New Zealand Engineer Kira Klein Develops AI Governance Tool to Help Regulators Keep AI Accountable

AUCKLAND, NEW ZEALAND, October 30th, 2026, FinanceWire

As AI spreads through financial services, Kira Klein is developing a tool to help make its use easier to oversee. The question behind it is simple. Who remains accountable?

Kira Klein, a 28-year-old Salesforce engineer from New Zealand, is developing an independent AI governance tool through her company, Klein Consulting, with regulatory bodies in mind. Her aim is to make the responsibilities and evidence behind AI use easier to examine.

Klein is building for the moment an AI decision has to be questioned.

Imagine a bank uses AI to help assess an application. A customer challenges the result. Someone now has to establish what the system was authorised to do, what was checked and who can review the outcome.

That is the kind of accountability problem Klein wants to address. For her, that ambition has a personal starting point. Growing up in New Zealand shaped her expectation that institutions should be trustworthy. Protecting that expectation as AI becomes more influential is part of why she wanted to build the tool.

“When a decision affects someone’s life, ‘the model said so’ should never be the end of the explanation,” Klein said.

The Gap After Approval

A survey published by the Bank of England and the Financial Conduct Authority on October 26, 2026 gives the ambition a timely backdrop. Of the firms responding, 86 percent reported using AI.

In the survey’s governance responses, 94 percent reported firmwide AI policies, principles or standards. Ongoing monitoring was reported by around half of respondents to that question. The findings suggest that establishing formal governance and maintaining oversight after deployment can be different tasks.

The consequences deserve attention. Stanford’s 2026 AI Index reported 362 documented AI incidents in 2025, compared with 233 in 2024. Those are recorded incidents, not a measure of the probability that any particular system will fail.

For Klein’s project, the practical question is what happens after an organisation approves an AI system. A supplier may update it. Its purpose may change. The people who reviewed it may move on. A useful record of accountability would need to remain meaningful through those changes.

Making Accountability Usable

Klein’s route into the problem runs through the everyday work of banking technology. She joined ANZ’s technology graduate programme in 2019 after studying Information Systems and Management at Victoria University of Wellington. Her experience includes software delivery, release management, cloud control documentation and accessibility testing.

That work brings her close to the practical questions behind a functioning system, how changes are introduced, which controls are documented and whether people can use the result. Her independent venture takes that concern with the workings of technology into AI oversight.

For the tool to fulfil its ambition, it would need to connect an AI use with the people responsible for it and the evidence supporting its approval and ongoing review. A reviewer should be able to see what remains uncertain and where a human decision is needed.

A record alone cannot establish that a model is safe. The information must be current and useful enough for someone to challenge it. That creates a demanding design problem, making evidence easier to follow while preserving the judgement required to assess it.

There is an established field to build within. The US National Institute of Standards and Technology’s voluntary AI Risk Management Framework addresses trustworthiness across the design, development, use and evaluation of AI systems. Klein’s task is to make her intended contribution useful in practice.

“I want to make it easier to see who owns the risk, what has been checked and what still needs a human decision,” she said.

At Sibos in Miami, where Klein followed discussions about AI and payments.

Public Trust and AI Accountability in New Zealand

New Zealand offers a meaningful starting point for that ambition. In the OECD’s 2025 survey on trust in public institutions, 62 percent of New Zealanders reported high or moderately high trust in the civil service, compared with an OECD average of 45 percent.

New Zealand also ranked joint fourth among 182 countries and territories in Transparency International’s 2025 Corruption Perceptions Index, scoring 81 out of 100. The index measures perceived public-sector corruption.

That confidence cannot simply be assumed to extend to AI. The same OECD survey found that 39 percent of New Zealanders were confident government agencies would maintain human oversight when using it. For Klein, the motivation is to help preserve trust by making accountability easier to examine.

“Growing up in New Zealand shaped my expectation that institutions should earn our trust. I want that expectation to survive as more decisions involve AI,” Klein said.

At the Forbes Under 30 Summit.

About Kira Klein

Kira Klein is a New Zealand software engineer of Asian descent and founder of Klein Consulting. Raised in Wellington and based in Auckland, she is a 2026 Forbes 30 Under 30 nominee in technology, Asia-Pacific. She is an Associate Member of the Institute of Directors, a Certified Member of INFINZ and a member of the AI Forum of New Zealand. Klein Consulting is independent of ANZ, and the views expressed are Klein’s own. More information is available on her LinkedIn profile.

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