Checkr
Checkr is an FCRA-regulated background screening platform that uses machine learning to parse, classify and standardize criminal, employment, education and motor-vehicle records, and to route them through customer-configured adjudication rulesets that flag candidates as eligible, review or escalated for employment decisions.
HireAIScore rates Checkr 54 out of 100 (grade F, Substantial gaps) under rubric v1.0, last reviewed August 2, 2026. Checkr ranks 23 of 92 vendors rated in Screening AI, against a category average of 47. That score is drawn from 28 evidence items across 7 rubric criteria for Checkr — 24 with a cited source, 6 recording that nothing was located.
§ 01 - Company facts
- Legal name
- Checkr, Inc.
- Founded
- 2014
- Headquarters
- United States · US
- Pricing tier
- Mid
- Market side
- Employer-side (AEDT)
- Categories
- Screening
- Website
- checkr.com
These are company details, not findings. They are editable by a verified representative and carry no weight in the score, which is built only from the cited evidence below.
§ 02 - Score breakdown
§ Score breakdown
Category scoring
Weighted contribution shown to the right of each bar.
- 01
Article 11 Technical Documentation
Weight 20%70
+14.0 · category avg 50
- 02
Bias Audit Transparency
Weight 18%35
+6.3 · category avg 46
- 03
FRIA Support
Weight 15%32
+4.8 · category avg 32
- 04
Data Governance Disclosure
Weight 15%62
+9.3 · category avg 54
- 05
Human Oversight Design
Weight 12%66
+7.9 · category avg 56
- 06
Post-Market Monitoring
Weight 12%50
+6.0 · category avg 40
- 07
Customer Documentation
Weight 8%68
+5.4 · category avg 58
Category avg is the mean raw score on that criterion across the 92 Screening AI vendors in scope of this rubric, this one included.
§ 03 - Strongest · weakest
Strongest category
Article 11 Technical Documentation
Raw score 70 · contributes 14.0 to total.
70 against a 50 category average
Weakest category
FRIA Support
Raw score 32 · contributes 4.8 to total.
32 against a 32 category average
§ 04 - Cited evidence
Download diligence record→§ Evidence
Cited per category
Every score is backed by at least one cited piece of evidence.
Evidence ledger
- Items
- 28
- Documentation
- 18
- Audit report
- 2
- Public statement
- 2
- Absence
- 6
- With a source URL
- 24 of 28
- Source hostnames
- 4
- Fewest items
- 3
- FRIA Support
These figures measure how thoroughly Checkr was reviewed, not how Checkr performed — an absence row, recording that nothing was located, is counted like any other item.
Article 11 Technical Documentation
4 items70
- Audit reportCaptured Aug 2, 2026
Checkr announced ISO/IEC 42001 certification on 22 October 2025, audited by accredited third party A-LIGN, describing itself as the first background check provider to achieve the AI management system standard and committing to provide 'extensive AI systems documentation' and demonstrate continuous improvement in AI controls and risk management.
https://checkr.com/resources/articles/iso-42001-artificial-intelligence-certification
- DocumentationCaptured Aug 2, 2026
Checkr's AI technology page enumerates named model components - charge classifier, charge explainer, name matcher, role matcher, document inspector and income comparison - and states ISO 42001 is 'an independent validation that Checkr AI meets international standards for accuracy, security, and human oversight', but publishes no model architecture, accuracy metrics or limitations.
- DocumentationCaptured Aug 2, 2026
Checkr's public SafeBase trust portal lists ISO/IEC 42001:2023 among its certifications and carries an AI section covering AI Security, AI Monitoring and AI Risk Management, though the underlying ISO 42001 certificate and statement of applicability are not among the publicly downloadable documents.
- AbsenceCaptured Aug 2, 2026
No model card, system card, Annex IV technical documentation pack or standalone explainability statement was found across checkr.com/our-technology, checkr.com/platform/foundation, checkr.com/resources, security.checkr.com or docs.checkr.com.
