviewed will result in the greatest
dollar amount of fraud prevention.
As mentioned earlier, there are many more low risk transactions than
high-risk transactions. Also, there are many more low-dollar purchases
than high dollar purchases.
Which items do you review? This oversimplifies the issue, but I would
be interested in a solution that can then be generalized.
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