Posts Tagged ‘deposit fraud’

Finding Fraud Detection Rules Through Evolution!

Monday, January 18th, 2010

Through the principle of  survival of the fittest, the natural evolution can find the best genes for the environment. A genetic algorithm (GA) simulates the natural evolution process to search the best solutions or fraud detection rules in our case. With our cutting edge GA based proprietary technology, a large number of initial fraud detection rules evolve to detect more fraud at lower false positive. After many generations of evolutions, the best fraud detection rules are the ones that survive.

ABA talk rescheduled (9/23)

Friday, September 18th, 2009

More talks: Q&A with Forrester Research on Oracle ODM (9/23) and a Babson class presentation on DM (9/24).

Optimize Fraud Detection System As a Whole

Sunday, August 30th, 2009

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.