When we set up fraud prevention rules, we should be aware of the complexity due to the interrelationships between variables. I use an example to illustrate the point. We can create two rules based on two variables:
Rule 1. Number of checks deposited in last 3 days
Rule 2. Number of checks deposited in last 5 days
Looking individually, both Rule 1 and Rule 2 are good. However, Rule2 does NOT detect many ADDITIONAL frauds because it overlaps with Rule 1. There is not much incremental value by including BOTH Rule1 and Rule 2 as part of the system.
So it is more effective to optimize rules holistically, i.e. , considering the multiple rules simultaneously, not individually. Each variable should provide new information and the overlap between variables should be small. After all, our goal is to optimize the system performance not the individual rule performance.