Bias Audit Transparency
4 items35
- AbsenceCaptured Aug 2, 2026
No NYC LL 144 bias audit, independent fairness audit, or demographic impact-ratio analysis for Checkr was found via targeted searches for Checkr alongside BABL AI, Warden AI, Holistic AI, DCI, ORCAA and Credo AI, nor on checkr.com, security.checkr.com or in any academic audit literature.
- Public statementCaptured Aug 2, 2026
The Assess product page asserts that with formalized adjudication rulesets 'the risk of bias is drastically reduced by 90%', a quantified fairness claim published with no supporting methodology, sample, demographic breakdown or auditor attribution.
- Audit reportCaptured Aug 2, 2026
The A-LIGN ISO 42001 audit is a governance and management-system assessment covering AI controls and risk management processes, and Checkr's announcement asserts fairness in general terms but discloses no bias testing methodology, fairness metrics or demographic results.
https://checkr.com/resources/articles/iso-42001-artificial-intelligence-certification
- AbsenceCaptured Aug 2, 2026
Checkr's own compliance overview describes adjudication filters as reducing bias by removing irrelevant charges from view, but contains no mention of AEDT regulation, bias auditing, or any measured disparate-impact analysis of its ML outputs.
https://checkr.com/resources/articles/compliance-made-easier-with-checkr
FRIA Support
3 items32
- AbsenceCaptured Aug 2, 2026
No Fundamental Rights Impact Assessment template, Article 27 guidance, EU AI Act deployer obligation guidance, or high-risk role-allocation statement was found on checkr.com, checkr.com/legal, checkr.com/resources, security.checkr.com or docs.checkr.com; the phrase 'EU AI Act' does not appear on any Checkr property located.
- DocumentationCaptured Aug 2, 2026
Checkr's publicly posted Data Protection Addendum (last updated 1 March 2025) covers GDPR/UK GDPR/Swiss processor duties, Standard Contractual Clauses, subprocessor notice and Annex III security measures, but contains no clause addressing AI systems, algorithmic processing or automated decision-making that a deployer could use to scope a FRIA.
- DocumentationCaptured Aug 2, 2026
The SafeBase trust portal provides a partial self-service trust package including an AI Risk Management section, but its materials are security- and privacy-oriented and most substantive documents require an NDA, offering no fundamental-rights or deployer-obligation assessment content.
Data Governance Disclosure
4 items62
- DocumentationCaptured Aug 2, 2026
Checkr's trust portal lists ISO/IEC 27001, ISO/IEC 42001:2023, SOC 2 Type II, SOC 3, GDPR, CCPA, CPRA, PIPEDA and Privacy Shield, and makes the ISO 27001 certificate, a security whitepaper and web app/API penetration test reports publicly downloadable, with SOC 2/SOC 3 reports and the ISO 27001 statement of applicability gated behind NDA.
- DocumentationCaptured Aug 2, 2026
The public DPA specifies controller/processor roles, a publicly maintained subprocessor list with 10-day advance change notice and objection rights, and Annex III technical measures including TLS 1.2+ in transit, AES-256 at rest, MFA, role-based access control and annual SOC 2 Type II audits.
- DocumentationCaptured Aug 2, 2026
Checkr describes its models as 'trained on millions of verified records, continuously refined through a human-in-the-loop model' drawn from 'hundreds of fragmented sources', but publishes no exclusion list, no statement on demographic attributes in training data, and no evaluation benchmarks or retraining schedule.
- DocumentationCaptured Aug 2, 2026
Checkr's trust and security page documents Data Privacy Framework certification for EU-US transfers, FCRA/CCPA/GDPR/PIPEDA adherence, candidate self-service data access and deletion via the Candidate Portal, and an explicit statement that it does not sell personal information.
Human Oversight Design
5 items66
- DocumentationCaptured Aug 2, 2026
Checkr frames its AI under an 'AI you can trust' section stating 'Your team makes the calls', and ships a charge explainer that generates a 'helpful overview of the charge, its severity, and relevant statutes' as in-interface explanation of each classified record.
