What is Synthetic Identity Fraud? How to Detect It in 2024

What is Synthetic Identity Fraud? How to Detect It in 2024

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Last Updated: February 21, 2024 by Bence Jendruszak

Criminals have found new ways to create convincing-looking identities – and one is synthetic identity fraud, fueled by the 14 million identities that are stolen each year.

They are combined with fake and generated data to help criminals achieve more – as well as with each other to create new personas. This is what makes fighting synthetic identity fraud so challenging.

But this isn’t as hard as it sounds with the right risk management tools. Let’s break it down below.

What Is Synthetic Identity Fraud?

Synthetic Identity (ID) fraud happens when criminals use a combination of fake and real data to create a new identity and then defraud one or more businesses. They can use this synthetic identity to bypass Know Your Customer (KYC) verification checks, abuse promotional offers and bonuses, take out lines of credit, buy goods with stolen credit cards, launder money, and more.

Fraudsters create synthetic identities in several ways. Some manipulate genuine ID data. Examples include changing a date of birth or part of a social security number. Others assemble real personally identifiable information (PII) from multiple sources, combining them to create a new identity. Some fraudsters manufacture elements of the identity entirely, for example by using a randomized social security number within a specified range of digits.

Regardless of which data points they are made from, businesses that identify synthetic identities should always flag them. Synthetic identity fraud is usually the first step in more elaborate fraud schemes, so catching it early is essential.

types of synthetic IDs: manipulated, blended and manufactured

Regardless of what data points the synthetic IDs are made of, the people who create them should always be considered high-risk. It is crucial to flag them as soon as possible as synthetic identity fraud is usually just the first step in more elaborate fraud schemes.

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How Does Synthetic Identity Fraud Work?

Synthetic identity fraud works by a fraudster creating an identity, then using it to defraud one or more institutions.

The first step is for the fraudster to create a synthetic identity, blending stolen, manipulated, and/or manufactured data. They might, for example, use a real social security number that has been stolen from a child, so has no credit history associated with it.

Next, the fraudster applies for credit. The goal is to create a credit file then build up a solid repayment record. As the synthetic identity has no credit history to begin with, this can take time. The fraudster will likely have to apply for multiple lines of credit before a lender will take a chance on them.

All the fraudster needs is a single line of credit. Once they have that, they can make regular, timely repayments to boost their credit score. This makes them eligible for credit with a wider range of lenders and for higher limits.

Eventually, the fraudster applies for a larger line of credit, takes the funds, and vanishes. The process can take months or even years; synthetic identity fraud is not a quick win for criminals, but it can be very lucrative.

As with all types of fraud, there are variations on the theme. Some fraudsters, for example, pay genuine account holders with good credit scores to link their accounts to the synthetic one, for added authenticity. Others create fake digital trails by setting up social media accounts linked to the synthetic identity. Some even try to double their gains, by using fake checks to repay the line of credit the first time they take it, then maxing it out a second time before the checks bounce.

How Dangerous Is Synthetic Identity Fraud?

One of the biggest dangers of synthetic identity fraud is that it is hard to catch. As reported by Forbes, synthetic identity fraud could cost businesses nearly $5 billion by 2024.

More often than not, the end goal is to bypass KYC screening, which may damage your business in numerous ways, including:

  • KYC and compliance fines
  • Loss of trust and brand reputation
  • Legal issues with the rightful ID holders

Moreover, synthetic identity fraud also impacts payments and chargeback rates, when fraudsters make payments in someone else’s name.Based on Experian’s research, synthetic identity fraud accounts for 80% of credit card fraud losses, and nearly 20% of chargebacks incurred by merchants

Last but not least, for consumers, the consequences are even direr, particularly in countries that realy heavily on static personally identifiable information PII). In the US, for instance, Social Security numbers (SSNs) are highly valued by fraudsters, as it allows them to usurp someone’s identity with relative ease.

Should a fraudster use your ID as part of a synthetic identity, you may have to deal with loans taken out in your name, lower credit score, and, at worse, criminal convictions.Fighting to clear your name of these misdeeds is also costly, both in terms of lost resources and emotional damage. It may take months or even years before you can finally convince the legal system that a fraudster targeted you using your ID details – up to 200 hours, according to a report from the SANS Institute.

Steps for Synthetic Identity Fraud Detection

Synthetic identity fraud is notoriously hard to detect, as it is specifically designed to fool anti-fraud measures. However, companies can deploy a number of powerful features to identify users beyond the standard KYC checks. 

1. Leverage Digital Footprint Analysis

Online digital footprint analysis is designed to identify people without relying on ID documents or biometrics. It’s a fantastic way to pre-screen for KYC checks, but also to instantly flag potential synthetic ID fraud.

Digital footpris analysis includes email and phone number analysis, which also lets you link data to social media profiles. This has a number of positive results for companies as you can:

  1. Use social media profiles to confirm identities.
  2. Flag users with no social presence
  3. Mark high-risk customers based on the kind of social networks they have joined.

Similarly, customers who sign up with virtual SIM cards, fake phone numbers or invalid email addresses should at least be considered high risk for your business.

2. Extract More Data With IP and BIN Lookups

Another way to spot suspicious identities is to find red flags in user’s alternative data, such as IP addresses or card numbers. In fact, you could even combine both tools to spot inconsistencies, such as a card issued in one country, and an IP pointing to another.

As is always the case with this kind of granular data, it’s not enough to claim an identity is fraudulent. You have to combine as many data points as possible to create a user profile and flag the suspicious ones accordingly.

