Hiring integrity stack — proving the applicant, the interviewee, and the hire are one person

On April 15, 2026, the Justice Department announced the sentencings of Kejia Wang and Zhenxing Wang for running “laptop farms” that placed North Korean IT workers on the payrolls of more than 100 U.S. companies, using the stolen identities of at least 80 U.S. persons and generating over $5 million for the DPRK. Every one of those companies ran a hiring process. Most of them ran background checks. What none of them had was a way to show that the person who submitted the application, the person who sat the interviews, and the person who received the laptop were the same human being.

That continuity is what this stack buys. It is four layers, and only three of them are software.

The shape: Greenhouse Real Talent (or Gem’s Fraud Detection Agent, depending on which ATS you already run) scores the application before a recruiter opens it, CLEAR identity verification inside the ATS binds a government ID and a live face to a named pipeline stage, Metaview records the interview so the assessed performance is attached to evidence rather than memory, and Checkr closes the loop post-offer with a report and a continuous check. The fourth layer is a written rubric and a stage rule, and it is the one that makes the other three defensible.

How the pieces fit

• Application scoring is the cheapest layer and it determines everything downstream. Greenhouse Fraud Detection, built on IPQS, analyzes phone number, email address, location, and IP address and returns three signal classes: identity-supporting signals (an established email account), high-risk signals (a data-center IP), and weak signals (a timezone that does not match the stated location). It sits in the Security screening tab of the candidate profile and in application review. Greenhouse’s own TA team published what this looked like on one machine-learning req: more than 35% of applicants carried high-risk signals, and 91% of the high-risk candidates its security team reviewed were confirmed fraudulent. Among weaker-signal candidates, 26% were confirmed — which is why that bucket is a review queue and not a filter.

• Identity verification is the only layer that proves a person, and it runs at one stage. Greenhouse partnered with CLEAR — announced June 3, 2025 — to put verification inside MyGreenhouse. CLEAR runs over 60 security signals including government-ID authentication, a selfie check with liveness detection, and device and network metadata; Greenhouse then cross-checks the result against the application’s last name, email, and phone. Verified candidates are marked CLEAR verified for the stage in which verification was completed, and you can filter the pipeline on that status. CLEAR does not store candidate data in Greenhouse — the identity record stays with CLEAR, which matters for the biometric exposure below.

• The recorder ties the verified identity to the assessed performance. Metaview Notetaker is $60/user/month on Pro for unlimited calls, with a free tier capped at 25 calls a month. The point is not the summary — it is that a proxy interviewer, a second voice off-camera, or answers arriving on a two-second delay leave traces in a recording that they never leave in a scorecard.

• Checkr is post-offer and post-hire, not pre-interview. Published pricing: Basic $29.99/report with identity verification a $4.99/check add-on, Essential $59.99/report with identity verification and unlimited county criminal search bundled, Complete $94.99/report. Continuous Criminal Search is $1.70 per individual per month. Essential is the default for a remote knowledge-work hire; the continuous check catches what changes after the report clears.

• The rubric and the stage rule are components, not paperwork. Structured interviewing is what makes a recorded interview comparable evidence rather than eight hours of video. A written stage rule — every candidate on this requisition verifies at the same stage — keeps the identity layer from becoming a disparate-treatment claim.

Named handoffs

1. Application submitted → fraud report attached. On Greenhouse Pro the report runs automatically; on Plus a recruiter initiates it. The flag lands on the profile with the underlying signals visible. Nothing auto-rejects — Greenhouse states outright that fraud signals are not a definitive assessment of a candidate’s authenticity, and a human resolves each one.
2. Candidate advances past screen → CLEAR verification requested in MyGreenhouse. Candidate completes a selfie and ID check; the stamp attaches to that stage; recruiters filter the pipeline by verified status before scheduling onsites.
3. Interview starts → Metaview records against the loop’s rubric. The transcript and scorecard land on the same candidate record that carries the verification stamp.
4. Offer accepted → Checkr Essential runs. Identity verification inside the report is a second, independent check against a different data source than CLEAR used.
5. Hire starts → Continuous Criminal Search runs monthly at $1.70/individual, and the device shipping address is checked against the address in the verified identity record. The DOJ laptop-farm cases turned on that mismatch.

The ATS fork — read this before you buy anything

Gem shipped its AI Fraud Detection Agent (announced December 16, 2025, early access February 2026, generally available April 21, 2026), powered by Tofu and priced per application with per-job controls. It evaluates six signal families — resume metadata, LinkedIn profile age and activity, email, phone, cross-source person verification, and IP/device data — and returns high/medium/low risk with a plain-language rationale, at a claimed 90%+ accuracy across Tofu’s 5-million-applicant base.

