Finsure NZ on the limits of AI and why human advisers win
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As artificial intelligence floods the financial services sector, New Zealand mortgage advisers face a defining choice about how they position themselves for the decade ahead
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AI has been called the most significant productivity tool in a generation. But a tool is only as good as its fit for the job at hand. A Swiss Army knife is impressive in the hands of a wilderness survivalist, but you wouldn’t use one to perform surgery. In financial services, the stakes of reaching for the wrong instrument are just as real.
“AI in financial services can’t just be clever – it has to be contextual,” says Jenny Campbell, country manager at Finsure New Zealand. “If it doesn’t understand lender policy, compliance obligations and the real-world workflow of an adviser, it’s not fit for purpose.”
The AI tools flooding the market right now vary enormously in quality, and the differences are not always visible on the surface. Off-the-shelf AI solutions are by far the most used among New Zealand firms, and the lending industry is no exception. Many providers have taken large public models like ChatGPT or Gemini and placed a wrapper around them, presenting the result as an industry solution.
Finsure Group is one of the fastest-growing aggregators in the Asia-Pacific, providing maximum value and helping advisers achieve their goals. We have achieved this success by getting to know our advisers’ needs and the nature of adviser success, and by gaining an understanding of how we can support our network members to become some of the best in the industry. In speaking with our partners in New Zealand, we identified the need for a holistic and comprehensive aggregation solution for Kiwis and have created award-winning services to bring to the table.
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“People want a human in their corner when they’re making one of the biggest decisions of their lives”
Jenny Campbell,
Finsure New Zealand
But a general-purpose AI model has no inherent understanding of New Zealand lending criteria, responsible lending obligations or the practical realities of what a mortgage adviser does each day. The best platforms, by contrast, are purpose-built from the ground up. They embed intelligence within proven frameworks that reflect real-world lending scenarios, rather than generating polished-sounding responses that may be unreliable when it counts.
The practical implication is straightforward: good AI enhances judgement and strengthens decision-making. Bad AI attempts to shortcut it.
Published 13 Apr 2026
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“AI isn’t coming for advisers’ jobs – it’s coming for their paperwork”
Jenny Campbell,
Finsure New Zealand
Source: AI Forum New Zealand, AI in Action – New Zealand’s AI Productivity Report, August 2025
74%
Generic AI tools
7%
Custom-built solutions
19%
Mix of both
Adoption of generic vs custom-built AI among New Zealand firms
The agentic adviser A new phrase is starting to circulate in financial services circles: the agentic adviser. It sounds technical, but the idea behind it is grounded and practical.
An agentic adviser is someone actively using automated, AI-driven tools to scale and strengthen their business, not to replace their expertise but to extend it. In day-to-day terms, this might mean using AI to draft client communications, automate marketing content, summarise meetings or streamline CRM workflows. These tools can initiate actions
and run automated sequences, effectively giving advisers back hours that would otherwise disappear into administration.
“The agentic adviser isn’t outsourcing their judgement to AI – they’re outsourcing their admin,” says Campbell. “That’s a powerful distinction.”
The practical outcomes of this shift are tangible: faster response times, more consistent communication and the ability to operate at a higher level without increasing headcount. For a sole operator or a small team, that kind of leverage can be the difference between a business that grows and one that plateaus.
What this model does not mean, however, is stepping back from the work that requires human intelligence. The time freed by automation is most valuably redirected towards strategy, growth and the client relationships that no software can replicate.
Proportion of financial and insurance firms using AI
Spread of AI in financial and insurance services in New Zealand
Sep 2024
Mar 2025
Aug 2025
60%
80%
100%
Source: AI Forum New Zealand, AI in Action – New Zealand’s AI Productivity Report, August 2025
When clients arrive with AI-generated advice High-performing advisers are already adjusting to a shift in how clients show up to conversations. Customers today are more tech-savvy than previous generations, and many are using tools like ChatGPT or Gemini to research interest rate forecasts, loan structuring options and borrowing capacity before they pick up the phone.
That changes the starting point of many client conversations, and not always in straightforward ways.
