Artificial Intelligence in Brazil: AI Agents in the Financial Sector

Summary: Core Thesis, Key Insights and Strategic Recommendations

Core Thesis:
The adoption of AI agents in the Brazilian financial sector is already bringing measurable results in productivity, personalization, automation and efficiency, establishing a new level of competitiveness, scalability and digital maturity for banks, fintechs and insurers.

Key Insights:

• Leading financial institutions are reaping proven benefits such as increased productivity, cost reduction, faster negotiations and greater customer satisfaction with AI agents.
• Real cases demonstrate automation of critical processes such as debt renegotiation, customer service, credit analysis, fraud detection and offer personalization.
• The maturity of the ecosystem is evidenced by major Brazilian financial companies already operating concrete AI use cases.
• The financial sector is moving towards operational autonomy: it is estimated that, according to Gartner, by 2028, 15% of daily decisions will be made autonomously by intelligent agents.

Strategic Recommendations:

• Evaluate and prioritize critical processes for automation with AI agents, focusing on high operational impact and relationship areas.
• Structure adoption initiatives from a solid foundation of data, governance, digital integration and innovation-oriented culture.
• Track efficiency metrics, customer satisfaction and cost reduction in each new application, promoting continuous improvement cycles.
• Anticipate strategies for safe, ethical and regulated use of agents, protecting operations and strengthening customer trust.
• Promote controlled experimentation (pilots) and progressive scaling to consolidate results and accelerate competitive gain.

Real Cases: Banks, Fintechs and Insurers Transforming Operations with AI

Bradesco – BIA Assistant and RendaBra 5.0 Model

Bradesco is a pioneer with the BIA virtual assistant, which handles around 3 million monthly interactions and achieves a resolution rate of up to 90%. Implemented across multiple flows, onboarding, customer service, finance, CRM and software engineering, BIA has increased productivity and customer satisfaction. The RendaBra 5.0 model also supports segmentation, policy definition and credit decisions.

Banco do Brasil – Personalization and Automated Transactions

Banco do Brasil uses intelligent agents to suggest personalized products, achieving acceptance rates of up to 90% when there is clear explanation. The bank is a reference in using WhatsApp and Messenger for automated financial transactions with high security and encryption standards.

Banco BMG – Debt Renegotiation via AI Agents

Banco BMG adopted automation with AI agents on WhatsApp for debt renegotiation. The company achieved a 40% increase in closed agreements and a 79% conversion rate on issued slips, combining automated service with the option of human interaction, with a significant reduction in operational costs.

AXA XL – Insurance Management and Intelligent Claims Forecasting

AXA XL employs AI for predictive analysis and reserve management, anticipating claims trends. Intelligent agents proactively inform brokers and clients, improving loss prevention and insurance solution customization.

Recovery and Telecom – Automated Collection and Credit Recovery

Collection and telecom companies used trained agents to negotiate debts through digital channels. The result: over 10% increase in credit recovery, 30% reduction in collection costs and greater customer satisfaction with personalized service.

Market Indicators and Future Trends

• Financial institutions report significant reduction in critical process time with super AI agents, improving precision in risk analysis and compliance.
• According to IDC, 90% of major financial corporations already have real AI cases deployed, consolidating the sector’s maturity.
• The expectation is that by 2028, autonomous agents will account for at least 15% of daily decisions in major institutions, driving a new standard of productivity, innovation and regulatory adaptation.

Conclusion

The implementation of AI agents ceases to be a trend to become a competitive reality in the financial sector. Success cases prove significant gains in automation, cost reduction, personalization and governance. Organizations that invest in data, integration and digital culture are better positioned to lead, and accelerate, the next phase of the financial market, increasingly autonomous, secure, efficient and resilient.

About the Author

Rodrigo Bornholdt is Co-founder and Chief Technology Officer at Zappts, specialized in Software Architecture and Artificial Intelligence, with solid experience leading technology teams, developing complex systems and innovation applied to business strategies.

About Zappts

Zappts is a Brazilian technology and innovation company that for over 10 years has been creating, modernizing and evolving secure and scalable digital solutions for large organizations. Combining practical experience in software engineering, data and artificial intelligence, it integrates technology, methodology and processes accelerating value delivery with efficiency, quality and governance. Its scope goes from strategy to software application development and artificial intelligence, being a reference in Brazil on the topic of intelligent agents, always oriented towards the impact on the business results of its clients and partners. Click here to learn more.