Build a Fraud Feedback Loop Your ATS Can Actually Audit

Recommendation: run fraud response like an incident loop with evidence packs, not like one-off investigations. If a candidate clears your funnel and later turns out to be a false identity, the damage is not just the miss. It is the absence of a defensible narrative: who approved the candidate, what evidence existed at the time, and what controls were executed before privileged steps. Checkr reports 31% of hiring managers say they have interviewed a candidate who later turned out to be using a false identity. That volume is enough to overwhelm manual review unless you instrument a feedback loop with SLAs and clear owners. Replacement cost is a budget event. SHRM estimates replacing an employee can cost 50-200% of annual salary depending on role. Late-stage fraud multiplies that cost by adding cycle-time waste and offer fallout.

Recommendation: stop trying to "connect" siloed tools with spreadsheets. You need an ATS-anchored audit trail with immutable evidence references. Legacy ATS workflows optimize for moving candidates forward, not for capturing chain-of-custody. Verification happens after access, assessments log activity but not standardized rubrics, and background checks arrive as PDFs that do not map to hiring-stage events. The common failure modes are operational: sequential checks that slow everything down, no unified evidence packs, no review-bound SLAs, and shadow workflows that turn labeling into chat messages. If it is not logged, it is not defensible.

Recommendation: assign owners by control type and define one system of record for each artifact class. Recruiting Ops owns the workflow and SLA mechanics. Security owns policy, thresholds, and audit rules. Hiring Managers own rubric discipline and timely notes. Analytics owns dashboards and drift monitoring. Sources of truth must be explicit: ATS for stage history and decision narrative; verification and assessment layers for evidence artifacts; and a case queue for labeling decisions and appeals, all linked by evidence pack ID.

Recommendation: design the loop as Detect - Triage - Confirm - Learn - Deploy - Monitor, with timestamps at every hop. Identity gating before access reduces the blast radius. Event-based triggers reduce reviewer fatigue by routing only candidates with concrete anomalies. Automated evidence capture produces a defensible record. Dashboards surface where SLA breaches and fraud leakage occur. Standardized rubrics prevent unstructured notes from becoming your only evidence.

IntegrityLens AI provides an ATS plus identity and assessment controls that keep the fraud loop closed and auditable, not scattered. It enforces identity verification before access, captures fraud signals as timestamped events, and produces immutable evidence packs linked to ATS-anchored audit trails. It supports 24/7 AI screening interviews with structured rubrics and technical assessments with execution telemetry, so the feedback loop trains on evidence, not vibes.

Recommendation: treat each suspected fraud case like a ticket with an SLA, an owner, and an evidence pack ID. Run the loop weekly for dataset cuts and monthly for model or policy updates. If you cannot commit to that cadence, your loop will silently rot. Below is a policy template that Recruiting Ops can operationalize and Security can audit.