Author: Charitarth Sindhu, Fractional Business & AI Workflow Consultant
AI super-apps are changing where financial conversations start. Over half of Americans have already asked AI super-apps like ChatGPT for financial advice, according to a University of Illinois study. Meanwhile, J.D. Power found that 51% of consumers now turn to AI for financial guidance. The shift is not coming. It is here.
So we asked six industry leaders a simple question. Will AI super-apps reduce banks and fintechs to invisible back-end infrastructure? And if that risk is real, how should financial institutions respond?
Their answers reveal a consistent theme. The threat is genuine, but structural advantages in regulation, liability, and trust give banks a fighting chance. However, only if they act now.
AI Super-Apps Are Reshaping Where Money Decisions Happen
The generational divide tells the story clearly. Experian data shows 67% of Gen Z and 62% of millennials use AI super-apps for personal finance tasks. By contrast, only 28% of boomers do the same. Furthermore, PYMNTS Intelligence reports that 37% of power users have made AI their primary finance tool.
OpenAI is not stopping at advice, either. ChatGPT launched Instant Checkout in 2025, powered by the Agentic Commerce Protocol co-developed with Stripe. PayPal then integrated its 400 million user wallets into the platform. Visa now processes AI-initiated transactions. In addition, shopping queries on ChatGPT grew 70% in the first half of 2025.
These moves signal that AI super-apps want to go far beyond answering questions. They want to act. And as we explored in Your Next Customer Might Not Be Human, agentic commerce is already reshaping how SMEs think about payments and customer interactions.
Yet the gap between advising and acting is exactly where banks hold their strongest position.
Even though the mega models like ChatGPT can scan a consumer’s bank statements and give advice, what they cannot do is act on that advice. That includes moving money, accepting credit, making trades, or most importantly, assuming financial liability. Banks and fintechs won’t outsource this decision-making or money movement to a third-party AI anytime soon. Their own regulatory and liability risk is too high. The more likely scenario is that banks and fintechs will have AI agents and chatbots inside their own apps and channels, where they control governance, data, permissions, and actions on a consumer account.
- Maya Mikhailov, CEO, Savvi AI
Maya raises the point that every expert we spoke with circled back to. AI super-apps can analyse statements, compare products, and recommend strategies. But moving money, underwriting credit, and assuming financial liability remain firmly inside the regulatory perimeter.
AI super-apps are changing where financial conversations begin. Many people now start by asking an AI assistant to explain spending patterns, compare options, or interpret documents like bank statements. This does not necessarily eliminate banks or fintech platforms, but it does shift where customer relationships are formed. If users increasingly interact through AI interfaces, financial institutions risk becoming invisible infrastructure. In that scenario, their products still power the system, but the AI layer owns the user experience and the trust built through daily interaction. The real issue is not whether banks become APIs. Instead, the issue is who controls the interface where decisions happen. When the interface becomes intelligent and conversational, the organisation that guides the conversation often shapes the outcome.
- Ahad Shams, Founder, Heyoz
Ahad’s framing highlights a subtle but important distinction. AI super-apps do not need to replace banks to disrupt them. They simply need to own the moment where customers make decisions.
AI Super-Apps Face a Regulatory Wall That Still Favours Banks
Regulation remains banking’s deepest structural advantage. Banking charter requirements, capital adequacy standards, and KYC obligations create barriers that no technology company can easily sidestep. On top of that, the EU AI Act now classifies AI-driven credit scoring as high-risk. It demands conformity assessments, bias testing, and human oversight. Penalties reach €35 million or 7% of global turnover.
The liability framework reinforces this moat further. The SEC fined WealthTech Advisors $4.8 million for failing to supervise AI suitability determinations. The message is clear. Automated advice does not absolve the deploying firm of fiduciary responsibility. As a result, banks have a powerful structural incentive to deploy their own AI rather than defer to third-party platforms. This tension between AI automation and human expertise in regulated finance remains one of the defining challenges for the sector.
AI super-apps will pull more financial decision-making into the chat layer. However, I don’t think banks and fintechs become mere pipes unless they let the customer relationship migrate away. The defensible moat remains regulated capabilities and balance-sheet trust: identity and KYC, custody, payments rails, credit underwriting, fraud, dispute handling, and compliance. In practice, whoever owns consented data access and the last mile UX can repackage these services. That’s the real risk. The response is to treat AI as a distribution and risk-control layer, not a novelty feature. Build secure bank-hosted copilots that keep raw statements inside a governed environment. Use fine-grained permissions, redaction, and audit logs. Then publish clear policies on data retention and model training. Banks should also expose high-quality, well-documented APIs with explicit consent and liability boundaries. After that, compete on outcomes: faster dispute resolution, better fraud detection, clearer fee transparency, and personalised guidance tied to real product actions.
- Hans Graubard, COO and Cofounder, Happy V
Hans correctly identifies the dual nature of the threat. AI super-apps gain power when they control data access and the user experience. But regulated capabilities like custody, fraud detection, and dispute handling remain hard to replicate outside the banking system.