Accuracy is an issue when generic AI is used for specialist tasks. Many AI tools can oversimplify or miss important nuances in lender criteria. A client who has spent an hour with a general-purpose chatbot may arrive confident in conclusions that don’t hold up against the specifics of a particular lender’s policy. The adviser who can engage with that information calmly, correct it where necessary and explain the actual policy position is demonstrating value that no algorithm can substitute.
“Clients will increasingly say, ‘ChatGPT told me this’,” says Campbell. “Advisers need to be ready to say, ‘Let’s unpack that – here’s what the lender policy actually says.’ That’s where expertise matters.”
The most effective advisers are already operating in this way: using AI behind the scenes to improve efficiency, while investing more, not less, in their credibility and depth of knowledge in client-facing interactions.
The human element is not a selling point – it’s the point Emotional intelligence is the one quality that makes advisers genuinely irreplaceable, and the mortgage context makes this especially clear.
Obtaining a home loan is not a neutral financial transaction. For most people, it represents security, ambition and significant personal risk. It’s often one of the largest financial commitments of their lives, and it frequently coincides with moments of major life change. Technology can process numbers and generate comparisons efficiently, but it cannot read hesitation in a client’s voice, provide real reassurance to a nervous first home buyer, or navigate a sensitive conversation about financial stress or competing family priorities.
“A mortgage isn’t just a transaction – it’s a milestone,” says Campbell. “People want a human in their corner when they’re making one of the biggest decisions of their lives.”
There is also a broader pattern worth noting here. As digital interactions increase across every sector, face-to-face connection becomes a more powerful differentiator, not a weaker one. The adviser who invests in in-person meetings, community engagement and regular client reviews is not working against the tide of technology. They are working with it, using automation to create more space for the human moments that build loyalty.
“As the industry becomes more digital, human connection becomes more valuable – not less,” says Campbell.
Why loan writing alone is no longer enough Advisers who still define themselves primarily as loan writers risk becoming commoditised. Consumer expectations have shifted considerably, and clients are increasingly looking for simplicity and integration when it comes to managing their financial lives.
An adviser positioned purely as someone who processes home loans will increasingly be compared on rate alone, and that’s a difficult position to defend long-term. Rate
comparisons are easy; they take seconds online. Relationship and expertise are not so easily benchmarked.
Advisers who broaden their offering to include personal loans, business lending, asset finance, insurance referrals and strategic refinancing advice are building something more durable. Multiple financial touchpoints with a single adviser create a stickier client relationship and a more resilient business.
“When advisers step into the role of financial problem-solver rather than product arranger, they shift from being transactional to being strategic,” says Campbell. “That’s where long-term value lies.”
Remaining narrow in scope is a long-term relevance risk, particularly as AI continues to automate the more mechanical parts of the process.
How Finsure is thinking about AI and aggregation AI isn’t going away. Indeed, in many sectors, AI is now used daily. For aggregators like Finsure New Zealand, the AI era creates both an obligation and an opportunity. The obligation is to provide tools that genuinely serve advisers rather than adding noise. The opportunity is to remove the friction that costs advisers time and limits their capacity to grow.
Finsure’s approach centres on intelligent systems that automate repetitive administrative tasks, strengthen compliance workflows and enhance data insights, freeing advisers to focus on relationships and business development.
“AI isn’t coming for advisers’ jobs – it’s coming for their paperwork,” says Campbell.
AI as a productivity enabler sits very differently from AI as a threat. For advisers who embrace this distinction, the practical path forward involves reskilling in some targeted areas: developing a working knowledge of how AI tools operate, understanding their limitations and identifying where automation genuinely adds value versus where human involvement is non-negotiable.
That reskilling doesn’t require advisers to become technologists. It requires them to be informed users of the tools available to them and confident enough in their own expertise to know where technology ends and professional judgement begins.
“AI should free advisers from paperwork, not from purpose,” Campbell adds. “The future isn’t human versus machine; it’s human empowered by machine – and that’s where real progress lies.”
There is a reason that surgeons don’t carry Swiss Army knives into theatre and mountaineers don’t carry scalpels in their backpacks. The right tool depends entirely on the task at hand and the hand that wields it.