We are all familiar with the term, identity theft. It occurs chiefly when a fraudster uses another person's information for financial gain, be it a bank account or credit card number to steal money or make purchases, or another’s personal details to open a new account. Losses from online payment fraud are rising worldwide, with most incidents recorded on new account creations. There is another, less understood form of identity theft which is growing fast and is the hardest to detect and combat: Synthetic identity fraud. It is executed by combining fictitious elements – say, a name or address - with genuine information such as a real social security number to create brand new fraudulent identities. According to the US Federal Reserve, SIF is globally the fastest growing financial crime with up to 95% of potential synthetic IDs undetected by conventional fraud models.

Most fraud detection and prevention methods used to tackle identity theft rely on passwords as the top form of authentication. The challenge is to recognise genuine customers during a faceless interaction. While current authentication methods help to address traditional ID theft by determining that the account holder is who they say they are, by contrast, identifying a synthetic identity by these methods would only serve to verify that synthetic identity – i.e. the account itself belongs to a criminal.

A synthetic identity can be established by a fraudster via a series of steps aimed at building a good credit history over time so available credit is increased with new cards and higher limits. Ultimately then the synthetic identity will max out all credit and disappear. The key to uncovering synthetic identity fraud before the imposter can profit from it is to evaluate the depth and consistency of information available about such fake IDs using multiple data sources. Genuine identities exhibit consistent attributes over time from phone, address or employment records to email and social media accounts, so they regularly appear in different data sources. By contrast, synthetic identities tend to be inconsistent. While a fake applicant may give some real details such as a name visible in various data banks, other elements of the profile are fabricated so they do not reoccur or conversely, when the identity is entirely fictitious, the profile seems to be suspiciously too uniform.

EMDYN has responded to the growing incidence of synthetic identify fraud by publishing a detailed case study offering solutions based on a layered approach to the problem. EMDYN BioTrace gives businesses the means to identify genuine customers, without compromising the user experience and introducing unnecessary friction. It combines ultra-fast, scalable biometric technology with investigative tools for a deeper analysis to detect potential frauds. Unlike transaction-based fraud detection methods, BioTrace prevents fraudulent identities from applying for accounts during onboarding before any real damage is done. It can be deployed within just one month on or off-site, in one or multiple locations and full data privacy is assured.

EMDYN BioTrace is especially relevant to the threats posed to the financial services industry from both traditional ID theft and the growing synthetic identity fraud. To uncover the full features and benefits of EMDYN BioTrace, its applications across multiple situations and how it can provide a cost effective, accurate solution to your ID validation issues, let’s talk.

You can download the FULL COPY of this case study here