ID Analytics introduces solution to address multifaceted synthetic fraud challenges

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ID Analytics released two new products designed to provide businesses with a solution to the disparate challenges of synthetic identities. The approach taken by both ID Score Synthetic and Credit Optics Intentional Misuse complements existing fraud and credit risk solutions and attacks a range of synthetic identity abuse. The solutions can help enterprises minimize losses associated with synthetic identities while minimizing friction for low-risk consumers.

Synthetic identity fraud has become a challenging issue as fraudsters become more sophisticated and build synthetic identities which appear valid to most fraud and credit assessments. Today synthetic identities are not always created using valid information from multiple consumers. Many are composed of invalid information with no ties to a known consumer – making them difficult to detect.

With no victim to report that their identity has been stolen, or conflicting personal identifying information (PII) to raise a red flag, fraudsters can operate undetected for years, building up credit with multiple institutions before busting out and vanishing without a trace.

“ID Analytics is tackling the problem of synthetics by focusing on the root cause – identity legitimacy,” said Ajay Nigam, CEO of ID Analytics.

“All forms of synthetic fraud are subject to this question. Only by leveraging an identity intelligent assessment can one form an opinion on legitimacy – our solutions were developed through an R&D process that included extensive consultation with our customers and partners and were designed from the ground up to maintain a high level of performance, as synthetic fraudsters shift their methodologies.”

Current synthetic identity solutions often fail in a number of ways. Clever synthetic fraudsters can pass many traditional identity fraud screens which aren’t optimized to the problem, and existing synthetic fraud detection solutions can miss the damage caused by fraudsters who do not engage in traditional “tricks of the trade” like credit piggybacking.

Likewise, existing credit risk solutions miss applications from synthetic identities who have developed profiles for large longer-term payoffs and limit lender’s ability to take adverse action if malicious intent is identified.

To address these challenges, ID Analytics developed two new products: ID Score Synthetic and Credit Optics Intentional Misuse. These products target the core issue of identity legitimacy and the typical outcomes of synthetic fraud:

ID Score Synthetic – Designed from the ground up to address the core challenge of synthetic identity fraud, while sparing low risk consumers from unnecessary friction, ID Score Synthetic attacks the root cause through a predictive assessment of identity legitimacy. It is predictive regardless of methodology or attack vector such as manufactured synthetic, manipulated synthetic and regardless of the length of time the synthetic identity has been in use. Beta testing with ID Analytics customers found that it identified more synthetic fraud risk than legacy systems in place at leading financial institutions.

Credit Optics Intentional Misuse – For organizations that view synthetics as a credit issue, Credit Optics Intentional Misuse is designed to address the net outcome of credit abuse – including synthetic identities and first payment default – by identifying applicants who may be plotting to misuse and abuse requested credit or services. As an FCRA solution, risk assessments from Credit Optics Intentional Misuse are adverse actionable – an important feature when dealing with applicants who intend to misuse credit, but who have passed through identity proofing screens. This solution was developed as a direct response to feedback from leading U.S. lenders and service providers to address the broader range of credit abuse, including synthetic identities. In a beta test with a major financial institution, the solution identified nearly 3x more risky consumers over a traditional credit risk model.

“Synthetic identities have emerged as one of the biggest challenges for businesses because they are so difficult to detect. In 2017, synthetic identity fraud resulted in $800 million in losses through credit cards alone, and that could reach $1.2 billion by 2020,” said Julie Conroy, research director for the retail banking & payments practice at Aite Group.