“Where there’s mystery, there’s margin.”
That old axiom may have almost vanished in the face of AI.
For ages, pricing power and product differentiation in nearly every industry relied on a simple truth: where there’s mystery, there’s margin. Customers lacked perfect information, and businesses optimized profits by managing that information gap.
That era is over.
Artificial Intelligence has ushered in a historic shift: for the first time in human history, customers across every industry have near-perfect access to knowledge about the products and services they’re buying. Pricing, features, reviews, and hidden fees, once scattered, inaccessible, or opaque, are now surfaced instantly by AI assistants.
Banking is no exception. While much of the industry’s AI discussion has focused inward—on making banks more efficient, productive, secure, and profitable—there has been far less conversation about the outward implications: How do banks serve customers who are AI-informed, perfectly rational, and radically empowered?
There are six critical constructs that will shape the next era of customer engagement. These principles are already guiding how we evolve our product suite, and they should guide every bank preparing for the AI-informed future.
1. Distribution has shifted: Banks must “sell to the agent”
The shift: In the 2025 Accenture Global Banking Consumer Study, generative AI is described as “a powerful engine for continuity of conversation,” enabling banks to “anticipate needs” and integrate directly with customer interactions. As the gatekeeper shifts from human interface to algorithmic filter, banks that don’t provide consumable, machine-readable product metadata risk invisibility.
The opportunity: Banks must optimize not just for human eyes but for machine parsing. Structured, machine-readable product data delivered through APIs and standardized disclosures is table stakes. Just as importantly, marketing language must evolve toward explainability: side-by-side comparisons, plain-language rationales, and transparent “why this product fits you” narratives. In an AI-mediated marketplace, every hidden ‘gotcha’ will be known, and judged poorly.
2. Trust is the currency
The shift: Customers are wary of opaque algorithms. A mixed-methods study from the FPA of robo-advisors found that, while users saw value in algorithmic advice, trust strongly correlated with firm reputation and transparency of operations. In finance especially, trust trumps speed. Studies consistently show that when customers sense coercion or manipulation, they hesitate or disengage.
The opportunity: Banks must embrace radical transparency. Explain how products are priced, how credit scores are evaluated, and how investment recommendations are generated. Give customers adjustable “levers” (such as sliders for fees, amortization, or risk tolerance) that restore agency and build confidence. Trust, not just convenience, becomes the competitive edge.
3. Personalization as the path to perceived value
The shift: AI makes hyper-personalized journeys possible, from spending insights to contextual nudges to targeted product offers. Yet this power comes with a paradox: personalization can delight when it feels helpful, but erode trust when it feels invasive or generic.
The opportunity: Anchor personalization in explainability. A message like “We suggested this card because you spent $X on travel last year” resonates far more than a vague “recommended for you.” Build opt-in choice architectures where customers select the dimensions they care about, whether it’s rewards, sustainability, or security. And ensure robust auditing to protect against bias and fairness risks.
4. Category nuance matters
The shift: Customers engage with AI differently depending on the product category. For commoditized offerings (savings accounts, credit cards), customers are comfortable letting AI recommend the best fit. But for high-stakes, identity-linked decisions—mortgages, retirement planning—human reassurance still matters deeply.
The opportunity: Position AI as the pre-qualification and simulation tool, and humans as the trust anchors who validate and finalize decisions. Transparency at every stage ensures customers feel empowered rather than manipulated.
5. Customer journeys are shorter and stickier
The shift: Research from BAI shows that AI recommendations are “sticky,” once a product is suggested, customers are less likely to switch. If your product isn’t in the AI-generated shortlist, it may as well not exist.
The opportunity: Banks must optimize for AI visibility just as brands once optimized for search engines. Clear pricing, standardized product comparisons, and partnerships with aggregators and digital assistants will be essential. New metrics will matter too, such as “share of shortlist” rather than “share of voice.”
6. Ethics & compliance as differentiators
The shift: Regulations like the EU AI Act and evolving privacy frameworks in Canada and beyond mean banks face increasing scrutiny over AI usage. But what looks like a constraint is actually an opportunity: responsible AI can be a powerful brand differentiator.
The opportunity: Banks should publish clear principles for ethical AI, implement transparent model governance, and provide customers with audit trails explaining why a product was recommended. Equally important: train frontline staff to articulate AI outputs in human terms. Ethical clarity becomes a competitive advantage.
The age of the fully informed customer
The mystery is gone. Margin will no longer come from complexity hidden in disclosures or asymmetry of knowledge. Instead, success in banking will depend on how effectively we engage, empower, and build trust with customers who are fully informed by AI.
At Zafin, we believe this is not a threat, but an opportunity. By embracing transparency, explainability, and ethical AI, banks can thrive in this new era of customer empowerment.
The question is no longer “What can AI do for the bank?” but “How will the bank serve the AI-informed customer?”