Financial Services

Financial institutions face three major challenges: 

- Modernization: Technology debt vs. acceleration. Banks are caught between maintaining legacy systems (think COBOL) and adopting fast-moving AI (like GPT). This dual reality compounds technical debt and slows modernization. 

- Balancing innovation and risk. AI opens the door to reinventing customer experiences, but fraud, compliance, and regulatory obligations remain guardrails that limit speed. 

- Talent and culture shift. Success hinges on bringing in new talent, upskilling existing teams, and anticipating the skills needed for tomorrow’s AI-driven industry. 

The real breakthrough is moving beyond transactional banking to become true financial advisors. With AI-powered personalization at scale, banks can tackle themes like financial health, more accurate credit scoring, or support for economic development from a new lens—while evolving their business models to deliver on that promise.

- Front office – Reinventing distribution. The rise of agents and voice banking seems inevitable, reshaping how people interact with their banks. Instead of a single app or the familiar branch, we’ll see a shift toward more fragmented and diverse channels. Branches won’t disappear, but almost every touchpoint will look radically different from today. 

- Customer experience – Building technology that delights. Banks will need to learn from other industries to design experiences that people don’t just use, but actually enjoy. Money is deeply emotional – far less rational than what we think – and in the age of agentic AI, the difference between being perceived as a trusted companion or just another utility will depend on creating experiences that connect. 

- Middle & back office – Refounding the core. To enable this shift, the middle and back office need more than incremental change. Balancing customer experience, risk, and efficiency requires new foundations: ways to assess emerging risks, processes that support hyper-personalized offers, and functions built for needs that are only starting to appear.

In the AI era, success is no longer about running pilots or experimenting at the edges—it’s about redefining what “success” means in business outcomes. That starts with measuring and understanding the baseline: knowing where you stand today, how processes perform, and where the biggest gaps/opportunities exist. With data as the compass, leaders can identify where AI creates the most meaningful impact—whether reducing risk, improving speed, or unlocking growth. Clear, outcome-driven metrics enable decisions based on evidence rather than intuition. From there, scaling AI responsibly requires strong governance, robust technology, and cultural readiness. Ultimately, success is about turning measurement into momentum—using AI not just to improve what exists, but to reimagine what’s possible. 

At Globant, we help financial institutions connect these dots: redefining success under AI, building the right foundations, and ensuring every initiative translates into trusted, scalable impact.