Banking transformation in action: Banco do Brasil

As part of the Qorus-Infosys Finacle Banking Innovation Awards 2026, we selected a few of the banks whose projects impressed us the most. Among them, Banco do Brasil in Brazil presented the incredible transformation work they have accomplished.


What transformation strategy has your organization led in recent years?

Banco do Brasil has led a structural transformation to become an AI-enabled and governance-led organization, repositioning data and artificial intelligence as core drivers of its business and operating model.

The strategy moves beyond digitalization by establishing an integrated system that connects enterprise data platforms, generative AI capabilities, and institutional governance mechanisms, enabling scalable and responsible AI adoption. This approach embeds AI into critical domains such as risk, pricing, legal operations, and customer management, while ensuring reliability and compliance at scale.

Simultaneously, the bank redesigned its operating model by aligning leadership development, experimentation, and solution delivery, transforming AI from isolated expertise into an organizational capability.

This transformation also reshapes culture and workforce, enabling leaders to make consistent, data-driven decisions and orchestrate cross-functional execution, positioning Banco do Brasil as a coordinated, enterprise-scale AI innovation system.


What prompted this strategic transformation?

This transformation was prompted by the need to respond to a more complex, data-intensive, and highly regulated financial environment. Banco do Brasil faced growing pressure to make decisions faster and more consistently across diverse business areas, while reducing manual effort, operational risk, and fragmented use of data and AI.

At the same time, generative AI created new opportunities to improve productivity, customer experience, risk management, and business performance, but also introduced challenges related to reliability, explainability, security, and compliance. Scaling AI without a structured model could increase inconsistency and reputational exposure.

The leadership team therefore initiated a long-term transformation to turn data and AI into coordinated organizational capabilities, supported by governance, workforce readiness, and responsible adoption mechanisms, ensuring that innovation could scale with trust, control, and measurable business value.