Your customers have a new financial advisor. It is not you.
"What should I do with my money?"
This question is being asked hundreds of millions of times a month by your customers. Increasingly, the answer is not coming from a bank, a credit union, a fintech, or a financial advisor. It is coming from a chatbot.
This shift is compounding as the number of LLM and financial institution partnerships increases. In the first 3 months of 2026 we have seen Perplexity partner with Plaid to deliver personalized portfolio management and Anthropic expand its relationship with LPL to reach 30,000 advisors.
To understand what these partnerships mean for community financial institutions and fintech, it is important to first understand what your customers are actually looking for. We dug into that below and spotlight what is on the horizon.
The scale of what is already happening
This is not a future scenario. It is already in market at enormous scale.
According to a 2026 BestMoney study, 58% of Americans are now turning to AI for financial guidance, making it the second most common use case for AI overall, behind only health and wellness. A 2024 BMO Real Financial Progress Index survey of more than 2,500 American adults found that more than a third of Americans are already using AI to manage their finances and investments. Among Gen Z, that number reaches 61%.
These are not lookup queries. These are planning conversations happening entirely outside of any regulated, institution-aware channel.
ChatGPT alone processes roughly 2.5 billion prompts per day. The number of monthly financial guidance interactions occurring without institutional involvement runs well into nine figures. Every month. Growing.
Three questions that reveal the shift
The same three question clusters surface every time. No single authoritative dataset exists because LLM providers treat topic-level prompt data as proprietary. But the pattern holds across consumer surveys, academic field studies, and a five-minute prompt into any major LLM. Try it yourself.
01 Cash flow and budgeting
"How much should I save versus spend?" "Can you build me a monthly budget?" "How do I stop living paycheck to paycheck?" A 2025 LendingTree survey of 2,000 U.S. consumers found that budgeting is the single most common financial decision category influenced by AI, cited by 33% of users. This category dominates because it is immediate, emotionally charged, and recurring. Every month, the question resets. It is also the category where banks have historically provided the least guidance. You could open an account and never once receive advice on how to actually use it.
02 Wealth building and investing
"Where should I invest $10,000?" "Should I buy stocks, ETFs, or real estate?" "How do I build wealth?" This category used to belong to financial advisors and wealth managers. It is now on-demand, conversational, and free. A 2026 BestMoney study found that 64% of Americans who use AI for financial guidance say investing tops their list. What was once gated behind a minimum balance or an advisor relationship is now a three-second prompt.
03 Contextual decision-making
"Should I pay off debt or invest?" "Can I afford this house?" "Should I refinance my loans?" These are the highest-stakes questions in the category. They require synthesis of someone's full financial picture, not just data retrieval. They historically required a banker, an advisor, or hours of personal research. AI is increasingly acting as the decision layer here, not just an information source.
The meta-pattern across all three is the same...
Your customers are not asking for products. They are asking for decisions.
Consumers are not "give me a savings account." But "what should I do with my money?" Banks have long owned accounts, transactions, and products. However, these questions sit above that layer entirely.
- Budgeting is a behavior question
- Investing is a strategy question
- Contextual decisions are cognitive questions
That is exactly where AI is winning, and exactly where most financial institutions have no presence.
Perplexity just raised the stakes
In March 2026, the competitive pressure intensified in a way that should remove any remaining doubt about the direction of travel.
Perplexity upgraded its finance platform with a Plaid integration that allows users to directly connect brokerage accounts and query their actual holdings, balances, allocation drift, and risk exposure in plain language. The platform now has access to more than 40 live finance data tools pulling from the SEC, FactSet, S&P Global, LSEG, and Coinbase.
A December 2025 Harvard-led field study drawing on hundreds of millions of anonymized Perplexity user interactions found that financial services workers showed disproportionately high agent adoption on the platform, with investment analysis among the top tasks. According to Perplexity, over 75% of its paying users engage with finance features on a monthly basis.
As Plaid's GTM AI lead wrote announcing the partnership: this marks a shift toward "intelligent finance, where your data doesn't just sit in an app or static interface, it informs AI experiences designed to respond to you."
AI is not waiting for financial institutions to build a better interface. It is routing around them, one decision question at a time.
What's on the Horizon
The wave of LLM and financial institution partnerships is not slowing down. What started as headline news is becoming table stakes. Financial institutions and fintech companies actively engaged in staying ahead of this shift are building the infrastructure to meet customers where they already are, with guidance that is personalized, compliant, and held to a fiduciary standard.
Quinn is one of those solutions. Built entirely on proprietary in-house models and registered as a fiduciary, Quinn gives institutions a guidance layer that keeps customers engaged inside the relationship rather than routing to a general-purpose chatbot with no stake in their outcome.
The community financial institutions, banks, and fintech firms that get this right will not just retain customers. They will deepen the relationships that matter most.