Fraud originating with EBT cards differs drastically in
appearance than fraud originating from commercial cards. The reason for this
dramatic difference is simple enough, EBT fraud origin requires collusion
between the cardholder and the retailer (vendor in the SNAP world, but for the
purposes of this blog, retailer). This allows fraud investigators to use EBT
data to present a prima facie case to a judge that the intent and the action
show a criminal act. It’s a pity that investigators do not use this most
remarkable aspect of needs based payment data to track extremely vicious and
powerful criminals.
I suspect the reason we do not use the data has nothing to
do with malicious or planned practices, and everything to do with the
difficulties of collection of data to present a prima facie case. Different
vendors (sellers of goods and services, not retailers) possess the data.
However all of the data regardless of the holder actually belongs to the
administrators of the SNAP program and therefore shipped routinely to FNS.
I have developed a theory of fraud detection for needs based
payment environment that I call behavior detection and evasion detection (BD/ED
or conveniently enough Bad Ed). Subsequently I showed (at least to myself) that
Bad Ed works well in other types of payment environments. Bad Ed provides prima facie evidence for SNAP
investigators because the data within the X9.58 message coupled with data from
points of presence (POP) shows commission of a crime. For example, if the
transaction originates from a place other than where the retailer conducts
business then it is a crime and the data from a single transaction will show
that.
The other aspect of Bad Ed, the evasion detection filter,
requires that investigators construct it before deploying the behavior
detection filter. Evasion detection works because criminals run after
exposure of an attack method from behavior detection filter; they use another method,
which exposes the new attack and gives foundation for the construction of
a new behavior detection filter.
No comments:
Post a Comment