For Board · Heads-of · Practitioner
Three Lines of Defence
Also known as: Three Lines Model · 3LoD
The risk governance model used across UK financial services, in which the business owns and manages risk, an independent risk and compliance function oversees it, and internal audit gives the board independent assurance. Applied to AI, it decides who owns a model, who challenges it and who checks both.
- three lines
- risk governance
- internal audit
- second line
- financial services
The three lines
First line: the business that builds, buys or uses the AI system owns its risk and runs its controls. Second line: risk management and compliance set the standards, including the risk appetite, and challenge the first line's evidence; independent model validation sits here. Third line: internal audit tests whether the first two work and reports to the board. The Institute of Internal Auditors restated the model in 2020 as the Three Lines Model, with more emphasis on how the lines work together than on keeping them apart.
Where AI strains it
A vendor model sits partly outside all three lines. The second line may lack the skills to challenge a model it does not understand, which makes challenge a formality, and internal audit may have no AI expertise at all. Business units adopting AI tools on their own create first-line risk that nobody has recorded, which is shadow AI.
What good looks like
Name a first-line owner for every system in the AI inventory, give the second line the competence and authority to challenge (including independent validation under PRA SS1/23 for banks), and put AI in internal audit's plan. The register entry is unclear AI ownership and accountability; the control is the AI ownership and accountability framework.
Sources
Related Terms
Accountability
The principle that individuals and organisations can be held responsible for decisions made by the AI systems they deploy, and must be able to explain those decisions to the people affected.
AI Assurance
The work of measuring, evaluating and communicating whether an AI system, or the organisation running it, meets the claims made for it, so that others can rely on those claims. It spans internal testing through to independent audit and certification, and the question it answers is not whether a system is good but whether a statement about it can be trusted.
Governance Framework
A structured set of policies, roles and controls that guides an organisation's decisions about AI and its oversight of AI systems.
Model Risk Management (MRM)
The discipline of identifying, measuring, controlling and reporting the risk that a model is wrong, misused or misunderstood, across its whole life from development to retirement. It predates AI by decades in banking, and it is the frame UK regulators have chosen for AI in financial services: the PRA's SS1/23 principles have applied to AI models as to any other since May 2024, and were amended in April 2026.