Synthetic Identity Fraud

$1.3 Billion

in synthetic identity losses estimated by credit card companies for 2020

53%

rate of synthetic identity growth per year expected for the next several years

2011

the year during which Social Security Numbers were randomized in the US, making it easier for synthetic ID fraudsters to operate.

New risk for banks and merchants

Not a 'victimless crime'

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Synthetic identity fraud – schemes that use fabricated identities – is growing fast with banks and digital merchants most vulnerable. If you don’t catch synthetic identity accounts early, they can be very difficult to catch because they exhibit all the behaviors of an ideal customer. Detect synthetic IDs before they cause significant and unexpected losses by scrutinizing identity factors at account creation. Fraud.net’s global transaction network can sort out the highest risk synthetic identity abusers. Read our deep dive into synthetic identity theft.

How to steal using an identity that doesn't exist?

‘Synthetic Identity’ fraud — a group schemes that use completely or partly made-up identities — is on the rise and hitting banks especially hard. Specifically, fraudsters manufacture IDs to obtain credit cards and other lines of credit, then diligently pay their bills for long periods of time, some times many years. Once their credit limits have been raised to a certain threshold, they “bust out”, spending all the available credit, then disappear.

The Power of Getting Identity Right

Organizations are challenged on many fronts in their efforts to protect their customers and their businesses against fraud. The increasing growth and complexity of digital commerce leaves merchants and financial services firms vulnerable to cybercriminals and requires that organizations continue to innovate their security and anti-fraud policies across all digital channels.

But once your organization can accurately confirm the identity of your new website visitor, applicant or customer, the virtuous cycle begins. Use Fraud.net’s Identity Services to identify and remove the <1% of fraudulent and high-risk users so that you can focus on thrilling the >99% of high-trust customers.