Google Could (GOGL34) is betting on artificial intelligence as the next driver of transformation in the financial sector. During a panel held this Thursday (28), at a company event in São Paulo, Rafael d’Ávila, Head of Financial Services at Google Cloud in Brazil, stated that banks and fintechs will need to accelerate the adoption of technology to face challenges linked to operational efficiency, customer experience and digital security.
During the presentation, the executive highlighted five of the company’s central bets for the financial market: multimodal artificial intelligence, autonomous agents, assisted search, hyperpersonalized experiences and security reinforced with AI.
“We have a very active regulator, the Open Finance system, for example, in Brazil. With money changing registrations faster and faster, we must also monitor the increase in competitiveness in the coming years. There is no more room for inefficient systems in this new scenario of increasingly faster production”, stated Rafael during the panel.
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In a round table with journalists, the executive explained that the problem is mainly in the structure of legacy systems still present in traditional financial institutions, which were built at different times and without an integrated view of the customer journey.
In practice, this means that banks still force consumers to repeat information previously provided, as the data is isolated on different internal platforms. “This ends up hindering the experience, principality and personalization”, added the Head of Financial Services.
Still according to the executive, this scenario is more common in traditional banks than in more recent fintechs, which are generally born with a more modern and customer-oriented technological architecture. According to Rafael, these newer institutions tend to find it easier to integrate data, use cloud computing and incorporate artificial intelligence into their operations.
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For professionals, the difficulty of organizing and sharing information between systems impacts not only operational efficiency, but also limits product customization and the use of Open Finance.
Security, in fact, was highlighted by Rafael as one of Google Cloud’s main concerns in the advancement of artificial intelligence within the financial sector. According to the executive, the same technology that enhances efficiency gains for companies and consumers also increases the ability of fraudsters and hackers to develop scams, exploit vulnerabilities and create increasingly convincing deepfakes.
“Artificial intelligence is available to everyone. Including those with bad intentions. At Google, we have the philosophy of combating attacks made with artificial intelligence with the use of artificial intelligence”, he revealed.
To reinforce this strategy, Google has increased investments in cybersecurity and threat detection tools in recent years. The executive recalled that the company started to reinforce its protection policies after suffering a major hacker attack more than 15 years ago — an episode that gave rise to the so-called “Aurora Project” and led the company to adopt a security model based on “Zero Trust”, in which no access is automatically trusted.
The executive also highlighted the acquisition of Israeli cybersecurity startup Wiz, announced in 2025 for US$32 billion — the largest acquisition in Google’s history. According to Rafael, Wiz was incorporated into the company’s portfolio to accelerate the detection and correction of vulnerabilities precisely at a time when AI-driven threats tend to grow. The company’s technology uses artificial intelligence agents capable of identifying security flaws during code development, before the systems are even launched.
With regard to autonomous agents, Rafael was emphatic in differentiating this new generation of tools from traditional chatbots or systems based on static responses. “Agents in this new era are assistants who act alone,” he said.
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To enable this type of solution, Google Cloud offers platforms such as Agent Studio, which allows you to create and scale agents in parallel, and the Agent Development Kit (ADK), aimed at more complex architectures. “Now it allows us to create networks, where these agents work by delegating and dividing tasks among themselves,” he explained.
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