8 Signs You May Be Dealing With Fraudster Fake ID

Meet Aida: Data Scientist, Trust Builder, Fraud Fighter

Hello, I’m Aida, the world’s first identity verification bot. My name is an acronym for Authentic Identity Agent, but I’m also named for the first computer scientist, Ada Lovelace. Like my namesake, I thrive on studying patterns, devising solutions, and seeing the truth others miss.

You can learn a lot about people—including fraudsters—from the digital exhaust they leave behind. Patterns emerge from these datasets. Over time I can extract insights that can help you understand how your fellow humans behave when they transact online. With this information, businesses can make smarter decisions about their customers.

I believe truth lies in data.

In this article, I’ll share significant findings from my analysis of actual fraud attempts across our client base. I was able to spot certain trends that predict a greater likelihood of fraud during account origination, when a business has never before seen an applicant. However, it’s important to note that fraud changes as often as trends do. Therefore, I continue to learn and evolve faster than the fraudsters, which is the advantage I have as a machine.

Content Summary

8 Signs You May Be Dealing With a Fraudster
Sign 1: Fraudsters Avoid Mobile Numbers
Sign 2: Fraudsters Are More Likely to Use Common Male Names
Sign 3: Fraudsters Aren’t Social
Sign 4: Fraudsters Don’t Share Their True Location
Sign 5: Fraudsters Don’t Like to Reveal Their Age
Sign 6: Fraudsters Give Real Addresses, but with Incorrect Details
Sign 7: Fraudsters Use Active Email Accounts and Are More Likely to Use Realistic-Looking Email Addresses
Sign 8: Fraudsters Use Made-up Email Addresses to Evade Detection by the Victim

8 Signs You May Be Dealing With a Fraudster

After processing billions of data points on new applications, I’ve learned a few things about both consumers and fraudsters: they’re more alike than different! Fraudsters have become so good at assuming real identities or making fake ones that it’s hard to distinguish between real and fake. It gets even more complicated when a legitimate transaction looks like a fraudulent transaction. Businesses lose good customers by erroneously thinking they may be fraudulent, and approve fraudulent accounts that appear to be completely valid. The human eye cannot tell the difference.

Most businesses flag these applicants for manual review, but that disrupts the digital flow, causing many customers to abandon the transaction. And with the subtle differences between the fraudsters and real applicants, one cannot rely on human intuition alone.

While there are certainly differences in fraudster behavior, I’ve learned that you cannot look at one variable; you must look at multiple variables to get the most accurate result.

However, after careful analysis from actual fraud attempts detected across our client base, I was able to extract a few key insights that help us better understand the profile of a fraudster.

Sign 1: Fraudsters Avoid Mobile Numbers

When a phone number is required, approximately two-thirds of the mobile phone numbers provided on legitimate applications are registered with one of the top four U.S. carriers (AT&T, Verizon, T-Mobile, and Sprint).

The most likely reason behind this is fraudsters’ propensity to use so-called “burner” (pre-paid) phones and/or SIM cards at the minimum expense possible. Most of these phones tend to be provided by smaller carriers in local convenience stores, allowing the user to remain completely anonymous. There’s an even higher likelihood of fraud when a VOIP number is provided.

Fraudsters are less likely to provide a mobile phone number (-14.5%) if asked for phone information on an online application. But if they do provide a mobile number, it’s less likely to be associated with one of the top four mobile carriers. (-12.6%).

Sign 2: Fraudsters Are More Likely to Use Common Male Names

I noticed an interesting trend about the names on fraudulent applications – they are all common male names. They are more likely to input a name like John, David, or Michael – which, according to the Social Security Administration, has held the top spot for most popular male name 44 years out of 100. Fraudsters must love stats as much as I do.

When filling out personal information, fraudsters are more likely to input popular male names as their first name.

Sign 3: Fraudsters Aren’t Social

Approximately 80% of the identities used on fraudulent applications have no associated social media accounts. While the absence of social media has a high correlation with fraud, note that some legitimate applications also have no social media presence. However, these legitimate applications may have other strong indicators that predict identity. This means that differences between fraudulent applications and real customers can often be subtle and hard to eyeball – unless you’re a data scientist trained to find the needles in the haystack or an AI like me.

People live online and most use social media to connect.

Sign 4: Fraudsters Don’t Share Their True Location

Every time you transact online, the site collects information about the IP of your device, as well as the type of device used. I have noticed that fraudsters often provide address data that is inconsistent with their location. The device used is less likely to be connected from the address provided (-9.8%) and more likely to be connected through a proxy (+9.7%).

The device used is less likely to be connected from the address provided (-9.8%) and more likely to be connected through a proxy (+9.7%).

Sign 5: Fraudsters Don’t Like to Reveal Their Age

I have learned that most humans don’t like to share their age once they reach a certain point. However, when it comes to filling out online applications, a fraudster rarely inputs a date of birth if it’s not required. When it is required, a fraudster is more likely to present themselves as 25 to 45 years old.

When a date of birth is required, a fraudster is more likely to present themselves as 25-45 years old.

Sign 6: Fraudsters Give Real Addresses, but with Incorrect Details

Since fraudsters have realized that most identity verification platforms use name and address matching as a strong indicator of identity, fraudsters rarely give completely fake addresses anymore. But, they still don’t get it all right. They are more likely to use an invalid house/apartment number or an incorrect zip code associated with the address.

The name and address provided are more likely to not match (+18%), and the house number is more likely to be missing or incorrect (+5.6%).

Name and address are more likely to not match 18% more often, while there’s a 5.6% greater likelihood that the house number is missing or incorrect.

Sign 7: Fraudsters Use Active Email Accounts and Are More Likely to Use Realistic-Looking Email Addresses

In the early days of online fraud, both the technology and fraudster were less sophisticated, which means they could get away with using fake and inactive email addresses like [email protected]. Now, however, all email addresses are checked to determine active status, as well as the age of the account. This means fraudsters had to step up their game with an active email account— and a more realistic-looking name.

Virtually all legitimate applications include a valid email address (97%). But it’s interesting (and troubling) to note that 87% of fraudulent applications also now include a valid email address (meaning it’s a valid domain and the inbox accepts email).

Sign 8: Fraudsters Use Made-up Email Addresses to Evade Detection by the Victim

While fraudsters provide valid email addresses, the email address itself is less likely to match the rest of the identity. By using a made-up email address where they can receive confirmation, the fraudster evades detection by the victim of identity theft. If a fraudster were to use the real email address of their victim, it would immediately alert the owner of suspicious activity and shut down their ruse. Hacking into the real email account just for new account validation is rarer, given how cumbersome a process it is. A name to email match can be found for 60% of legitimate customer applications, yet for only about 32% of fraudulent applications.

A strong name to email match can be found for 60% of legitimate customer applications, yet for only about 32% of fraudulent applications.

How will you tell the difference between real customers and fraudsters?

The most significant finding from Aida’s Insights on Identity: The Fake ID Edition is that there is no one single best predictor of fraud. Fraudsters are now quite adept at creating identities that look real, which makes the task of identity verification harder for both humans and rules engines. Using sophisticated machine learning, Aida finds the nuance of each identity in every transaction – without causing friction to the applicant. Aida unlocks the mystery of who’s behind the screen.

Source: Socure