For Board · Heads-of · Practitioner
Consumer Duty
Also known as: FCA Consumer Duty
The FCA's outcomes-based standard requiring firms to deliver good outcomes for retail customers, in force since July 2023. It sets no AI-specific rules but applies in full to AI-driven customer journeys, pricing, advice and communications.
- FCA
- Consumer Duty
- PRIN 2A
- vulnerable customers
- retail financial services
- Mills Review
What it requires
The Duty (PRIN 2A) requires firms to act to deliver good outcomes for retail customers, avoid causing foreseeable harm, and enable customers to pursue their financial objectives. Four outcomes structure it: products and services, price and value, consumer understanding, and consumer support. It applied to open products from 31 July 2023 and to closed products from 31 July 2024.
Where AI meets it
An AI system that prices, advises, communicates or decides on support is inside the Duty. The risks are familiar: pricing models that charge vulnerable customers more, chatbots that are confidently wrong or block access to a person, assistants that tell customers what they want to hear (sycophancy), and explanations customers cannot understand. The FCA's Mills Review of AI in retail financial services, published in July 2026, examines these questions.
What good looks like
Test AI-driven journeys for outcomes across customer groups, including customers with characteristics of vulnerability; keep a route to a person; monitor complaints and outcomes for AI-driven failure; and be able to show the board how AI affects each of the four outcomes. The register entry is exploitation of vulnerable groups by AI; automated decision-making safeguards is the control.
Sources
Related Terms
Automated Decision-Making
A decision about a person taken by technological means without meaningful human involvement. In UK data protection law, Articles 22A to 22D of the UK GDPR (inserted by the Data (Use and Access) Act 2025 and in force since 5 February 2026) allow significant automated decisions, but only with safeguards: information, the right to make representations, human intervention and the right to contest.
Explainability
The ability to give a person an account of why a system produced a particular output, in terms they can act on. Explainability is a property of the account and its audience, not of the model: an opaque model can be explainable, and an interpretable one can fail to be explained.
Fairness & Bias
The principle and practice of ensuring AI systems do not produce systematically different outcomes for individuals or groups because of protected characteristics or other vulnerable attributes. Algorithmic fairness is the same idea expressed as measurable criteria.
Sycophancy
A model's tendency to tell users what they want to hear, agreeing, flattering or validating at the expense of accuracy. It is a side effect of training on human approval, and in customer-facing financial services it is a conduct risk as well as a quality one.