Synthetic Identity Fraud: You can buy data… Or you can generate knowledge
By Doug Wood, Infoglide Senior VP
In recent years, the integrity of the SSN has been severely compromised in credit bureau profiles and other trusted authorities. This threat, known as Synthetic Identity Fraud (SIdF), uses modified name and date of birth attributes combined with another person’s Social Security Number. This scheme has caused a phenomenon called “piggy-backing” in the major credit bureau profiles.
Piggy-backing is the newly created fraudulent profile that enters the system as ‘genuine’ and is shared between credit bureaus and trusted authorities in an authentication fraud loop. This is how institutions becomes at great risk. SIdF should not be confused with ‘true name’ identity fraud. The identities of real people are assumed in true name identity fraud, whereas scammers create a whole new identity to open an account via SIdF.
The Federal Trade Commission (FTC) estimates that SIdF costs American businesses $50 billion per year in fraudulent charges. In our technology driven world, where personal information is easily accessible, synthetic identity theft is the fastest growing crime in America.
ID Analytics™, a leading identity analysis company who was recently acquired by consumer identity protection company LifeLock, Inc., reports that synthetic identities are more commonly used to commit identity fraud than true-name identities. Their study also showed that, overall, synthetic identity fraud comprises 88.3 percent of all identity fraud events and 73.8 percent of the total dollars lost by U.S. businesses.
Systems that rely on public record databases alone are generally capable of detecting, on average, 85 percent of synthetic identity fraud attempts and 72 percent of true-name identity theft attempts. Approximately 18 percent of total identity fraud attempts are not detectable using these systems. That startling statistic – that one in 5 synthetic identities go on to wreak havoc – is the genesis behind Infoglide Software Corporation’s SIdF Detection offering for new account opening.
Working with leading financial institutions, privacy lawyers, industry data providers, and a variety of fraud prevention experts, Infoglide has developed a process for scoring new account applications for SIdF using a combination of a bank’s internal fraud data, publicly available data, social media analysis, and the new Inter-Bank Intelligent Risk Data Search (I-BIRDS) mechanism.
I-BIRDS, another Infoglide innovation, allows financial institution members to securely search into each other’s known fraud database without revealing any PII. The privacy-compliant search returns only a ‘probability score’, or likelihood that one or more member banks matched a searched identity in their ‘bad guy’ list. No other data is returned, yet the querying bank now has valuable information in the fight against SIdF.
Using their core software product, Identity Resolution Engine (IRE), Infoglide performs a series of searches into those disparate internal and external data stores to provide a realistic view of risk – including the 18% of SIdF cases that standard public data searches completely miss.
Using entity link analysis, IRE is able to identify suspicious relationships between the applicant and other members, employees, vendors, and of course known fraudsters and SIU cases.
Banks and credit providers can certainly buy data and scores from a variety of aggregators, but only the Infoglide SIdF Detection tool allows organizations to generate NEW information in the fight against identity-based financial crimes.