Artificial intelligence is becoming a central feature in the New Zealand insurance sector, with companies increasingly deploying AI, machine learning, and data analytics to streamline underwriting, claims management, and customer engagement.
According to Fintrade Securities Corporation Ltd (FSCL), these technologies are being used to automate routine processes and support staff in making more informed decisions, rather than replacing human roles outright.
For example, the underwriting process – traditionally reliant on historical records and expert judgement – is now being reshaped by AI.
FSCL reported that machine learning models are enabling insurers to evaluate risk using a broader set of data, including behavioural patterns, geographic factors, and economic signals. This shift is allowing for more granular and dynamic risk assessments.
Insurance’s heavy dependence on paperwork has also led to the adoption of intelligent document processing (IDP) systems.
By leveraging optical character recognition (OCR) and natural language processing (NLP), insurers can digitise and interpret both structured and unstructured documents. This reduces manual data entry, lowers the risk of errors, and speeds up claims and policy administration.
NLP is also being used to extract key information from customer communications, improving operational efficiency and service quality.
AI-driven tools are further enabling insurers to move beyond conventional demographic-based pricing. Access to real-time behavioural data is supporting the development of personalised insurance products, such as usage-based policies that adjust premiums according to individual driving habits or lifestyle factors.
AI systems can also deliver proactive risk notifications to policyholders, such as alerts about severe weather or property maintenance needs.
Recent research from Snowflake and the Enterprise Strategy Group showed that organisations in Australia and New Zealand (ANZ) are allocating a greater proportion of their technology budgets to generative AI (GenAI) compared to the global average.
Thirty-two percent of surveyed ANZ firms are investing more than a quarter of their technology budgets in GenAI, outpacing the global figure of 25%.
These investments are producing slightly higher returns, with ANZ respondents reporting a 44% return on GenAI spending, compared to 41% globally.
As AI becomes more embedded in insurance and other sectors, calls for specific regulation are intensifying.
More than 20 AI experts have signed an open letter urging the New Zealand government to introduce a regulatory framework for AI, citing concerns about public trust and potential risks.
In an interview with the Science Media Centre, Dr Andrew Lensen, senior lecturer and programme director of artificial intelligence at Victoria University of Wellington, pointed to the European Union’s AI Act and Australian proposals as examples of risk-based regulation.
“There are a number of examples we could draw on. The most discussed one is the EU AI Act, which employs a risk framework similar to what we are proposing in our letter. I think that is a good starting point, alongside what has been done in Australia. The EU’s act is also very comprehensive, though; we don’t need to have something so complex,” he said.
He warned that without regulation, New Zealand could face harms such as deepfakes, fraud, and biased automated decisions, as well as less visible issues like increased emissions and intellectual property risks.
Chris McGavin, director at LensenMcGavin AI, highlighted the need for regulation that reflects New Zealand’s unique context, including Māori Data Sovereignty.
“Most of the world’s jurisdictions which are exploring AI regulation are opting for risk management models. This means that regulatory intensity scales proportionally with the perceived risk of a model or application,” he told Science Media Centre.
He also noted that regulatory uncertainty may be hindering innovation and public trust in AI.
Legal scholars caution that existing laws may not be sufficient to address the new risks posed by AI.
Dr Cassandra Mudgway, senior lecturer in law at the University of Canterbury, noted that current legislation was not designed with generative AI in mind and may not adequately protect against emerging forms of online harm, such as non-consensual image generation and chatbot-enabled abuse.
Dr Kevin Shedlock, lecturer at Victoria University of Wellington, emphasised the importance of governance models that protect Māori interests and uphold Te Tiriti o Waitangi. He warned that without proper oversight, AI could reinforce biases or be used to spread misinformation, particularly affecting Māori communities.
Professor Ali Knott of Victoria University of Wellington advocated for the creation of a national AI oversight body to coordinate New Zealand’s contributions to international AI governance and manage domestic impacts.
“It would serve two important purposes. Firstly, it would help to coordinate our contributions to international discussions about AI safety,” Knott said. “Secondly, a national body would help us to coordinate AI legislation relevant to New Zealand.”
Dr Olivia J. Erdelyi of the University of Canterbury underscored the urgency of establishing a suitable regulatory environment, noting that uncertainty could limit both the benefits and safe adoption of AI.
“Simply put, inadequate – too much, too little, or the wrong type of – regulation hinders the optimal functioning of an economy. So, if AI regulation is needed and we fail to put it in place, we will not be able to realise the benefits and mitigate the risks of AI,” she said.