AI super-apps will absolutely push banks and fintechs toward being interchangeable infrastructure for the parts that can be standardised: balances, payments, transfers, statements, KYC. If the primary user experience moves to an AI layer, the brand that wins is the one that controls context and trust. The bank risks becoming a utility unless it offers something AI can’t easily commoditise: better pricing, faster underwriting, smarter risk decisions, or privileged data-sharing agreements. The constraint isn’t just product. It’s governance. Users uploading statements into general-purpose AI creates privacy and liability issues, so regulated institutions still have an advantage if they can offer comparable AI help inside a compliant perimeter. Banks should respond by building an API-first platform plus an owned experience that’s safe to use: explicit consent, audit trails, redaction, and clear boundaries on what the assistant can do. Fintechs should differentiate by packaging domain workflows like cash-flow forecasting, bill negotiation, and dispute handling rather than just access to an account.
- Igor Gobrko, Developer and Founder, TwinCore
Igor extends this into the technical layer. Banks that treat AI super-apps as another client over well-designed services can maintain control. Similarly, fintechs that package domain-specific workflows rather than raw account access create defensible value that AI platforms cannot easily replicate.
AI Super-Apps: How Banks and Fintechs Should Respond Now
The convergence of open banking, embedded finance, and AI super-apps creates both threat and opportunity. The CFPB’s Section 1033 rule mandates that banks share consumer-authorised data through secure APIs. This regulation essentially hands AI super-apps the keys to financial data. But it also lets banks position themselves as trusted infrastructure partners.
McKinsey estimates that banks risk losing $170 billion in annual profits if they fail to adapt their business models. Consequently, the firms that thrive will pursue a dual strategy. First, expose clean APIs so AI super-apps can surface banking services inside the conversation. Second, build proprietary AI interfaces that leverage regulatory positioning, customer data, and fiduciary accountability.
The privacy dimension adds urgency, too. Harmonic Security’s 2025 analysis of 22.4 million prompts found that ChatGPT accounted for 71.2% of all sensitive enterprise data exposures. Banks that offer AI-powered advisory within their own regulated, auditable environments hold a meaningful value proposition. In fact, Accenture found that 71% of consumers would welcome an AI assistant within their primary bank’s mobile app.
We’re building GiaAI right now, so I watch this space closer than most. The banks that win won’t be the ones with the best rates or the slickest app. They’ll be the ones that show up where the conversation starts. And right now, that conversation starts inside ChatGPT for a growing chunk of consumers. It’s the same pattern we see in SEO every day. Google didn’t kill businesses. But businesses that ignored where people were searching absolutely got killed. Banks need to think about AI visibility the same way a local tradie thinks about showing up on Google. If you’re not in the conversation, you don’t exist. The good news for fintechs is that most of them are already built on APIs. They’re closer to being AI-ready than the big four banks will ever be. The risk isn’t becoming a back-end pipe. The risk is being a back-end pipe that nobody bothers to connect to.
- Callum Gracie, Founder, Gia AI
Callum draws a parallel that resonates with any business owner who has navigated digital visibility. AI super-apps function as a new search layer. If banks do not show up where the conversation happens, they lose relevance regardless of how good their products are.
I built Remotify to solve a specific problem: getting freelancers paid across borders without the headaches. So when people ask whether AI super-apps will turn fintechs into invisible plumbing, my honest answer is that for payments infrastructure, we’re already plumbing. And that’s fine. The question is whether you’re commodity plumbing or specialised plumbing. ChatGPT can tell a freelancer in Portugal how to invoice a client in Texas. What it can’t do is move that money, handle DAC7 reporting, manage withholding across three jurisdictions, or take on the compliance liability when something goes wrong. Those are regulated, high-trust functions. No AI assistant is assuming that risk anytime soon. Where I do see genuine disruption is in the advice layer. Freelancers already ask ChatGPT about tax obligations before they ask their accountant. That’s a shift in the entry point, not a shift in who does the work. For fintechs like ours, the play is straightforward. Build clean APIs so AI tools can surface your services inside the conversation. Then compete on the things AI can’t fake: speed of settlement, compliance rigour, and the willingness to sit on the regulated side of the table when real money moves.
- Hasan Can Soygok, Founder, Remotify
Hasan brings the perspective of a founder who already operates in the plumbing layer. For specialised fintechs, AI super-apps do not eliminate value. Instead, they redistribute it. The winners will combine clean API infrastructure with the compliance rigour that AI platforms cannot provide on their own. His point about DAC7 is especially relevant. As we covered in How DAC7 Changed Freelancer Payments, the regulatory burden of multi-jurisdiction tax compliance is precisely the kind of specialised work that AI super-apps are not equipped to handle.
The bottom line is straightforward. AI super-apps won’t kill banks or fintechs. But they will render invisible any institution that fails to show up where financial decisions now begin. The institution that explains the decision will matter more than the one that processes it. And right now, AI super-apps are doing most of the explaining.