The Next Frontier of Banking Retail

During my garden leave—when I was contractually restricted from professional activity— I participated in two transformative programs worth highlighting: Leading AI-Driven Organizations at the MIT – Massachusetts Institute of Technology and the Corporate Governance Program – Developing Exceptional Board Leaders at Columbia University. Both programs, from complementary perspectives, addressed topics such as the evolution of business, the impact of emerging technologies, state-of-the-art management and governance, as well as the challenges and opportunities ahead for corporate leadership.

Reflections on the Transformation of Banking Retail and Payments

At MIT, I explored in-depth discussions on the impact of Artificial Intelligence (AI) in banking retail and the payments industry. These reflections stemmed from analyzing how technology has progressively shaped our relationships with banks.

Looking back over recent decades, we can identify a few key inflection points in banking technology:

The Branch Customer

In my first job as a teenager, I worked as an office boy. My main tasks were visiting bank branches to pay bills and cash checks. At the time, you had to go to the specific branch where the account was registered, since the balance and signature cards were kept at the teller. Often, I had to visit several branches of the same bank on the same day. Online systems eventually ended this phase, which now seems prehistoric to younger generations.

Internet Banking and Apps

The introduction of Internet Banking, followed by mobile apps, brought banking to the customer's fingertips. This drastically reduced the need for in-person visits for everyday transactions like bill payments and transfers.

The Decline of the Physical Branch

The massive adoption of PIX (Brazilian instant payment system), the rise of fintechs and fully digital banks, and widespread use of debit and credit cards have nearly eliminated the need to visit branches for routine transactions. Unsurprisingly, we are now seeing the mass closure of bank “stores.” Just like in traditional retail, no customer traffic means, no justification to keep a physical branch open.

What’s Next? The Influence of Big Techs

Banking is undergoing another inflection point. We’re seeing a shift toward unified platforms rather than fragmentation by segments, products, or geographies. The benchmark comes from high-tech industries: Amazon, Netflix, Uber and others operate global platforms, highly customizable and heavily reliant on machine learning to deliver consistent, personalized experiences regardless of geography.

 The next frontier of banking retail is built on the fusion of data, technology, and human intelligence to deliver smoother, more reliable customer journeys 

In Brazil, neobanks lead this journey, benefiting from the absence of heavy legacy systems. However, they still lack the robustness and product portfolio compared with the traditional incumbent banks.

The Rise of AI in the Financial Sector

As in other markets, AI is the hot topic. But despite expectations, it must be said: AI is not a silver bullet. It’s a tool—a powerful one—for enhancing processes and experiences.

One of the earliest applications is Deep Learning, which has improved credit underwriting and risk assessment models. This enables greater credit volume with better precision, without increasing provisions for loan losses.

Machine Learning has the potential to revolutionize behavioral models, offering highly accurate product suggestions, cross-selling, and upselling. Imagine a client with a positive account balance, an investor profile and a consistent PIX payment history: banks could suggest suitable investments or credit lines at just the right moment.

On the other hand, financial institutions must ramp up investments in anti-fraud systems, staying ahead of AI-powered fraud techniques increasingly used by criminal networks.

The New Banking Retail Customer Experience

The most imminent disruption is the reinvention of customer service. With the closure of physical branches, the traditional channel where customers were assisted by specialists is vanishing.

While other retail sectors developed alternatives (e.g., easy returns in fashion, electronics showrooms), the financial sector now faces the challenge of remotely serving middle- and low-income populations—those who previously relied on branches as their main interaction channel.

Today, the primary scalable service alternatives are contact centers, chatbots, and banking correspondents/autonomous agents. Contact centers and chatbots generally leave consumers dissatisfied. The experience with both, across almost any sector, is frustrating. Many chatbots are unusable for entire customer segments, like baby boomers or parts of Gen Z. Meanwhile, correspondents or autonomous agents typically lack comprehensive product knowledge and are incentivized in ways misaligned with real customer needs.

“People will forget what you said, people will forget what you did, but people will never forget how you made them feel.” — Maya Angelou

GenAI and Human in the Loop

The most promising solution lies in using Generative AI agents to serve clients in real time via natural channels like WhatsApp—an interface intuitive for all generations and social classes.

Training a GenAI to act as an assistant for investments, credit, and other financial services could significantly improve service quality. However, the concept of Human in the Loop is crucial: AI should complement human work, not replace it.

With AI (and Human in the Loop), it’s possible not only to identify the most suitable investment or credit product for a customer’s situation and profile, but also to reach out at the ideal time and through the most convenient channel.

Data and Governance: Foundations of the New Era

“Data is the new oil.” — Clive Humby

Data is AI’s fuel. Implementing robust data governance strategies is essential. AI governance should be integrated into data governance, always upholding the Human in the Loop principle.

This model leads to RAI – Responsible AI: a set of principles, practices, and governance to ensure ethical, transparent, and secure AI system development and use. The central idea is to design and deploy AI that benefits people, respects human rights, promotes fairness, and avoids harm.

Conclusion

The next frontier of banking retail is under construction—built on the fusion of data, technology, and human intelligence to deliver smoother, more reliable customer journeys. And let’s be clear: companies that create AI must take responsibility for the decisions and impacts of their systems. We can’t just “blame the algorithm”