GUEST COLUMN:
Daniel Mines
CEO
Menna
For years, diving into a financial decision – whether it’s choosing a mortgage for your home or insurance for your business – has largely revolved around Google. The search engine sends you off on a ramble through price comparison and review sites, as well as product pages on brand sites.
The financial services industry has built its distribution model around this type of browser-driven journey that ends with customers hitting the buy button.
But that’s changing. Yes, you may still plug a query into Google, but there’s a chance you’ll also ask ChatGPT, Gemini, Perplexity or Claude.
The rise of zero-click search
General AI engines are genuinely starting to change how people find and buy financial services products. I recently contributed to a report by The Folk Group on how AI is changing financial services distribution, in which 11% of people said they had used AI to compare financial services products, such as bank accounts, mortgages or insurance before buying. I’ve no doubt this figure will increase.
In other words, so-called zero-click search is starting to take hold, where product and brand discovery happens within AI summaries and responses rather than traditional clicks.
The general purpose AI assistants that facilitate this can be immensely helpful if you’re seeking generic answers or explanations for low-stakes financial decisions. They can save you a lot of time and handwringing.
But as many of us have discovered when using these seemingly super-smart chatbots for precise, higher-stakes issues – in complex, regulated decisions such as business finance – the benefits of general AI engines start to unravel. The same prompt can return different answers every time, and they operate outside of UK financial services regulatory frameworks.
For bigger financial decisions, more specialist help is needed
In my field, SME financing, ‘general’ AI certainly isn't good enough. Decisions about financing are high stakes, regulated and unique to each business.
As it stands, SMEs simply can’t get the funding they need to grow – a problem I come across this all the time in my role of co-founder of Menna, which exists to support SME owners.
But general AI isn’t the answer. SME owners need more specialist support. They need an expert assistant that is accountable, explainable, and built specifically for their world.
This is where narrow, purpose-built AI agents like Menna come in. Unlike general-purpose assistants, AI agents are designed for specific regulated tasks, operating within fixed frameworks, trusted datasets and compliance boundaries.
That means better answers, yes, but also enforceable protections, transparent data handling, and decisions that can be unpacked and challenged. This avoids hallucinated lending rates, unexplainable decisions and ambiguity about where your data is actually going.
Unlike general purpose assistants, agents plug into fixed, rules-based models to deliver accurate quotes, eligibility checks and product comparisons. They don’t just explain options, but can complete steps on the user’s behalf, such as gathering data, checking eligibility or initiating applications.
So AI agents could be transformative for SMEs seeking financial services that truly work for them, and will undoubtedly lead to the birth of many new players in the space – all offering agentic AI in different niches.
Ultimately, it’s likely that both AI agents and general assistants will sit side by side in the delivery of financial services, each playing different roles.
Financial services firms must adapt
Where does that leave financial services firms? It’s a “deer caught in the headlights moment” for financial services, as another contributor to The Folk Group report described it.
They will continue to provide the products people and businesses need, but their world will change. As customers increasingly delegate financial decisions to AI agents for the curated and personalised processes they offer, providers of loans, investments, mortgages and savings will have to adapt to get their attention. The traditional digital channels that have given them consistent customer acquisition models are changing!
As we are seeing, some will embrace AI agents as part of their acquisition mix, making sure they are ‘learning’ as early as possible, while others will wait and see. Many will worry about being disambiguated and being pushed away from their customers.
The impact of AI is particularly interesting for price comparison sites, of which Wales has more than its fair share. The traditional comparison model is built on the assumption that consumers arrive via Google search, complete a form, receive a ranked results table and click through to buy.
As a former head of customer and innovation at Confused.com, it reminds me of the early growth of consumer price comparison. There were winners and losers, as some big financial services brands held back from using price comparison in the early days, being forced to use it later as it dominated the sector. Similarly, the winners used price comparison early to grow, including current market leaders.
Ultimately, price comparison sites and other financial firms will need to optimise not just for human consumers, but for the AI agents acting on their behalf.
The firms that thrive in this next era will be those that design for a world where AI agents, not search engines, become the primary gatekeepers of financial choice.
