In California, an identity thief was recently sentenced to five years in prison for committing what appears to be classic new account fraud. The thief reportedly used a victimâ€™s identity to open a mailbox at a shipping store in Modesto, which he often used to have fraudulently issued credit cards and other financial and identity information mailed.
Typically, new account fraud refers to financial identity theft in which the victimâ€™s personally identifying information Â¾ generally a Social Security number Â¾ is used to open new accounts on the strength of the victimâ€™s name and good credit standing, which are then used to obtain products and services.
Since a thief typically provides an alternate mailing address, such as the shipping store mailbox used in this particular case, the victim never receives the bills accumulating in his or her name, and may remain entirely unaware of the accountsâ€™ existence until the debts have gone unpaid long enough to prompt creditors to track down the victim.
This thief used victimsâ€™ information to create fake drivers licenses with his photo, which helped make the scam stick when he was asked for ID when using fraudulently obtained credit cards.
There are technologies that help credit issuers detect and stop new account fraud by providing real-time intelligence on the device being used to apply for online credit. This technology, called device reputation by iovation Inc., not only alerts businesses when velocity thresholds have been met, it also exposes whether financial fraud, identity theft and other frauds have attempted by the device or associated computers.
Credit issuers can set up and customize their own unique business rules, and iovation analyze each application and then return a recommendation to allow, deny, or review response for the transaction, along with an explanation of the factors involved.
By identifying new account fraud in real time, credit issuers can save millions of dollars in fraud losses annually.Â In one case, a Fortune 100 company used iovation to identify 43,000 fraudulent credit applications and save themselves $8 million in fraud loss over two years.