How familiar is your institution with synthetic identity fraud? Are you aware that fraudsters are combining a possible valid SSN with other fake identity elements to bypass your security measures? Synthetic Identity theft is nothing to ignore. According to a recent study from ID:A Labs the fraud rate for synthetic identities has increased more than 100% since 2010 and the problem continues to grow. Unfortunately, the advent of digital technology and the anonymity it provides has led to a rise in the creation of fictitious credentials used to commit fraud.
The true danger of synthetic fraud is that, unlike third-party fraud where an entire identity is stolen and used to defraud enterprises and victims, synthetic fraud frequently has no specific consumer victim. The lack of a clear consumer victim often allows a synthetic fraudster to operate undetected for months, only to eventually “bust out” (suddenly use the remainder of a credit line). This long-term “con” or fraud is particularly dangerous because criminals employing this technique for financial gain can often nurture the synthetic identity into generating larger credit limits and larger loss amounts for the lender than the average identity theft scenario. It is estimated that synthetic identity fraud accounts for 85% of all identity fraud in the United States, costing an estimated $2 billion a year.1 So how can your institution identify and stop synthetic identity fraud?
The potential rise of synthetic identity theft indicates that institutions may not be authenticating the identities of credit applicants. Instead it appears that some institutions may be authenticating an applicant’s SSN by comparing it to the date of birth provided, rather than ensuring that the number is actually associated with the applicant. Synthetic identities can be identified with a high degree of confidence using sufficient historical data combined with our proprietary analytics. The availability of historical application data, especially data on the asserted SSN, is the key to determining if an identity is artificial. With ID Analytics’ ID Network, it is possible to confidently determine whether an identity is synthetic or not. Additionally ID Analytics’ methodology can categorize identities as likely synthetic identities, possible synthetic identities for further consideration or normal identities.
Check out our infographic below, The Rising Tide of Synthetic Identity Fraud, to learn how your organization can effectively combat the increasing problem of synthetic identity fraud. For more on this topic download our white paper The Long Con: An Analysis of Synthetic Identity.
Ken Meiser is the Vice President of Identity Solutions at ID Analytics.