- DocumentationCaptured Aug 2, 2026
Assess is explicitly decision-support rather than auto-adjudication, reducing manual review by 40–85% depending on tier while leaving humans to decide, with customer-configured rulesets offering up to 235 granular filters and unlimited rulesets at Premium so the employer defines the criteria rather than the model.
- DocumentationCaptured Aug 2, 2026
Checkr operates a location-aware compliance engine that automatically filters records by local restrictions (a per-jurisdiction control), automates pre- and post-adverse action notices with mandatory waiting periods and in-portal candidate disputes, and offers Candidate Stories so applicants can add context supporting an EEOC individualized assessment.
https://checkr.com/resources/articles/compliance-made-easier-with-checkr
- DocumentationCaptured Aug 2, 2026
Checkr states its compliance tools 'combine the power of technology with the confidence of human review' and that a Quality Assurance team manually reviews certain reports before completion, backed by routine audits, with legal experts continuously monitoring legislative changes.
- Public statementCaptured Aug 2, 2026
Checkr articulates auditability as a principle -'Every decision needs to be explainable, especially in regulated industries'- and acknowledges candidate transparency gaps in its own survey data, though it publishes no corresponding candidate-facing AI disclosure mechanism.
https://checkr.com/resources/articles/trust-humans-with-checkr-ai
Post-Market Monitoring
4 items50
- DocumentationCaptured Aug 2, 2026
Checkr operates a public status page monitoring 18+ components including API, webhooks, candidate portal and named ATS integrations, showing dated incident history (e.g. SSN trace delays on 31 July 2026 and Illinois MVR turnaround delays on 30 July 2026) with email, SMS, Slack and Atom/RSS subscription options.
- DocumentationCaptured Aug 2, 2026
The trust portal carries an AI section covering AI Monitoring and AI Risk Management alongside publicly downloadable external and internal penetration test reports, and posts dated updates on new SOC 2 Type II reports and ISO 27001 renewals.
- DocumentationCaptured Aug 2, 2026
Checkr states it conducts 'regular application and infrastructure security vulnerability and penetration testing' using both internal staff and third-party specialists, though no dedicated vulnerability disclosure policy, security.txt or bug bounty programme was located.
- AbsenceCaptured Aug 2, 2026
Checkr's public API documentation contains no changelog or release-notes section, and no model-update log, retraining notice, model performance dashboard or AI-specific incident channel was found on any Checkr property.
Customer Documentation
4 items68
- DocumentationCaptured Aug 2, 2026
Checkr maintains public, ungated API documentation covering credentialing, authentication, candidate and report creation, webhook events and security, and adverse action workflows, including the Assess eligible/review/escalated assessment values returned on completed reports.
- DocumentationCaptured Aug 2, 2026
A full Data Protection Addendum is published openly at checkr.com/legal/dpa rather than being gated behind sales, covering processor duties, SCC modules, the UK Addendum, Swiss modifications and subprocessor governance.
- DocumentationCaptured Aug 2, 2026
Checkr publishes transparent per-report pricing ($29.99 Basic, $59.99 Essential, $94.99 Complete, plus custom enterprise) with itemized add-on costs, which is unusual disclosure for the screening category.
- AbsenceCaptured Aug 2, 2026
No AI-regulation deployer guidance was found - searches across checkr.com resources and blog surfaced no content on NYC Local Law 144, the EU AI Act, Colorado SB 205 or Illinois HB 3773 AI disclosure duties, despite Checkr customers now carrying those obligations.
