Avoiding Charge Backs on Credit Card
Credit card charge backs contribute to significant losses in business
for merchant processing not only in lost revenues but with increased
false positives. With online credit card payment fraud in the U.S. and
Canada steadily increasing as eCommerce has continued to grow 20% or
more each year, ThreatMETRIX is assisting merchants reduce chargeback
fraud and increase eCommerce revenues.
4 Insights in to Avoiding Charge Backs on Credit Cards
On the whole, the threat of online payment fraud has led merchants
to over-compensate, spending large sums on looking for, and blocking,
suspicious transactions. ThreatMETRIX introduces to online merchants
payment processors a new dimension in credit card fraud control used
by one of the world's largest online credit card processors. Online
fraud continues to be a significant and growing cost for merchants of
all sizes.
1. IP Geo-Location
The use of IP geo-location for risk mitigation of credit card fraud
essentially presents a large false-positive risk to merchants who rely
on it as a filtering criterion, and will at least place a larger burden
on manual credit card verification processes. In 2008, many people,
including many Americans, will travel to China for the Olympic
Games – using IP geo-location as a filter may cause a significant
increase in customer complaints.
2. Trends in use of Malware and proxies
Understanding malware and proxies to reduce charge backs on credit card
is very important. In June 2007, the FBI
reported that over one million Internet users might have been the victims
of compromised computers used to steal passwords and identities. A recent
investigation by ThreatMETRIX of 500 suspicious transactions with a
single site indicated that 80% of the transactions were via open proxies.
3. Identity – device fingerprinting
The ThreatMETRIX fingerprinting
and fingerprint verification processes can be performed without affecting
the user’s website experience. Because ThreatMETRIX stores the fingerprint
data, multiple merchants can benefit from the accrued device intelligence.
4. Anomaly detection
Even if a perpetrator acts through multiple proxies, their fingerprint
allows their activities to be tracked and anomalies detected. For example,
a perpetrator who uses multiple stolen credit card identities via different
proxies will be exposed as originating from the same device, thus exposing
the fraudulent activity.