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State
goes after food stamp violators
By Cornelius Frolik
Photo
by Lisa Powell
The
state of Ohio on Tuesday announced it has partnered with the
U.S. Department of Agriculture to use technology to crack down on fraud
in the federal
food stamp program, which costs U.S. taxpayers hundreds of millions of
dollars
each year.
Under
a new agreement, Ohio will try to identify fraud among
recipients of food stamp benefits by sharing information about their
transactions with USDA.
USDA
said it will provide training and data-mining assistance to
identify suspicious patterns of benefit redemption that could indicate
illegal
activities, such as using benefits far from home or at stores in
high-risk
areas.
“These
data mining partnerships … will give the states and the
federal government both the opportunity to share these electronic data
systems,
and we think we can help each other in that regard,” said Kevin
Concannon, USDA
undersecretary for food, nutrition and consumer services. “It’s one
thing to
take the stores or the store owners out of the program, but there have
to be
consequences too for the individual households that may have trafficked
benefits in those stores.”
USDA
is in charge of investigating food stamp fraud perpetrated by
retailers and vendors. The state and county agencies are in charge of
investigating fraud among residents who receive food benefits.
A
common form of fraud involves people illegally selling or
trading their benefit cards to friends, store clerks, drug dealers or
others
for cash, drugs or other non-food items. Buyers usually pay 50 cents
for every
$1 in benefits.
Fraudulent
activities are a drain on taxpayers. USDA estimates
that about 1 percent of food stamp benefits are misappropriated because
of
trafficking. The program distributed $74.6 billion in fiscal year 2012,
meaning
about $746 million was lost to fraud.
USDA
said it discovers most food stamp trafficking activities
using its electronic data-mining monitoring system. State officials
hope they
will be able to root out fraud among recipients by analyzing redemption
behaviors…
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