Category: Compliance & Audit

Third-Party Audit

Also known as: Independent Audit, External Audit

Simply put

A third-party audit is an examination of an organization's processes, controls, or compliance conducted by an outside organization that is independent of the company being reviewed and its customers or suppliers. Because the auditor has no direct stake in the outcome, this type of audit is intended to provide objective, external validation. It contrasts with internal reviews a company performs on itself and with reviews a customer conducts of its own supplier.

Formal definition

As commonly defined across quality, security, and compliance contexts, a third-party audit is a systematic and independent examination conducted by an external organization that has no direct relationship with either the customer or the supplier being assessed. It typically evaluates an organization's internal controls, security practices, management systems, or compliance processes against established requirements or standards, and is often distinguished from first-party (internal, self-conducted) and second-party (customer-of-supplier) audits. The evidence draws primarily on quality management and cybersecurity settings; the specific scope, applicable criteria, and any certification outcome depend on the framework or standard being audited against, and the term's precise meaning in AI governance and model risk contexts is not established by the evidence provided here and should be confirmed against the relevant framework.

Why it matters

Third-party audits matter because independence is what gives an assessment credibility to parties who did not conduct it. When an organization reviews its own controls, the results may be sound but carry an inherent conflict of interest; an examination by an outside organization with no direct stake in the outcome is intended to provide objective, external validation. In AI governance and model risk contexts, this distinction supports the broader principle of independent challenge and oversight, where separation between those who build or operate a system and those who assess it strengthens the reliability of the conclusions.

The value of a third-party audit depends heavily on what it is auditing against and how its scope is defined. As commonly framed across quality management and cybersecurity settings, such audits evaluate controls, security practices, or compliance processes against established requirements or standards. The evidence here draws primarily from quality and security domains rather than from AI-specific frameworks, so professionals should be careful not to assume that a third-party audit automatically covers model-specific concerns such as validation, performance degradation, or fairness unless the audit's criteria explicitly include them.

It is also important to recognize the limits of what an audit accomplishes. A third-party audit provides point-in-time or periodic assurance against defined criteria; it reduces and helps manage risk rather than eliminating it, and it does not by itself substitute for ongoing internal monitoring or the organization's own accountability structures. Where the applicable standard, scope, or certification outcome is unclear, the meaning and weight of a given third-party audit should be confirmed against the specific framework being applied.

Who it's relevant to

Auditors and Assurance Professionals

Those conducting or commissioning independent examinations rely on the concept to establish that an assessment carries no direct stake in the outcome. They must define the criteria and scope precisely, since the audit's conclusions are only meaningful relative to the standard being assessed against.

Compliance Officers

Compliance teams use third-party audits as a source of external validation of controls and compliance processes. They should be careful to distinguish independent external audits from internal self-reviews and from customer reviews of suppliers, and to confirm what framework the audit applies.

Model Risk Managers

Model risk professionals may draw on third-party audits as one input supporting independent challenge and oversight. Because the term's precise meaning in model risk contexts is not settled by the evidence here, they should verify that any audit's scope actually addresses model-specific concerns rather than assuming general coverage.

Vendor and Third-Party Risk Managers

Professionals overseeing suppliers and vendors may request or review third-party audit results to assess an external organization's controls and security practices. Understanding the first-, second-, and third-party distinction helps them interpret whose independence and stake underlie a given report.

Inside Third-Party Audit

Independent Assessment Party

A third-party audit is conducted by an external entity that is organizationally and functionally independent of the party being assessed. This independence is central to the concept, distinguishing it from first-party (self) or second-party (customer or related-party) assessments.

Defined Scope and Criteria

The audit is bounded by an agreed scope and evaluated against stated criteria, which may include a standard, framework, contractual requirement, or regulatory expectation. Scope definition determines what aspects of an AI system, model, or governance program are examined and what is excluded.

Evidence-Based Evaluation

Auditors typically gather and examine documentation, controls, processes, and other evidence to form conclusions. In an AI governance and model risk context this can include model documentation, validation records, monitoring reports, and governance policies, subject to what the auditor is granted access to.

Audit Report or Attestation

The output is generally a report or attestation communicating findings, identified gaps, and conclusions relative to the criteria. The nature and assurance level of this output vary by engagement type and by any applicable standard, and should not be assumed to be a certification unless explicitly stated.