The constraint that decides the stack: Gem’s fraud agent runs on Gem’s native ATS, with Greenhouse and Workday shops directed to sales. So the rule is not which agent is better. It is:

• Already on Greenhouse Plus or Pro → Real Talent. Fraud Detection and CLEAR identity verification both require Plus or Pro; Pro also runs the reports automatically instead of on request.
• Already on Gem’s all-in-one ATS → the Fraud Detection Agent, and skip Real Talent entirely.
• On neither, and choosing an ATS anyway → Gem publishes startup pricing at $130/month (annual, 1-10 FTE) and gives companies under 30 employees six months free, which is the only published entry price in this stack. That is an ATS decision that happens to include fraud screening, not a fraud-screening decision.

Do not migrate an ATS to get a fraud agent. The screening layer is the cheapest part of this stack and the ATS is the most expensive thing to move.

Cost baseline

For a 200-person company hiring 50 people a year with five recruiters on remote roles, the priceable half of the stack:

• Metaview Notetaker Pro, 5 seats: $3,600/year
• Checkr Essential, 50 reports: ~$3,000/year (Basic + the $4.99 ID add-on is $34.98 per report if you do not need unlimited county search)
• Continuous Criminal Search across 200 employees: ~$4,080/year

That is roughly $10-11K/year, before the ATS. Greenhouse does not publish tier pricing, and the Plus-or-Pro requirement is the unpriced variable that dominates the total — if you are on the entry tier today, price the upgrade before you price anything else here.

Variations and when to swap

• BrightHire instead of Metaview. Zoom closed its BrightHire acquisition in December 2025 and runs it as a standalone brand inside Zoom Workplace. Swap if you interview on Zoom and want the recorder in the meeting layer rather than bolted alongside it. Do not swap if your loops run on Google Meet.
• Add proctored assessment for engineering roles. HackerRank or CodeSignal address a different failure than this stack does — answer assistance by a real, correctly-identified candidate. Add them when the risk is cheating; they do nothing about a stolen identity. See the technical hiring stack.
• Drop the continuous check for contractor-heavy or short-tenure populations where the monthly per-head fee outruns the average engagement length.

What this stack does not replace

• It is not an interview-quality stack. Recording for evidence and recording for coaching are different jobs; the interview intelligence stack covers scoring, debriefs, and interviewer calibration.
• It is not an assessment stack. Nothing here measures whether the verified person can do the work.
• It does not decide. Every layer produces signals that a named human resolves. A stack that auto-rejects on a fraud flag is a stack that rejects candidates on VPNs.
• It does not cover work authorization. I-9 and E-Verify are a separate obligation with separate timing rules, and a CLEAR stamp is not a substitute.
• It does not cover IT onboarding. The laptop-farm scheme in the DOJ case survived hiring processes and failed at the device-and-network layer. Shipping-address verification, no-remote-desktop-on-company-hardware, and hardware-key enrollment belong to security, not recruiting.

Watch-outs, each with a guard

• Biometric verification is regulated, and Illinois is the live risk. CLEAR’s selfie-with-liveness collects a biometric identifier, which puts Illinois BIPA (740 ILCS 14) in play for Illinois candidates: written notice and a written release before collection, plus a retention schedule. The August 2024 amendment limits recovery to a single claim per person per collection method, which caps exposure without removing it. Guard: turn verification on at one named stage for every candidate on the requisition, keep the notice and release in the candidate record, and rely on the fact that the identity data stays with CLEAR rather than in your ATS.
• Selective verification is a discrimination claim waiting to happen. Guard: the stage rule is written and applies per requisition. Never trigger a check because a recruiter found a name or an accent suspicious.
• Checkr output is a consumer report under the FCRA. That means a standalone disclosure and authorization, a pre-adverse-action notice with a copy of the report and the summary of rights, and a waiting period before the final decision. Guard: run rejections through Checkr’s adverse-action flow, and never mark the candidate rejected in the ATS first — the ATS status is the paper trail that contradicts you.
• High-risk signals catch legitimate candidates. Data-center IPs mean VPNs, and a relocating candidate’s timezone will not match. The 26% confirmation rate on weak signals is the number to internalize. Guard: require corroboration from a second signal class before any action, and treat weak signals as a review queue.
• Verification stamps are per-stage, and a stamp at screen says nothing about who joins the onsite. Guard: for fully remote roles with system access, re-verify at the final round, and have the recorder running for it.

Match rules

Right pick when: hiring is fully remote; the roles carry system, code, or financial access; application volume per requisition runs into the hundreds; and you are already on Greenhouse Plus/Pro or Gem’s ATS. It is strongest on engineering, IT, and finance reqs at companies between roughly 100 and 1,000 people — large enough that recruiters cannot know every candidate, small enough that there is no internal fraud team.

Wrong pick when: hiring is in-person and hourly — the high-volume recruiting stack fits that motion, and physical presence solves identity for free. Also wrong when an agency owns sourcing and screening end to end, when you make fewer than about ten hires a year, or when your ATS sits below the tier that gates the screening layer and the upgrade costs more than the fraud does.

If you can only do one thing: turn on application-layer fraud scoring and read AI interview fraud before you write the stage rule. It is the cheapest layer, it runs before any recruiter time is spent, and Greenhouse’s own pilot suggests it is where the volume actually is.