Fintel Connect CEO Nicky Senyard on AI-driven discovery, GEO, and why affiliates now shape fintech visibility in a world of generative search.
Nicky, you’ve built a market-leading business over 15 years and used creativity and leadership to help shape a specialized industry. Could you start by sharing your professional journey?
Like many people, where I started is not where I landed. I began my career as a PR consultant in the 90s, well before digital marketing existed in the way we know it today. When I first came across affiliate marketing, it felt familiar because it reminded me of working with journalists. Publishers, much like journalists, are conduits to an audience. They create trust and translate information in a way that helps people make informed decisions.
That connection is what drew me into the digital world. Early on, I saw how powerful partnerships could be when you bring the right content, the right brands, and the right audiences together. Once I stepped into affiliate marketing, I stayed. I’ve now spent 25 years in this space, first in another niche and today in financial services.
I’ve never been a generalist. I work best when I can go deep, understand an industry fully, and help build something meaningful within it. That focus continues to guide my work and the work we do at Fintel Connect today.
You’ve long focused on transparency, scalability, and growth in digital performance marketing. How do you see large language models (LLMs) reshaping the broader landscape of digital discovery today?
What we’re seeing with LLMs is a real shift in how people discover financial products. Instead of searching for a list of options, consumers are asking open-ended questions and the model is deciding which brands and products make it into the answer.
Our research showed just how broad those information sources can be. ChatGPT used around four times more citations than Copilot, which tells us it draws from a wider mix of inputs. And in three of the four AI agents we tested, more than 60% of those sources came from publisher or affiliate sites, not the financial institutions themselves.
It’s a new channel, defining its own path of what visibility means. For a brand, it’s no longer only about where you rank on a search results page. It’s about whether your products are represented inside an AI-generated response. Publishers have always influenced consumer decision-making, but now they are part of the data that feeds these models.
For financial brands, if you are not represented through trusted, well-structured content, either on your own site or through partners, you risk being left out of the AI conversation entirely.
With AI search engines increasingly generating answers rather than listing links, how do you expect financial institutions to adapt their digital visibility strategies?
AI is removing the idea of a traditional results page. Because many people aren’t scrolling as much anymore and instead getting one compiled answer, financial institutions need to rethink visibility from the ground up.
The first shift is knowing that each model behaves differently. In our research, Gemini relied heavily on financial institutions’ websites, while Perplexity and Copilot pulled most of their information from publishers. One approach won’t work across all platforms. Institutions will need strategies that match how each engine sources content.
The second shift is around structure. LLMs consistently surfaced listicles, comparison tables, and clean educational articles. What we saw was that promotional banners and iFrames didn’t register. Product information needs to be clearer, well-organized, and aligned to common questions consumers are asking.
And the third shift is partnership. With more than 60% of citations in most models coming from publisher and affiliate sites, those partners are now critical visibility channels. If your products aren’t represented in that ecosystem, you may not appear in the answer the model generates.
The path forward is clear. Tailor your content to each platform, structure it in a way that AI can understand, and work with the partners the models already trust.
As new AI-driven discovery models emerge, what shifts do you predict in how consumers evaluate and choose financial products online?
Because AI is changing how people search, I think we will see consumers less motivated to compare products across multiple websites and more on getting a single, summarized answer from an AI tool. That shifts the early stage of product evaluation to the model itself, which means LLMs are looking for signals they can trust such as broad affiliate coverage, accurate rates, and current information. These factors help the models understand which products are credible and relevant.
For example, when an AI system identifies relevant products for a question like “What is the best savings account?”, it is effectively deciding which brands make it into consideration. And because each model pulls from different sources, early visibility depends on whether a brand is represented clearly, accurately, and consistently across the content that’s out there.
While people will still look for rates and rewards, they will also want context. In our research, one thing that kept showing up was simple educational explainers and ‘what to watch for’ guidance alongside recommendations. AI is helping consumers understand the category, which raises the bar for brands to present information clearly and transparently. Trust remains central. Financial products require a higher level of confidence, and consumers still rely on independent research for important decisions. Affiliates are still essential in the path to conversion because the more complex the financial product, the more people trust their guidance.
Why do you believe affiliates remain essential partners for banks and fintechs in an AI-powered search environment?
Affiliates are often gatekeepers in how consumers discover financial products today. They have always helped consumers make sense of financial products, but AI has amplified their importance in a way we haven’t seen before. In an environment where models generate a single answer rather than a list of links, affiliates are no longer just there to drive conversions. They are visibility partners, offering organized and trusted content that not only compares products but also explains more complex features clearly, aligning closely with how AI models pull information together.
For banks and fintechs, that means if you are not present in the affiliate ecosystem, you are not only missing potential customers, you may not be included in the AI answer at all. They give financial institutions reach, credibility, and context at a time when AI models are deciding which products show up for a question.
How can affiliate programs evolve to ensure financial brands maintain discoverability when AI models often summarize or mediate information for users?
