EU AI Act Compliance
How Cheqpoint satisfies the human oversight and transparency requirements for high-risk AI systems under Regulation (EU) 2024/1689. Includes article-by-article mapping, implementation guide, industry playbooks, and how to generate a regulator-ready compliance report.
What is the EU AI Act and when does it apply?
The EU Artificial Intelligence Act (Regulation (EU) 2024/1689) entered into force on 1 August 2024. It is the world's first comprehensive AI law and applies to any organisation that develops, imports, or deploys AI systems in the EU — regardless of where the organisation is headquartered.
The Act uses a risk-tiered approach. Most AI systems are low-risk and face minimal obligations. However, AI systems listed in Annex III are classified as high-risk and carry substantial compliance requirements — including mandatory human oversight (Article 14), transparency (Article 13), risk management (Article 9), and record-keeping (Article 12).
Who counts as a “deployer” vs a “provider”?
The Act distinguishes between providers (organisations that develop and place AI systems on the market) and deployers (organisations that use AI systems in their own operations). Most teams using Cheqpoint are deployers: they are running AI agents built on third-party models (OpenAI, Anthropic, Google) and deploying them against real business operations.
Deployers of high-risk AI are required — under Article 14 — to implement human oversight measures and maintain records showing that oversight operated. Cheqpoint is the technical implementation of that requirement.
Annex III — Is your AI system high-risk?
The following categories from Annex III are most relevant to teams using AI agents for real-world business operations:
| Annex III Category | Example AI actions |
|---|---|
| 5(b) — Creditworthiness / credit scoring | Credit limit changes, loan approvals, affordability assessments |
| 5(c) — Life & health insurance pricing | AI-driven underwriting decisions, policy acceptance, premium setting |
| 4(a) — Recruitment & HR decisions | Candidate shortlisting, performance scoring, promotion recommendations |
| 2(a) — Safety-critical infrastructure | AI actions on water, energy, transport, or digital infrastructure systems |
| 3 — Education & vocational training | AI-generated assessments, access decisions, grading |
| 6 — Law enforcement & evidence | AI-flagged fraud, risk profiling, investigation prioritisation |
| 7 — Migration, asylum, border control | Automated eligibility decisions, document verification |
Article-by-article compliance map
The table below maps each relevant EU AI Act article to the specific Cheqpoint feature that satisfies it, with links to where you configure it in the dashboard.
| Article | Requirement | Cheqpoint feature | Where to configure |
|---|---|---|---|
| Art. 9 | Risk management system — identify, analyse, and mitigate risks throughout the AI system lifecycle | Risk scoring per request (0–1 float), automatic routing by risk level, auto-approval rules for low-risk actions | Rules → Risk & Policies |
| Art. 12 | Record-keeping — automatically log events during operation of the high-risk AI system | Tamper-evident audit log of every request, decision, actor, payload, and timestamp. CSV export available. | Audit Log |
| Art. 13 | Transparency — enable deployers and users to understand the AI system's outputs and make informed decisions | Request detail shows action type, AI confidence score, risk score, full payload, and reason code. Reviewers see both Simple and Technical views. | Approval Inbox (Technical view) |
| Art. 14 | Human oversight — allow natural persons to monitor, understand, override, and intervene in AI outputs | Approve / Decline / Modify on every request. Kill switch to pause any AI Assistant instantly. No action executes without a human decision (unless explicitly whitelisted by policy). | Approval Inbox, AI Assistants |
| Art. 14(4) | Ability to decide not to use the AI system or disregard its output | Reviewers can decline any request regardless of AI recommendation or confidence score. Modified decisions create a separate audit entry. | Approval Inbox → Decline / Modify |
| Art. 17 | Quality management system — policies, procedures, and oversight structures for AI governance | Rules engine, Review Groups (routing by team/expertise), escalation policies, SLA targets, and notification channels | Rules, Review Groups, Settings |
| Art. 72 | Post-market monitoring — serious incident reporting and ongoing performance observation | Analytics dashboard (approval rates, response times, agent volumes, SLA compliance), anomaly visibility via audit log | Analytics, Audit Log, Compliance Report |
Article 14 — Human Oversight in detail
“High-risk AI systems shall be designed and developed in such a way, including with appropriate human-machine interface tools, that they can be effectively overseen by natural persons during the period in which the AI system is in use.”
