How to build a fraud-resistant hiring program

To catch fraud earlier, start verification earlier. Confirm identity at the beginning of the process, then carry that verified identity through each screening step.

Starting with identity verification gives every later step, including the background check, a more reliable foundation. Without a liveness check, you could end up with a complete and accurate report for the wrong person.

Checkr uses government-issued ID authentication, live selfie matching, liveness detection, device and behavioral signals, and deepfake detection certified at Level 2 by the National Institute of Standards and Technology (NIST). The process takes about two minutes, requires no external account or digital wallet, and can be placed at application, background check, onboarding, or at high-risk moments after the employee has started.

Look for coverage across application, interview, background check, onboarding, and post-hire in one connected screening flow. Fraud can appear differently at each stage, and manual review becomes harder as hiring volume grows.

Four of these six gaps fall outside a traditional background check. A modern provider should be able to surface fraud signals at any stage from one dashboard, without making your team or candidates switch tools.

Here’s where common types of fraud tend to appear and which fraud detection tools can help detect them at any scale.

Source: 2026 State of Screening Compliance Report

Many teams still detect fraud through a single batch of checks or an inconsistent manual process. A sequential flow spreads verification across the hiring journey, makes results easier to track, and helps teams avoid spending time and money on fraudulent candidates.

Only 21% of large organizations currently use a tiered approach, with lighter verifications early and more time-intensive checks later. Half run the same full set for every candidate in a role, simultaneously. Sequencing checks is at the forefront of the evolution of screening and fraud detection, and hiring teams that start to rethink their screening journey now will be leading the pack down the road.

Progressive checks change the quality of what reaches each hiring stage:

This approach also makes the process more efficient. Teams spend less time interviewing, checking references, and reviewing candidates who will not move forward. More in-depth searches run only after candidates clear earlier verification, creating a cleaner and more reliable pipeline.

Activus Connect, a remote-first business process outsourcing company running roughly 3,000 to 4,000 background checks a year, rebuilt its sequence around exactly this. Identity verification runs after application and live interview, and before anything else.

Some teams worry that added verification will hurt the candidate experience. But candidates also want confidence that real, qualified people are being considered fairly, especially as AI-generated applications become more convincing.

A short, clearly explained verification step can build trust when candidates understand why it is needed, how their data is protected, and what to expect from the process.

In fact, before Activus adopted automated identity verification, it tried solving the same problem itself by asking job applicants to go on camera and hold up an identification document. Drop-off ran up to roughly 85%. Candidates were being asked to share sensitive identification, on the spot, over a video with someone they had never met.

Whether verification builds trust or creates friction depends on three things: how much effort it requires, how clearly you explain its purpose, and how transparent you are about data security and results.

Bring fraud detection and screening into the same workflow within your ATS, HRIS, or HCM platform. That gives teams one place to review signals and results instead of piecing them together across separate tools.

41% of HR leaders named integrated fraud detection, verifications, and background checks in one progressive flow as a capability their program is missing in 2026.

When systems share data, teams can spot inconsistencies while a candidate is still in the hiring process and retain the records needed for reporting later.

HR teams are taking on more responsibility for fraud, often without more specialists or budget. Many programs still depend on individuals noticing problems, which becomes harder as hiring volume grows.

More training and careful manual review will not close the gap on their own. Teams also need detection systems that draw on fraud patterns seen across employers, data that no single employer can build alone.

That means shifting the primary fraud control from manual inspection to cross-employer data. For example, Checkr’s identity misuse detection flags candidates who provide a Social Security number or other deterministic PII belonging to another person, drawing on patterns found across relationships with more than 140,000 customers.

AI-powered screenings help teams spot risk earlier by surfacing signals and applying criteria consistently. It narrows the field to candidates who may need a closer look.

Each flag gives your team an insight to act on. Your team reviews the information, adds context, and makes the final decision. That’s where leaders want automation: supporting human judgment, not replacing it.

The capability leaders want most, automated cross-verification at 45%, is also the largest reported gap at 53%. They are not waiting for a new solution to be invented. They want to automate verification work they already know is necessary but cannot handle manually at their hiring volume.

Fraud prevention is already becoming a strategic priority: 51% of HR leaders say their organization treats it as a formal, distinct objective within its background check program, according to Checkr’s 2026 CHRO Insights Report. The next step is to give one person or team clear ownership and the support to move the work forward, then connect progress to metrics leaders already care about.

Shared contribution isn’t the problem. Fraud prevention is a shared effort across HR, security, legal, and IT. What matters is defining how those teams work together and empowering one function to lead.

Security can help assess threats, legal can advise on risk, and IT can support the systems involved. Because identity fraud enters through the hiring process, HR is well positioned to coordinate the response and keep the work moving.

Start with the metrics leadership already cares about. Quality of hire was the top metric HR leaders said they need to improve this year, named by 41% of respondents, and it ranked first across every industry surveyed. Fabricated credentials can directly undermine that metric. Connecting fraud prevention to quality of hire shows its value without adding another KPI.

This connection can also make budget conversations easier. If jurisdictional compliance and fraud prevention are funded separately, present them as two parts of the same hiring risk. A coordinated investment may be easier to support than a separate new budget request.

Teams making the most progress tend to do three things: give someone clear ownership, verify identity both before and after the offer, and automate reporting. You can start all three in a matter of weeks with the right verification and background check partner.