Consumer Data Right policy design
The Government has established a Consumer Data Right through the Customer and Product Data Act 2025.
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Participating as a data holder or accredited requestor
Taking part in the Consumer Data Right (CDR) means joining a trusted framework that empowers consumers and drives innovation. Learn more about the types of participants in the regime, what’s involved in becoming a participant, and the fees and levies that apply. Whether you’re a data holder or looking to become an accredited requestor, you’ll find the key information you need to get started.
Consumer Data Right
A Consumer Data Right (CDR) is a legal framework that lets you access, share, and manage certain data, like transaction history, with trusted third parties through secure digital systems. The goal is to provide greater choice, convenience, and innovation.
Trade regulatory system
This page describes the trade regulatory system administered by MBIE, and its objectives.
Standards and conformance regulatory system
This page describes the standards and conformance regulatory system and its objectives. It also lists the other government agencies involved in the system and main stakeholders.
Early access to KiwiSaver
Members can withdraw their KiwiSaver savings when they qualify for NZ Superannuation (age 65). You may also be able to get some or all of your savings earlier if you’re buying your first home, moving overseas, have a serious illness or a life‑shortening congenital condition, or are experiencing significant financial hardship.
Better protections available for Incorporated Societies under new Act
The New Zealand Companies Office is encouraging incorporated societies not yet reregistered under the Incorporated Societies Act 2022 to take action now ahead of the Easter Sunday deadline on 5 April 2026.
Use and outputs
Having humans-in-the-loop, and understanding how to use artificial intelligence systems effectively and securely, is key to responsible artificial intelligence use and deployment.
Data and modelling
Responsible training data collection and modelling practices support useful, secure and fair artificial intelligence systems.
Governance and accountability
Clear cross-business lines of oversight and accountability, including across artificial intelligence use or development, enables effective risk management.