Relationship to Governance and MRM

Within the three lines of defense model as commonly framed, third-party audit sits outside the organization and is distinct from internal audit (often described as the third line). It can support both AI governance oversight and model risk management activities without substituting for either.

Common questions

Answers to the questions practitioners most commonly ask about Third-Party Audit.

Does a third-party audit certify that an AI system is safe or compliant?

Not in the way this is often assumed. A third-party audit typically provides an independent assessment against a defined scope, standard, or set of criteria at a point in time; it does not guarantee ongoing safety or blanket compliance. The value depends heavily on the criteria used, the scope agreed, and the evidence made available. An audit reduces uncertainty about specific claims but does not eliminate risk, and a favorable finding should not be read as a universal assurance that a system is 'safe' or 'compliant' across all contexts.

Is a third-party audit the same as independent model validation under model risk management?

They are related but distinct. Independent model validation, as commonly framed in model risk management, is an internal-to-the-organization function that is independent of model development but still sits within the institution's lines of defense. A third-party audit involves an external party outside the organization. The two can overlap in techniques and objectives, but conflating them risks assuming that an external audit satisfies validation obligations, or that internal validation delivers the independence associated with a third party. Which is expected depends on the applicable framework, sector, and internal policy.

How should scope be defined before engaging a third-party auditor?

Scope is typically defined by specifying the system or model boundaries, the criteria or standard against which the audit is conducted, the time period covered, and what is explicitly out of scope. Because 'audit' can mean very different things across contexts, documenting the objectives, the evidence to be examined, and any limitations in access up front helps prevent later disputes about what the findings do and do not cover.

What evidence and access do third-party auditors usually need?

This varies by audit type and criteria, but auditors commonly require access to documentation such as model development records, validation or testing results, data lineage information, governance and oversight records, and monitoring outputs. Where access to source code, data, or systems is restricted, those limitations are typically noted as constraints on the assurance provided. Determining the level of access in advance affects both the depth and the reliability of the resulting findings.

How does a third-party audit relate to the three lines of defense?

In many governance models, first-line functions own and manage risk, second-line functions provide oversight and challenge, and third-line internal audit provides independent assurance. A third-party audit generally sits outside these internal lines and can supplement, but does not automatically replace, third-line internal audit or second-line oversight. How an external audit fits alongside these functions depends on the organization's structure and any applicable regulatory or standards expectations.

How often should third-party audits be conducted?

There is no single required frequency across all contexts. Cadence is often driven by factors such as the inherent risk of the system, material changes to the model or its use, contractual or regulatory expectations where they apply, and the results of prior audits. Because an audit reflects a point in time, organizations typically pair periodic third-party audits with ongoing internal monitoring rather than relying on the audit alone.

Common misconceptions

A third-party audit certifies that an AI system is safe, compliant, or free of risk.

An audit typically provides assessment against defined criteria at a point in time and within a stated scope. It reduces uncertainty and surfaces gaps, but does not eliminate model risk or guarantee ongoing compliance. Whether an engagement results in a formal certification depends on the specific standard and engagement type.

Third-party audit is interchangeable with internal audit or model validation.

These are distinct. Internal audit is typically an internal, independent function (often the third line of defense), while a third-party audit is performed by an external entity. Model validation is a model risk management activity focused on assessing whether a model performs as intended. An external audit may review these functions but does not replace them.

All third-party audits assess against the same universal standard.

Audit criteria vary by jurisdiction, sector, and the framework or standard selected for the engagement. There is no single universally applicable standard for AI system audits, and the meaning and rigor of an audit differ across contexts such as banking model risk versus general enterprise AI.

Best practices

Define and document the audit scope and evaluation criteria before engagement, and explicitly state what is out of scope to avoid over-interpreting the resulting findings.

Verify the independence of the auditing party from the function being assessed, and record any relationships that could compromise that independence.

Clarify the engagement type and expected output (for example, an assessment report versus a formal attestation or certification) so stakeholders do not overstate the assurance provided.

Ensure auditors are granted access to the evidence needed—such as model documentation, validation records, and monitoring outputs—and note where access limitations constrain conclusions.

Treat audit findings as inputs to ongoing risk management rather than a one-time sign-off, and establish a process to remediate identified gaps and re-assess over time.

Maintain a clear distinction between third-party audit and internal governance or model risk management functions, using the audit to complement, not replace, internal validation and oversight.