3. Deploy Device and Browser Fingerprinting 

If fraudsters are successful once, they tend to target the same companies multiple times. The challenge for them isn’t to create hundreds or thousands of synthetic IDs; it’s to make it look like each of these is connecting to your site as a new and legitimate user.

A device fingerprinting module can identify the tools that a fraudster relies on to spoof different users and devices. This is done by extracting data relating to their configuration of software and hardware, allowing you to spot:

  • unique browser setups
  • suspicious hardware configurations
  • emulators and virtual machines

Moreover, device fingerprinting lets you create hashes for each unique configuration, which lets you spot connections between users and instantly flag repeat offenders. 

4. Identify Fraudulent Behavior via Velocity Rules

Last but not least, it’s not just about looking at data points, but about understanding user behavior. This is particularly important for the more sophisticated attacks, and those perpetrated by money mules who use their real IDs.

In fraud prevention terms, user behavior is identified via velocity rules. These aren’t necessarily complex but can analyze a wide variety of data points, including timeframes. 

Here are some examples:

  • How quickly did the user go through the entire KYC process?
  • How quickly did they complete the user authentication stage?
  • Did they enter their social security number in one keystroke?
  • How many times has a similar browser/hardware setup appeared in the last few days?
  • How frequently does the user request to raise their credit limit?

Of course, the sky’s the limit with the kind of data you want to examine. But the key here is that you can identify suspicious behaviors, even from fraudsters who have already managed to infiltrate your platform.

5. Enable Machine Learning Suggestions

A whitebox machine learning system is particularly adept at spotting patterns that point to synthetic ID fraud. By extracting all the data mentioned in the points above (device, IP, card, behaior) and feeding it to the system with the right labels, you can expect insights that no analysts could have extracted.

If you are consistent in your reporting and use enough feedback mechanisms, you can begin getting suggestions that may point to the most undercover and sophisticated fraud. Best of all, the efficiency will improve over time, and the rules are based on your own historical business data.

Tips to Preventing Synthetic Identity Fraud

While there is very little you can do about a data leak (except minimize the amount of personal information you give out to third-party companies), all of the other exploits can be mitigated with common sense and basic security measures. These include:

  • Creating unique, complex passwords: you may use a password manager or browser feature designed to create hard-to-guess passwords. Avoiding reusing the same passwords is key to reducing risk.
  • Be suspicious of online/phone interactions: it’s a sad reality, but any kind of online interaction with strangers could potentially link to social engineering. Exercise due diligence, whether you’re using a dating app, selling items on an online marketplace, or making a payment to a new online store for the first time.
  • Deploy cybersecurity and fraud prevention tools: antivirus, 2FA, encryption… These tools are easier to leverage than you might think, even for the less tech-savvy.
  • Regularly review your credit reports: one of the earliest signs of identity theft will be suspicious financial activity. Credit monitoring can help flag inaccuracies and prevent further damage before it’s too late.
  • Be mindful when handing out PII: any online or offline interaction that requires you to submit personally identifiable information (PII) should be carefully considered, whether it’s a social security number (SSN) or a copy of your passport, or even your full name on social media.
  • Consider your relatives’ ID: criminals have been known to stoop as low as to steal children’s IDs to open credit lines in their name. Some parents take preventive action by freezing child credit reports.

Synthetic Identity Fraud Detection With a Multi-Layered Approach

Criminals have access to a growing number of resources to create synthetic IDs. For targeted companies, it’s not enough to simply implement static ID checks and fraud rules, and leave them to run on autopilot. 

However, you don’t have to waste all your resources on intensive manual reviews for identity proofing. Using sophisticated risk tech, you can combine tools to create a net that will filter out bad users, and only allow in those who will help your company reach its goals.

Frequently Asked Questions

What are the warning signs of synthetic identity fraud?

If you notice strange payments on your statement or start receiving suspicious emails, it’s possible some of your ID documents have been stolen and used for synthetic IDs.

How do people create synthetic identities?

To create a synthetic identity, you need some kind of real document to begin with. It could be a name, address or social security number. The fraudster then modifies or tweaks the information for their need.

Why do fraudsters use synthetic IDs?

Synthetic IDs are harder to detect than made-up, completely fake IDs because they contain an element of truth (the person’s ID documents). This is why fraudsters use them to bypass KYC checks or for fraudulent transactions, among others.

What kind of stolen data is used in synthetic ID fraud?

Fraudsters rely on any identifiable information they can find, including tax-related information, medical records, social security numbers, and even children’s identity records. 

You might also be interested in reading about:

Learn more about:

Digital Footprinting | Browser Fingerprinting | Fraud Detection API | Fraud Detection with Machine Learning & AI

Related Source for this article:

  • BBC: I was a teenage ‘money mule’
  • Federal Reserve: Synthetic ID Fraud in the US Payment System
  • Comparitech: Identity theft facts & statistics: 2019-2022
  • Experian: Experian’s 2023 Future of Fraud
  • IEEE: DeepFake Detection for Human Face Images and Videos: A Survey
  • Forbes: Socure Report Examines Rise Of Synthetic Identity Fraud

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Author avatar
Bence Jendruszak

Bence Jendruszák is the Chief Operating Officer and co-founder of SEON. Thanks to his leadership, the company received the biggest Series A in Hungarian history in 2021. Bence is passionate about cybersecurity and its overlap with business success. You can find him leading webinars with industry leaders on topics such as iGaming fraud, identity proofing or machine learning (when he’s not brewing questionable coffee for his colleagues).

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