Model Validation Report Template (EU AI Act, Articles 15 and 10)

A model-validation report is the document that proves your high-risk system actually does what your technical documentation claims. It records the tests you ran, the metrics you measured, the thresholds you set, the data you measured against, and who signed it off. Like a model card, it is not a statutory term — the Act never says "validation report." But it is the single most useful evidence artefact for two of the heaviest high-risk requirements: Article 15 (accuracy, robustness and cybersecurity) and Article 10 (data and data governance). And it is the practice that fills the validation-and-testing part of the Annex IV technical documentation that Article 11 requires. The report is a practice; the underlying documentation duty is the law — keep the two distinct and keep them in sync.

This is a provider's artefact: Article 11, Article 15, and Article 10 are provider duties, owed by whoever develops the high-risk system and places it on the market under their own name.

Why a validation report exists

Article 15 requires high-risk systems to achieve an appropriate level of accuracy, robustness and cybersecurity and to perform consistently across their lifecycle. Article 10 requires the training, validation and testing data sets to meet quality criteria — relevant, representative, and to the extent possible free of errors and complete, with bias examined and mitigated. Annex IV then asks the technical documentation to describe the validation and testing procedures, the metrics used to measure accuracy, and the system's expected performance for specific persons or groups.

A regulator reading your file does not want the claim "the model is accurate." They want the evidence: which metric, what value, on what test set, against what threshold, reviewed by whom. The validation report is where that evidence lives in one readable place, cross-referenced to the Annex IV section it populates.

What the report has to show (and where it maps)

The Article 15 numbers, not adjectives

The discipline of a good validation report is that it replaces adjectives with numbers. The words "accurate" and "resilient" fail an audit; a metric, a value, a test set, and a threshold pass one. Article 15 specifically requires the relevant accuracy metrics to be declared in the Article 13 instructions for use — so the report is where you record the figures behind that declaration.

Capture, for each metric:

• The metric and why it fits the use — accuracy alone is misleading for imbalanced problems; precision, recall, F1, false-positive and false-negative rates, calibration, or AUC may matter more. State which and why.
• The value, with the test set named — the number is meaningless without the data it was measured on.
• The acceptance threshold and pass/fail — the line you set in advance, so the result is a verdict, not a description.
• The per-group breakdown — performance disaggregated across the populations the system affects. A single headline figure hides exactly the disparities Article 15 and Annex IV want surfaced, and that a later bias review will otherwise have to dig out the hard way.
• Robustness and cybersecurity results — behaviour under noisy, shifted, or adversarial inputs, and resilience to attempts to manipulate the system. Article 15 names all three — accuracy, robustness, cybersecurity — so a report that covers only accuracy is incomplete.

The Article 10 data-quality half

Validation is only as trustworthy as the data it ran on, which is why the report also evidences Article 10. Record the provenance, scope and representativeness of the training, validation and testing data; the preprocessing applied; and — the part regulators read closely — the bias examination: what you checked for, what you found, and how you mitigated it. Where the model touches special-category data (GDPR Article 9) note the lawful basis and the governance around it. The test set used for the Article 15 metrics should be described here too, so the accuracy numbers and the data they rest on sit in the same document.

The fields to capture

1. System identity and version — name, version, intended purpose, classification (Annex III area), and the role under which it is placed on the market.

2. Validation objective and scope — what this validation covers and what it deliberately does not.

3. Test data — sets used, provenance, representativeness, the link to the Article 10 data-governance record.

4. Accuracy metrics (Article 15) — metric, value, test set, threshold, pass/fail, per-group breakdown.

5. Robustness tests (Article 15) — performance under distribution shift, noise, edge cases, and stress; resilience to errors and faults.

6. Cybersecurity tests (Article 15) — resilience to data poisoning, model evasion, and attempts to alter behaviour; results and residual risk.

7. Bias examination (Article 10) — what was tested, findings, mitigations, residual disparities.

8. Known limitations and failure modes — where the model underperforms; foreseeable misuse; conditions outside validated scope.

9. Annex IV cross-reference — which Annex IV section each result populates, so the report and the full Article 11 documentation never drift apart.

10. Sign-off — reviewer, role, date, and approval — the human accountability the technical documentation needs to be credible.