Article 14 breaks down into four specific capabilities that deployers must implement. Here is how Cheqpoint satisfies each one:
Implementation guide — 5 steps to Article 14 compliance
Follow these steps to configure Cheqpoint as your Article 14 compliance layer. This takes approximately 30–60 minutes for a development team already running AI agents.
Code example — Python SDK (fintech: credit decision)
from cheqpoint import Cheqpoint
cp = Cheqpoint(api_key="cq_live_...")
# Article 14: execution is blocked until a human reviewer decides
result = cp.request_approval(
action="credit_limit_change",
summary="Increase credit limit: £5,000 → £8,000 for customer #C-00412",
details={
"customer_id": "C-00412",
"current_limit": 5000,
"requested_limit": 8000,
"credit_score": 742,
"affordability_ratio": 0.31,
"ai_recommendation": "approve",
},
risk_score=0.68, # 0.0 (low) – 1.0 (high)
timeout=300, # seconds to wait for human decision
)
if result.approved:
apply_credit_increase(result.modified_details or result.details)
elif result.declined:
notify_customer_declined(result.decision_note)
Code example — Node.js SDK (fintech: refund approval)
import { Cheqpoint } from "@cheqpoint/sdk";
const cp = new Cheqpoint({ apiKey: "cq_live_..." });
// Article 14: human must review before refund executes
const result = await cp.requestApproval({
action: "process_refund",
summary: "Refund £1,240 to customer Sarah M. — Order #ORD-99812",
details: {
orderId: "ORD-99812",
customerId: "cust_Sm42",
refundAmount: 1240,
currency: "GBP",
reason: "Item not received",
agentConfidence: 0.91,
},
riskScore: 0.55,
timeout: 180,
});
if (result.approved) {
await stripe.refunds.create({ payment_intent: order.paymentIntentId });
}
Industry playbooks
Below are the key action types for each regulated industry that should route through Cheqpoint to satisfy Article 14. Use these as a starting point when configuring your AI Assistants.
- →Credit limit changes and loan approvals
- →Refund and chargeback decisions above £/€ threshold
- →Account access changes (password resets, MFA bypass)
- →AML or fraud flag overrides
- →Transaction limit modifications
- →Account closures or suspensions
- →Bulk data exports of customer financial data
- →Claims approval and payout decisions
- →Underwriting acceptance or rejection
- →Premium adjustment decisions
- →Policy cancellations or non-renewals
- →Fraud flag decisions on claims
- →High-value claim escalations
- →Clinical decision support recommendations
- →Prescription generation or modification suggestions
- →Patient record access by AI agents
- →Treatment pathway recommendations
- →Triage priority assignments
- →Diagnostic output requiring clinical sign-off
- →Candidate shortlisting and screening decisions
- →Automated interview scoring
- →Salary band recommendations
- →Performance review flags
- →Promotion or termination recommendations
- →Background check processing
- →Contract execution decisions
- →Regulatory filing submissions
- →Compliance flag resolutions
- →Sanctions screening overrides
- →Data subject request responses
- →Litigation hold actions
- →Large refund decisions (set your own threshold)
- →Account fraud suspension decisions
- →Bulk promotional pricing changes
- →Supplier payment approvals
- →Inventory write-offs
- →Customer data deletion requests
The Compliance Report — evidence for regulators
When a regulator, auditor, or procurement team asks you to demonstrate Article 14 compliance, Cheqpoint generates the evidence automatically. Go to Compliance Report in the dashboard sidebar.
The report shows, for any selected period:
- ✓Total AI requests submitted for review (excluding test/sandbox traffic)
- ✓Human decisions vs auto-approved (within policy rules)
- ✓Approved / Declined / Modified breakdown with percentages
- ✓SLA compliance rate (decisions within target response time)
- ✓Average, P50, and P95 response times
- ✓Risk profile (high / medium / low breakdown)
- ✓Per-AI-Assistant activity and action types
- ✓Per-reviewer activity and individual response times
- ✓Auto-generated Article 14 compliance statement naming your workspace, period, and reviewer count
- ✓Document reference number (CHQ-XXXXXX-YYYYMMDD) for your audit file
Click Print / Export PDF to produce a print-optimised document you can share with internal audit, external auditors, or directly with your regulator. The sidebar and controls are hidden automatically in the printed output.
Pre-launch compliance checklist
Use this checklist before going live with AI agents in a regulated context: