Static data alone can’t ward off synthetic fraudsters
The synthetic ascension
In 2021, identity fraud targeting US-based e-tailers made up 30% of all fraud losses. Within that troubling percentage lies an uptick in synthetic identity fraud, in which bad actors fuse stolen data (phone numbers, emails) with fake data to create a bogus identity.
Post-pandemic, fraudsters have feasted on users’ anxiety and increased online activity, phishing login information with very little effort. Given this trend, experts foresee another rise in synthetic identity fraud in 2022, especially in the financial services arena and on platforms that utilize seamless signup and other quick decisions.
With factors like social security number randomization making synthetic “Frankenstein identities” more prevalent, stopping this mish-mashed form of identity fraud is imperative before it festers into a costly and potentially years-long disaster.
Not your average identity fraud
The challenge of preventing synthetic identity fraud lies in its patchwork composition. A synthetic identity pulls together fake and legit info from multiple sources instead of targeting a single consumer victim, making it much more difficult to detect. With no defrauded person to tip off companies, accounts created via synthetic identity can remain active indefinitely like clandestine, money-sucking leeches only to vanish once the on-file credit card maxes out.
Again, there’s no real-life person to trace the account back to, which complicates the identification of synthetic identity fraud, much less the calculation of losses (assuming fraud is circled as the culprit). Unfortunately, differing interpretations of synthetic identity fraud among enterprises can often chalk cases up to credit-related issues, leaving credit lenders and related providers to carry the financial burden.
If need be, synthetic fraudsters can bypass defenses with more than a fake SSN and stolen email. Forget Frankenstein identities — the craftiest of synthetic fraudsters are combining facial features from multiple people with AI to create realistic “Frankenstein faces.” Yet another wire-crossing maneuver that throws traditional fraud prevention solutions off the scent.
The synthetic antiseptic
Old school fraud prevention tools rely on static data such as physical address and device fingerprinting to detect bad actors. This won’t cut it for synthetic identity fraud.
The only way to effectively root out stealthy synthetic fraudsters is to combine static data with live and historical real-time user activity data. By adding this extra layer of real-time intelligence —behavioral biometrics, time of day, location, etc. — there are too many holes for fraudsters to cover up or build an authentic digital “legend” and more than enough information to help companies spot a fraudulent identity.
This is precisely the extra punch Deduce provides. We pack more than 450 million anonymized US profiles and 1.4 billion daily user activities (logins, account creations, checkouts, etc.) from over 150,000 websites and apps into our real-time Identity Network, protecting organizations from financial losses and the other nightmarish side effects of synthetic identity fraud. For example, a solution that’s solely reliant on static data will fall victim to false positives and ultimately turn good customers away, while the Deduce approach is able to contextualize scenarios where a new device or other factor may not be consistent with identity fraud.
Fraudsters can fake a number of different attributes, but nothing they spoof can outsmart the collective intelligence and profile history of the Deduce Network. The breadth and diversity of our data (transactions, social media activity, etc.) is too gargantuan — and too expensive for the average fraudster to circumvent.
Tap into the Deduce Identity Network today and bolster your defense against synthetic identity fraud. Contact us here to get started.