Worked example: a medtech provider validating a triage model

Medrein BV, a Dutch medical-software provider with about 110 employees and roughly €28M turnover, develops a clinical-triage support model. Its validation report does not claim the model "performs well." It records sensitivity and specificity by age band and by presenting condition, against thresholds the clinical team set in advance — and it openly flags lower sensitivity on a rare paediatric presentation as a known limitation, with the mitigation (a mandatory clinician review) documented under Article 14 oversight elsewhere in the file. The Article 10 section describes the test set's provenance and the bias check across patient subgroups; the Article 15 section adds robustness results under noisy inputs and cybersecurity results against data-poisoning attempts. Every result is tagged to its Annex IV section, and the report is signed and dated by the validation lead. When the notified-body assessor reads the Article 11 file, the validation report is the evidence that the accuracy declared in the Article 13 instructions is real and measured, not asserted. (Medrein's model is a safety component of a medical device, so its high-risk route runs through MDR conformity with the 2 August 2028 product-embedded deadline; a stand-alone Annex III system would instead track the 2 December 2027 date — both set by the Digital Omnibus, in force since 27 July 2026.)

How Confir helps

Confir's data-and-technical-robustness assessment captures the Article 15 metrics, the test-set description, the robustness and cybersecurity results, and the Article 10 bias examination as structured fields, then assembles them into the Annex IV section of the Article 11 technical-documentation pack — so the validation report is a view onto the same record the assessor sees, not a separate document that goes stale. The engine is deterministic and rule-based: the same evidence inputs always map to the same documentation structure, and the rule that placed each field is human-readable.

Frequently Asked Questions

Is a model-validation report required by the EU AI Act?

Not by that name. The Act requires Article 11 technical documentation whose validation-and-testing content is set out in Annex IV, and it requires Article 15 accuracy/robustness/cybersecurity and Article 10 data quality to be demonstrable. A validation report is the practice that produces the evidence for those duties in one readable place. It supports compliance but does not replace the full technical documentation it feeds.

What metrics belong in a model-validation report?

The Article 15 metrics chosen to fit the use — accuracy is rarely enough on its own, so precision, recall, false-positive/false-negative rates, calibration or AUC often matter more — each with its value, the named test set, an acceptance threshold, and a per-group breakdown. Robustness results (under noise, shift, stress) and cybersecurity results (against poisoning and evasion) also belong, because Article 15 names all three properties, not just accuracy.

How does the validation report relate to Annex IV?

Annex IV is the legally required content of the Article 11 technical documentation, including the validation and testing procedures and the accuracy metrics used. The validation report is the artefact that produces that content in evidence form. Cross-reference each report section to its Annex IV theme so the readable report and the full technical file stay in sync and never contradict each other.

Who is responsible for the validation report?

The provider — whoever develops the high-risk system and places it on the market under their own name. Article 11, Article 15 and Article 10 are provider duties. A deployer consumes the resulting Article 13 instructions and accuracy declarations but does not author the technical documentation, although under Article 26 it keeps its own operating records and oversight evidence.

Does the report need a per-group performance breakdown?

Yes, where the system affects identifiable populations. Annex IV asks for expected accuracy for specific persons or groups, and Article 10 requires bias to be examined and mitigated. A single headline accuracy figure hides exactly the disparities these provisions target. Disaggregating performance across relevant subgroups is what turns a validation report from a claim into credible evidence — and surfaces problems before a bias review does.

When does the Article 11 documentation that the report feeds apply?

Stand-alone high-risk Annex III systems were originally due to apply from 2 August 2026, but the Digital Omnibus — Regulation (EU) 2026/1744, published in the Official Journal on 24 July 2026 and in force since 27 July 2026 — moved this to 2 December 2027, now the settled date. Product-embedded high-risk systems (Annex I) apply from 2 August 2028. The documentation must in any case exist before the system is placed on the market and be kept current.

Related guides

• Article 15 accuracy, robustness and cybersecurity — the requirement the report's metrics evidence
• Article 10 data and data governance — the data-quality duty the report's data section evidences
• Annex IV technical documentation explained — the nine areas the report helps populate
• Annex IV technical documentation template — the full file the report feeds
• AI model card template — the readable summary that sits alongside the validation report
• Bias assessment template — the Article 10 bias-examination practice in detail