AI hasn’t reduced the value of affiliates. It has expanded how brands should think about the value of their affiliate programs. When answers are summarized, visibility is no longer only about driving a click about making sure the information the models read is accurate, well-structured, and easy to access.
That begins with stronger collaboration as affiliates are creating much of the content that LLMs rely on. Brands should be sharing clearer product data, updated FAQs, priority customer segments, and even insights into the prompts consumers are using. The better the inputs, the stronger the content, and the greater the chance it will be picked up by AI.
Affiliate programs also need a broader mix of content. Our research showed that different models elevate different formats. Gemini leaned toward FI educational pages, while Perplexity surfaced comparison content for credit card queries. Modern programs need to support both educational content and detailed comparisons that align with real consumer intent.
What practical steps can financial institutions take to increase the likelihood that their brand appears in AI-generated responses or conversational search results?
AI models pull from information they can trust and interpret quickly. The most practical steps financial institutions can take are making their content easier for the models to read and aligned to the questions people actually ask.
The first step is to strengthen on-domain content. Product pages should be tightened, FAQs added, and comparisons made simple. Anything sitting behind an iFrame will be ignored, so that information needs to be brought into the main page.
The second step is to tailor your approach to each platform. Gemini relies heavily on FI websites, while ChatGPT, Perplexity, and Copilot pull more from publisher content. Institutions will need visibility strategies that match how each model sources information.
The third step is to participate actively in the affiliate ecosystem because publishers are part of the data pipeline for AI. If you want your products accurately represented in their articles and explainers, you need strong partnerships and up-to-date information flowing to them.
And finally, financial institutions should track their own presence. Look at which prompts you appear for across LLMs and where the gaps are. You can only improve discoverability if you know your baseline.
Generative Engine Optimization (GEO) is an emerging concept gaining traction. How would you define GEO, and why do you believe it will become a foundational marketing pillar for financial institutions?
I describe GEO as the practice of making sure your brand is present in the places AI models pull from when they generate answers. It is the evolution of SEO. Instead of aiming for a results page, you are aiming to be included in the answer itself.
It matters for financial institutions because consumer behavior is shifting quickly. Searches through LLMs are growing faster than traditional search, and people are asking very specific, conversational questions about money. The model becomes the intermediary and decides which products appear, how they are framed, and in what order.
GEO will become foundational because it connects directly to discoverability, trust, and accuracy. If your products are not reflected in the sources AI reads, you risk being invisible. If the information is not current, you risk being misrepresented. And if you wait, you give others a head start.
To me, GEO is simply the next stage of digital visibility. Financial institutions will need to invest in it if they want to stay part of the consumer conversation as discovery continues to move toward generative AI.
From your perspective, how does Fintel Connect’s mission align with these shifts toward generative search and GEO, and what opportunities does this create for the fintech ecosystem?
One thing I’ve always believed is that independent publishers create a powerful halo effect in the market. Platforms like NerdWallet, CreditCards.com, RateHub, and Borrowell have earned real consumer trust. They guide people through financial decisions, and historically our work with them has focused on cost-per-acquisition and measurable outcomes.
I’ve often said it is 80% acquisition and 20% halo. You get the new customer, and you also get the benefit of being present in trusted, independent content. Generative search has made that halo even more important. LLMs are now pulling heavily from affiliate and publisher content. If your products are not represented on those sites, you miss two opportunities: the direct acquisition and the visibility that fuels AI-driven discovery.
That is where Fintel Connect’s mission aligns so naturally with this shift. We have always been focused on helping financial brands grow through transparent, performance-driven partnerships. In a GEO environment, those partnerships become essential. They ensure products are discoverable, accurately represented, and included when AI engines generate answers.
For the fintech ecosystem, this opens the door to new opportunities. It elevates publishers as trusted visibility partners and gives emerging brands a clearer path to being found, not just clicked on. GEO is levelling the playing field, and our role is to help financial institutions navigate that shift with partners consumers already rely on.
Finally, what advice would you give to financial brands that are just beginning to navigate AI-driven discovery and want to future-proof their digital growth strategies?
In a period of this much change, financial brands need to move thoughtfully. This isn’t the time to dive in without understanding the landscape, especially given the regulatory environment the industry operates in. But it also isn’t the time to stand still.
The first step is to get into the flow. Begin building a GEO strategy, experiment with the major LLMs, and understand how each model surfaces content differently. That is why we produced our report, to give teams a starting point and show that no two engines behave the same way.
My advice is to get involved, but do it with intention. The models are evolving quickly. How ChatGPT behaved in version 4 is different from version 5, and that will continue. You don’t want a rigid strategy at this stage. You want a mindset of learning, testing, and adapting.
For brands that are just beginning, start with research. Use tools that show how your products appear across the different LLMs. Some platforms are advanced, some are more cost-effective, but even a simple view gives you a baseline to work from.
Future-proofing isn’t about having all the answers today. It is about building a clear foundation, experimenting responsibly, and giving your teams the confidence to navigate what comes next.
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