The world’s largest banks are investing billions of dollars to bring artificial intelligence to the center of every operational process. It’s a structural transformation already underway with numbers that speak for themselves.
According to multiple international sources, Wells Fargo has trained 90,000 employees on artificial intelligence and distributed AI tools across 180,000 corporate desktops.
Citigroup has freed 100,000 weekly hours of work in the technology division alone thanks to automation—a figure announced directly by CEO Jane Fraser during the October 2024 analyst call.
JPMorgan Chase has launched its own internal platform LLM Suite—going from zero to 200,000 users in eight months—which is used by developers to review code, by investment bankers to prepare presentations, by lawyers to analyze contracts and, more recently, to automate the drafting of internal performance reviews.
JPMorgan’s technology budget for 2025 is $18 billion, of which approximately $1.3 billion dedicated exclusively to AI development. According to MarketsandMarkets, the global value of AI in financial services is set to grow from $38 billion in 2024 to over $190 billion by 2030.
Extraordinary numbers. A real, rapid, irreversible transformation.
And with two very different faces depending on which side you’re on.
The first face: for banks, AI is pure efficiency
For banking institutions, artificial intelligence represents the opportunity to do the same thing—or much more—with fewer resources. Processes that required weeks of human work are completed in hours. Decisions that required complex manual analysis are delegated to algorithms that don’t get tired, don’t make mistakes due to distraction, and don’t cost like a team of specialists.
Citigroup completed 220,000 automated software code reviews thanks to internal AI tools. Wells Fargo is rethinking entire operational models by building AI agents capable of interacting with each other to execute complex banking operations. JPMorgan reduced response times during market volatility by 95% thanks to its AI coaching tools.
For banks, this is AI’s fulfilled promise: lower costs, more scale, less human error. A more efficient banking system from the inside.
The second face: for the international client, AI is an increasingly rigid filter
What is optimization inside banks becomes a wall from the outside.
Every account opening request, every application, every profile presented to a banking institution today passes through automated systems designed for one thing: minimize the bank’s reputational and compliance risk. The algorithm analyzes the profile, compares it with predefined parameters, and produces an assessment. In seconds.
The problem is that algorithms don’t reason in nuances. They’re trained on historical data and standard profiles. They know what’s “normal” for the bank that programmed them: a client resident in the bank’s country, with traceable income in that jurisdiction, with a linear and understandable corporate structure.
Those who don’t fit this scheme are categorized as complexity. And complexity, for a banking risk management algorithm, equals risk.
Resident in Dubai with an American company and clients in Europe? Complexity. Holding in one jurisdiction, tax residency in another, operations in a third? Complexity. Entrepreneur with cash flows from international markets and perfectly legal multi-jurisdictional structure? Complexity.
The algorithm doesn’t assess whether the situation is legitimate. It doesn’t ask for explanations. It doesn’t want to understand. It sees a profile that deviates from standard parameters, classifies it as potential risk, and rejects—or ignores—the request. Without explanations, without possibility of appeal, without a human being on the other side to turn to.
This is the paradox of banking AI: the more efficient banks become internally, the more inaccessible they become externally for those who don’t fit standard parameters.
A recognized but still unresolved problem
The phenomenon is documented enough to have prompted European regulators to intervene normatively.
The European AI Act (EU Regulation 2024/1689, in force since August 2024) has classified AI systems used to assess the reliability of natural persons in accessing financial services as “high-risk” systems—a category that imposes specific obligations of transparency, traceability and human supervision. From 2026, banks will no longer be able to treat their assessment algorithms as black boxes: they’ll have to explain their decisions and ensure that a human supervises the process (Bank of Italy).
The reason why legal intervention was necessary is exactly this: algorithms structurally penalize those with “thin” or complex financial history.
An international entrepreneur with significant wealth, articulated corporate structure and cross-border operations is often treated worse—by the algorithm—than an employee with local paycheck and bank account in the same country as the bank.
Not because they’re riskier. But because they’re harder to categorize.
It’s precisely in this context that one understands why GloboBanks operates exclusively through direct relationships with banking institution management—not by filling out online forms or going through automated channels.
When a client is introduced by GloboBanks, they’re not evaluated by an algorithm. They’re presented by a partner the bank knows, trusts, and who has already qualified the profile.
If you want to understand which approach fits your structure, you can schedule a free consultation with one of our experts.
While the public door automates, the private one becomes more valuable
There’s a dynamic that’s almost never openly discussed, but which those who work in the international banking sector know well.
As public access channels to banks—websites, online applications, digital forms—become increasingly automated and filtered by algorithms, the distance between those who manage to open accounts at high-level institutions and those who can’t widens based on how you arrive at the bank.
Those who arrive through a direct channel—an introducer who has an established relationship with the bank’s management, who has already performed their own due diligence on the client and vouches for the profile—completely bypass the algorithmic filter. They don’t go through the digital counter. They go through the private door.
The bank thus sees a pre-qualified client, presented by a trusted partner, with whom the bank has a relationship built over time. A client who brings with them an implicit guarantee: that of whoever introduced them.
This mechanism isn’t new. But AI has made it exponentially more important. Because as algorithms become the primary filter for new clients, having access to a channel that bypasses that filter stops being a competitive advantage and becomes a structural necessity for those with a complex international profile.
Relationships built on a contractual basis
GloboBanks is a strategic banking introducer with formal contracts with over 60 international institutions in more than 10 jurisdictions—from the United States to Switzerland, from Singapore to Panama. Relationships built over years of work in the field: dinners with bank management, direct relationships, mutual trust consolidated over time.
This means that clients GloboBanks introduces to institutions are not analyzed by an automated system. They’re presented by a partner the bank knows. The bank knows that profile has already been qualified. Knows that whoever presents it vouches for them. And this radically changes how the banking relationship takes shape—from account opening to ordinary management, with a dedicated relationship manager who knows the client, available when needed, in person.
While the banking world automates, the value of this type of access grows. Not because banks become less secure or less serious—quite the contrary. But because the algorithmic filter, however sophisticated, will never be able to assess the reality of those who have built wealth and structures in multiple countries around the world.
Want to know if your structure is compatible with high-level banks?
Every month GloboBanks opens banking relationships for international clients, even 100% remotely.
During a free consultation with a GloboBanks expert you can concretely understand:
- Which institutions—with specific names and jurisdictions—are accessible based on your corporate structure and residency
- How the introduction is managed and what the bank expects in terms of documentation and due diligence
- Whether your current profile is compatible with the desired type of banking relationship, and what to potentially optimize
- How long it’s realistically possible to have the account operational, entirely remotely
The consultation is free and without obligations.
For those with a complex international structure—or building one—it’s the most direct starting point.
→ Book your free consultation with a GloboBanks expert
