Synthetic identity fraud is one of the most cunning and challenging threats facing businesses today. These fraudulent identities slip into systems, exploit vulnerabilities, and bypass traditional detection methods, causing billions in losses every year.
But what exactly is synthetic identity fraud, and how can you spot the subtle signals before it's too late? Read on to uncover the mechanics of synthetic identity fraud, its wide-reaching impact, and how leveraging fraud and risk signals can help your business stay one step ahead.
What is Synthetic Identity Fraud?
Synthetic identity fraud occurs when a fraudster combines fake and real information, such as names and legitimate Social Security numbers (SSNs), to create a new identity. After passing detection, these synthetic identities are used to open bank accounts, take out loans, apply for credit cards, and engage in other fraudulent activities.
Unlike traditional identity theft, where an individual's personal information is stolen and used by another person, synthetic identity fraud involves many layers of deception. Criminals invest considerable time and effort into creating these false identities and demonstrating typical credit-building behaviors, making it challenging for traditional fraud detection systems to identify them.
The Consequences of Synthetic Identity Fraud
The financial toll of synthetic identity fraud is significant, with annual losses estimated to range from USD 20 to 40 billion. The financial services industry is particularly vulnerable due to its reliance on personal data for digital transactions. Fraudsters can easily manipulate this data to create credible fake identities.
Alarmingly, it’s estimated that 95% of synthetic identities are not detected during the onboarding process. As a result, companies face losses from unpaid credit, fraudulent transactions, and high fraud prevention and investigation costs. These financial impacts are substantial and often require significant resources to address.
As businesses allocate more time and money to fraud detection and mitigation efforts, the strain on resources and operations is considerable. This includes extensive manual labor for resolving fraud cases, filing reports and conducting employee training.
Recognizing the Signals
Synthetic identities can look and behave like normal customers. Fraudsters will nurture identities for months, sometimes years, to build a positive credit history and maximize their eventual payoff.
Although challenging to pinpoint, recognizable characteristics and recurring patterns make synthetic identities detectable. These discrepancies can indicate fraud. Examples include:
Inconsistent credit histories that don’t align with typical consumer patterns, such as a 40-year-old with a six-month credit history
Multiple applicants with the same address or phone number
Several identities linked to one Social Security Number (SSN)
It's important to remember that while characteristics such as the length of credit history can be helpful in detecting fraudulent activity, focusing on just one characteristic can lead to false positives. This approach may also unfairly disadvantage legitimate customers, like immigrants or individuals recently accessing credit. To more effectively detect synthetic identities, it's crucial to gather and analyze multiple data sets and consider various customer characteristics.
Leveraging Risk Signals to Detect Synthetic Identity Fraud
A multi-layered defense is essential for combating synthetic identity fraud. While no single tool is a silver bullet, layering multiple safeguards can help to build resilience.
Traditional identity verification uses trusted criteria, like validating government-issued IDs, to confirm a person's identity. However, fraudsters continually find new ways to bypass these measures. Email, mobile, and IP risk signals, along with traditional KYC checks, are key components of this multi-layered strategy, providing the necessary breadth and depth to strengthen fraud detection.
During customer onboarding, it's common practice to collect phone numbers and email addresses, followed by 2FA verification, like sending a one-time password to the provided phone number. As a result, bad actors try to sidestep these controls by:
Stealing a legitimate person’s phone number via phone porting
Generating synthetic or one-use phone numbers to bypass 2FA processes
Stealing or acquiring credentials to access a legitimate person’s email address and mailbox
To combat these tactics, businesses can leverage the following measures:
Examine email addresses for their creation date, domain type, and risk level. New or disposable email addresses, as well as those linked to malicious domains, raise red flags.
Verify phone numbers for type (mobile, VoIP, landline), carrier, and porting history. High-risk numbers, like VoIP or recently ported numbers, trigger further scrutiny.
Analyze IP addresses for geolocation, latitude, longitude, and registered Internet Service Provider (ISP). This information helps verify if the IP address aligns with the customer's claimed location and identifies any discrepancies.
Integrating these risk signals allows businesses to build a more comprehensive and dynamic risk profile for each user. When executed effectively, these risk signals can uncover potential synthetic identities without disrupting the customer journey.
How Data Zoo Can Help
Synthetic identity fraud is a major threat to businesses, but by leveraging fraud and risk signals from phone numbers, email addresses, domains, and IP addresses, you can enhance your defenses without compromising the customer experience.
That’s where Data Zoo comes in.
Our Fraud & Risk Indicators, powered by a global network of Mobile Network Operators (MNOs), Email Intelligence, and Cybercrime Analytics, offer comprehensive insights to improve your risk management and customer onboarding.
Our Fraud & Risk Indicators complement identity verification workflows, helping you detect potential fraud risks and assess the risk level based on your risk thresholds.
Detect phone numbers involved in porting scams
Identify compromised email addresses from data breaches, hacking, or sales on the dark web
Spot one-time phone numbers or suspicious email domains used to bypass 2FA
Verify network operator, email domain, and device IP address details
With over 99% coverage of mobile network operators across 60+ countries and monitoring of 1,000+ criminal forums, websites, and chatrooms, Data Zoo enhances your risk management and fraud detection capabilities.
Our Fraud & Risk Indicators can be used independently or integrated with your existing KYC process, offering identity match results and fraud signals in one streamlined response.
Ready to strengthen your defense? Download our guide to gain the knowledge and tools to combat Synthetic Identity Fraud effectively.