AI Growth Sparks Financial Stability Concerns at RBNZ
The growing use of artificial intelligence (AI) within New Zealand’s financial and insurance sectors is driving efficiency improvements but also raising regulatory alarms. The Reserve Bank of New Zealand (RBNZ), in its May 2025 Financial Stability Report, highlighted that AI’s increasing role could alter risk profiles and operational frameworks across financial institutions.
Benefits and Risks of AI in Finance
The report points to advances in data modelling, fraud detection, and cybersecurity as key areas where AI adds value. Yet, it also warns that the complexity of AI technologies and reliance on external AI providers might increase systemic risks.
Kerry Watt, RBNZ’s director of financial stability assessment and strategy, commented on the dual nature of AI’s impact: “There is still considerable uncertainty around how AI will shape the financial system. While it can boost resilience, it may also introduce or amplify vulnerabilities.” The report urges financial institutions to integrate AI-related risks into their existing risk management frameworks and signals that regulatory policies will need to evolve alongside technological developments.
Significant Investments in Generative AI Across ANZ
Businesses in New Zealand and Australia are investing heavily in generative AI (GenAI). A study by Snowflake and the Enterprise Strategy Group found that 32% of firms in the region allocate more than 25% of their technology budgets to GenAI, compared with 25% globally.
The study also reported a 44% return on investment from GenAI projects locally, slightly higher than the 41% global average. Moreover, 91% of respondents from the region said GenAI improved decision-making speed, outpacing the 84% global figure. Many organisations focus GenAI efforts on customer-facing activities like personalised communications and engagement.
However, challenges remain. The report reveals that 63% of ANZ businesses faced higher-than-expected staffing costs while scaling AI teams, significantly above the global rate of 48%. Data infrastructure issues, including fragmented systems and lengthy data preparation, also delayed AI implementation.
Consumer Skepticism Persists in Insurance
Despite AI’s operational benefits in insurance, consumer trust remains cautious. GlobalData’s survey including New Zealand participants showed that while faster service and efficiency are recognised, concerns linger over data privacy, transparency, and automated decisions.
Beatriz Benito, lead insurance analyst at GlobalData, highlighted that “AI can simplify claims processing and support services, but certain interactions still need human oversight.” She added that clearer communication about AI’s capabilities and limitations will be essential to improve consumer acceptance.
- Key Takeaways for Finance and Insurance Professionals:
- Integrate AI risk assessments into existing frameworks to manage emerging vulnerabilities.
- Prepare for higher staffing and data infrastructure costs during AI adoption.
- Maintain transparency and human involvement in customer interactions to build trust.
- Stay informed on evolving regulatory standards related to AI.
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