Why isn't investing more in technology solving the financial sector's problem?

The banking sector is about to break a new record in technology investment. And yet, most financial institutions admit that transformation is not going as planned. This contrast between the volume of capital allocated and the actual capacity to execute is the starting point for understanding what truly separates banks that move forward from those that get stuck in endless modernization cycles.

The largest technology budget in the private sector

In 2026, Brazilian banks are expected to invest R$50.4 billion in technology, an 8% increase from the R$46.8 billion invested in 2025, according to the 34th edition of the Brazilian Banking Technology Survey (Pesquisa Febraban de Tecnologia Bancária), conducted with the support of Deloitte. This figure is not isolated: in the last five years, the sector's IT budget has grown by 58%, consolidating the banking sector as the private segment that invests the most in technology in the country.

This volume of capital is not being directed solely to keep the lights on. It reflects a race for competitive relevance in a market where the line between bank and technology company has practically disappeared after the emergence of fintechs.

Where the money is going

Three fronts concentrate the largest share of new investments: artificial intelligence (generative and traditional), cloud infrastructure, and cybersecurity. It's no coincidence that these three areas appear side-by-side in the most recent sector reports because, in practice, they are interdependent. There is no AI at scale without a mature data infrastructure, and there is no modern infrastructure without a robust security layer.

The growth in technical teams confirms this trend: 42% of financial institutions plan to expand their technology teams in 2026, with an expected average increase of 22% in staff. At the same time, the sector has already trained 226,000 professionals in technology and cybersecurity in the last year alone, evidence that transformation is no longer an IT project but has become an agenda for the entire organization.

The most common symptom: fragmented pilots

The KPMG Global Tech Report 2026, which surveyed 2,500 technology executives in 27 countries (150 of them in Brazil), helps explain why there is still a gap between the appetite for innovation and the ability to convert these investments into results.

Practically all Brazilian companies interviewed have already implemented some level of automation and AI, including agentic AI. The problem is not adoption, it's integration. 45% of Brazilian executives state that their organizations maintain multiple AI projects operating disconnectedly, without a robust technological platform to support them.

Instead of a cohesive strategy, what many institutions have is a collection of isolated experiments, each with its own data, its own architecture, its own owner. It's a pattern that consumes budget without generating the expected return, and which can only be resolved with structural decisions about data, platform, and engineering, not with yet another AI pilot.

It is this type of fragmentation that approaches like Genius AI Modernization, from Squadra, were designed to solve, not as another isolated pilot, but as a continuous and flexible journey of evolution, ranging from mapping legacy architectures and extracting hidden business rules to agentic operation, with autonomous intelligent agents acting end-to-end. In practice, this means that migrating, modernizing, and evolving cease to be disconnected projects and become part of the same journey supported by a single data and architecture base.

The growing parallel pressure: fraud and cybersecurity

While banks race to modernize, the risk environment is also changing rapidly. According to data from the Central Bank presented at Febraban SEC 2026, cyber incidents in the National Financial System grew by 29% in 2025 compared to 2024, while cases classified as fraud jumped from 9 to 39 in the same period.

The aggravating factor is that AI itself is being used by criminals to create fake documents, simulate voices, and produce increasingly convincing deepfakes. This shifts the discussion: fraud protection is no longer an isolated detection layer but directly depends on the reliability of the entire systems architecture that supports financial operations.

This is why solutions like the Genius AI anti-fraud funnel, from Squadra, combine over 12 pre-trained AI models, merging computer vision and behavioral analysis to make decisions at millisecond scale during digital onboarding and financial transactions. Instead of static rules that create friction for legitimate customers, intelligent risk orchestration dynamically adjusts approval flows according to the risk level of each operation, reducing false positives and maintaining full compliance with LGPD.

What separates those who invest from those who execute

Putting the pieces together, a pattern emerges: the money is available, the competitive pressure is real, and technology has already proven its value in specific cases. What is missing, in most institutions, is not appetite, but a technical foundation solid enough to support this ambition at scale: mature data architecture, modern engineering, and a modernization strategy that does not treat legacy, AI, and security as separate fronts.

It is precisely at this point that Squadra has been working alongside financial institutions in recent years, supporting banks and companies in the sector with legacy system modernization projects, software engineering, and digital platform evolution.

If your institution is facing the same dilemma – budget approved, ambition defined, but execution stalled – it's worth a conversation with those who have been through it. Talk to our specialists.