Chapter 08 · Finance, data & evidenceSustainable Finance & Investment
Anti-greenwashing rule
Definition
An anti-greenwashing rule is a regulatory or supervisory requirement intended to prevent misleading sustainability claims in financial products, services or communications.
References
(ESG 4.3): sustainability claims must be fair, clear and not misleading — applies to all FCA-authorised firms from 31 May 2024.
FCA Sustainability Disclosure Requirements & investment labels (SDR)FCA Sustainability Disclosure Requirements (PS23/16) · verified 2026-08-22Official text
This reference provides supporting context for how “Anti-greenwashing rule” is defined and used.
Overview
What it means in practice
Anti-greenwashing rule should be read as a sustainable-finance term. Its meaning depends on the instrument, mandate, metric, disclosure framework and evidence of use or outcome.
In practice, users should state the boundary, actor, method and evidence. That keeps anti-greenwashing rule specific enough for review without turning it into a broader claim.
Why it matters
Anti-greenwashing rule matters because finance labels can influence capital allocation, product claims and accountability. Clear boundaries help distinguish ambition, method, measurement and realised outcome.
Common misconception
A common error is to use Anti-greenwashing rule without stating the financial product, portfolio boundary, metric or disclosure rule. Those details often determine the claim.
Review questions
Who or what is covered by the term? What evidence supports it? What limitation, method or affected group would change how a reader interprets the claim?
How it is used
The term appears in capital allocation, risk assessment, measurement, valuation, due diligence and performance analysis, where investors, lenders, analysts, data providers and sustainability teams use it to classify, assess or communicate a regulatory or supervisory requirement intended to prevent misleading sustainability claims in financial products, services or communications.
Its correct use depends on the calculation method, data provenance, assumptions, boundary and decision purpose.