Applicant fraud: why now and how to stop it

Hey, it’s Jason Zoltak. 👋 If this is your first time reading The Final Interview, here’s where you can subscribe so you don’t miss future breakdowns on navigating AI in recruiting and talent management. 

The Future of Tofu: Building the Best Inbound Tool

Last week I wrote about Tofu’s pivot, a change towards building a powerful Agentic-AI recruiting platform that equips companies with better data, signal and decision making.

The reason being is that the marketplace alone wasn’t enough, and there are simply a ton of problems we feel haven’t been addressed.

I’ll reiterate because I feel it’s important. The hiring marketplace our users love isn’t going away;, we’re just focused on creating a product that meets companies ever- evolving hiring demands. So we’ve reimagined Tofu into a powerful, Agentic AI-first platform that works as an extension of your inbound team, performing tasks that enable you to:

✅Screen smarter: AI-powered resume reviews customized to your hiring needs.

✅Search deeper: Enrich your ATS with rich, searchable data across the internet.

✅Filter faster: Detect and eliminate fraudulent applicants with ease.

The foundation of any great recruiting process is high-quality data. We are committed to arming our customers with the best signal and inputs they can get so they can move faster, work smarter and make better decisions.

And that starts with building solutions to the biggest problems recruiters are facing in 2025. 

One of the most annoying problems today? 

Applicant fraud. 

Fake Applicants, Real Threats

When we first started talking to users, customers and prospects about Tofu’s AI resume review tool, we noticed a recurring theme emerging:

“We’re inundated with fake profiles.”
“It’s hard to tell who’s real and who’s not from a resume.”
“We hired someone, and the person who showed up wasn’t the one we interviewed.”

Imagine spending an entire day interviewing applicants in the final round, only to discover you’ve been duped: your top candidate isn’t the qualified applicant they claimed to be.

While we’ve all sounded the alarm bells around fake jobs and other scams affecting job seekers, applicant fraud is also on the rise–and it’s becoming a major headache for many recruiters. 

This isn’t a future problem; it’s happening right now—and shows no sign of lessening as scammers continue to become more sophisticated.

This issue is especially prevalent in remote companies. Without the need for an in-person presence, fraudsters can more easily slip through the cracks of a recruiting process. 

While fraud can be as minor as fudging work experience on a resume, some fraudulent candidates are part of organized operations designed to gain unauthorized access to company systems. Some companies are even being successfully infiltrated by fake candidates, with some even gaining access to sensitive IT systems. 

It’s a security risk no one can afford.

At the very least, it’s a massive headache–one your recruiting team shouldn’t have to deal with. By our estimates from Tofu platform data, mid-level, remote engineering jobs get an average of 20%-30% of fake applications. Sometimes it’s higher. If you hire remotely and this doesn’t feel like a problem to you, I’d caution you to look again.

Thankfully, we’ve built something to help protect against this. I’m breaking it down below 👇

How Applicant Fraud Detection Works

Tofu’s Applicant Fraud Detection feature makes it quick and easy to highlight fraudulent candidates before they even hit your team’s radar.

It flags suspicious profiles using billions of internet data points to evaluate attributes such as:

• LinkedIn profile health

• Keyword stuffed resumes with language that too closely matches your JD

• “Perfect” work history curated exactly to the listing requirements 

• Discrepancies between social profiles, resume, and reported work experience

• Lots of other stuff too

None of these on their own are evident red flags. It’s how they work together where you need to read between the lines. Anyone can spend the time to run through these checks and determine if an applicant isn’t who they say they are, but at scale, it will kill your time and productivity.

The average remote role gets 300 applicants. At an average of 30% fake applicants, you’re wasting 45 minutes on candidates that you could’ve easily filtered out. 

This feature is one part of Tofu’s mission to be the ultimate inbound filtration tool—helping you identify the best candidates, enrich their profiles, and ensure they’re legitimate.

When we sent out our first announcement email about this feature to beta testers, the response was overwhelming:

“This is exactly what we need right now.”
“Fake profiles are such a huge issue—can’t wait to try this!”
“This will save us hours every week.”

It’s becoming clear to me that this isn’t just a tiny annoyance—it’s a problem begging for a solution. Wham bam, alakazam. Now you can use it.

What’s Next?

Tofu’s Applicant Fraud Detection is already live, and we’re releasing more tools in the coming weeks. I won’t share what that is yet but stay tuned.

Tofu is here to make your recruiting workflows smarter, faster, and safer while preserving the magic of your human team’s ability to connect with candidates.

If you’re tired of wasting time on fake candidates and want to take control of your hiring process, let’s chat.

Jason