§ 05 - Editorial notes
Company overview
Checkr, founded in 2014 by Daniel Yanisse and Jonathan Perichon and headquartered in San Francisco, is a consumer reporting agency and background screening platform serving gig, staffing and enterprise employers. Its products span criminal, employment, education, MVR/DOT, drug and international screening, wrapped in an API-first platform with pre-built integrations into most major ATS vendors. The AI layer is unusually well-documented at the component level: a proprietary charge classifier that categorizes criminal charges across fragmented US jurisdictions, a charge explainer that renders severity and statutes in plain language, name and role matchers, a document inspector for forgery signals, and an ML turnaround-time predictor. Its Assess product layers customer-defined rulesets (up to 235 filters at Premium tier) on top of the classified records, reducing manual review by up to 85% while returning advisory eligible/review/escalated values rather than final decisions. Pricing is usage-based and publicly listed at $29.99–$94.99 per report with custom enterprise tiers.
Regulatory exposure
Checkr sits in an unusual regulatory position: it is primarily governed by the FCRA as a consumer reporting agency, not as a classic automated employment decision tool, and NYC LL 144 places the compliance duty on the employer rather than the CRA. But the honest reading is that its ML materially influences employment decisions - the charge classifier determines how a record is characterized, and Assess rulesets convert that characterization into an eligibility signal, which is squarely within the kind of candidate evaluation the EU AI Act treats as high-risk under Annex III. Checkr's strongest compliance asset is ISO/IEC 42001:2023 certification, audited by A-LIGN and announced in October 2025, making it the first background screener certified to the AI management system standard; that maps closely to EU AI Act Article 17 quality-management expectations. Against that, there is no published bias audit of any kind, no demographic impact-ratio analysis, no FRIA or deployer guidance, and no mention anywhere on Checkr's site of the EU AI Act, LL 144, Colorado SB 205 or Illinois HB 3773. The Assess page's claim that 'the risk of bias is drastically reduced by 90%' is a marketing figure with no published methodology behind it. Accuracy risk is also live rather than theoretical: Davis v. Checkr Inc. (S.D. Fla., 0:26-cv-60088, filed January 2026) alleges Checkr failed to maintain reasonable procedures to assure maximum possible accuracy and mismatched criminal records to the wrong consumer - precisely the failure mode an identity-matching model creates.
Path to a higher score
The single highest-value move is publishing an independent demographic bias audit of the charge classifier and Assess eligibility outputs - impact ratios by race/ethnicity and sex, ideally intersectional, from a named auditor with a date. Because Checkr's data flows disproportionately affect populations with criminal records, this would be the most consequential fairness disclosure any screening vendor could make, and the 90% bias-reduction claim needs methodology behind it or should be retired. Second, publish an Article 11-style technical pack or model cards for the named components (charge classifier, name matcher, document inspector) with accuracy metrics, known limitations and demographic performance breakdowns; the ISO 42001 certificate proves a process exists but discloses none of its contents. Third, produce explicit deployer guidance - a FRIA template, an EU AI Act high-risk role allocation statement, and per-jurisdiction notes for LL 144, Colorado and Illinois HB 3773 disclosure duties - since Checkr's customers now carry those obligations and get no help with them today. Fourth, add an AI-specific surface to post-market monitoring: a model-update changelog and published drift or fairness monitoring alongside the existing operational status page. Finally, make the ISO 42001 certificate and its statement of applicability publicly downloadable rather than badge-only.
§ Regulatory frame
What applies to screening ai.
Treated as high-risk under Annex III §4 when the screening output is decisive. EU AI Act Article 13 transparency obligations apply; deployers must give candidates a way to contest.
§ Compare
Build any comparison→Checkr against its nearest-scoring peers.
In Screening AI.
§ Others rated in Screening AI
All screening vendors→Ranked 23 of 92 by weighted total under rubric v1.0. The ordering is arithmetic on the rubric and carries no view on which tool suits a given hiring process.
- 20iCIMS55F
- 21Plum54F
- 22Metaview54F
- 23CheckrThis profile54F
- 24Bullhorn54F
- 25Codility54F
Conflicts of interest
No vendor pays for placement, scoring, or removal. Casework - the consulting firm that operates this directory - provides paid services to some vendors. Any active or recent (within 24 months) commercial relationship is disclosed on the affected vendor profile and the review is reassigned to an independent reviewer. See the full policy on About.
Casework has no commercial relationship with this vendor.