Architecting Growth in Latin America's Payments Ecosystem

Gonzalo Esquitino is a finance and payments executive with extensive experience in FP&A, capital markets, and data-driven strategy across Latin America. Currently serving as Business Performance & Data Science Director at Kushki, he leads the integration of analytics, finance, and technology to strengthen profitability, and strategic decision-making within the payments ecosystem.

In an interview with CIOReview Latin America, Esquitino discussed the role of standardized data infrastructure in driving growth, the importance of aligning unit economics with client strategy, and how artificial intelligence can enhance operational performance while maintaining disciplined human oversight.

A Career Built on Payments, Finance and Market Discipline

My career has always been rooted in finance, and most of it has been within the payments industry. I began in 2017 at PayPal, working in the FP&A team for Latin America. That experience was foundational for understanding how the payments ecosystem operates at scale. Even though Latin America was not the company’s core region, we managed significant volumes of transactional data, generating insights, tracking client performance, and acting as business partners to sales teams.

In that role, I worked on forecasting, budgeting, identifying risks and opportunities, supporting go-to-market strategies, and contributing to pricing discussions. We navigated complex regulatory processes in Brazil, including PIX, and supported major product expansions in Mexico, such as installment-based payment solutions. That environment strengthened my understanding of how data, regulation, and commercial strategy intersect.

After PayPal, I moved to a shopping center company with a clear objective: to support its IPO. Working across financials and investor relations, I was involved in preparing the company for public markets. An IPO demands alignment between numbers and narrative. It requires navigating regulatory requirements, engaging in roadshows, and presenting a value proposition that the market understands and trusts. That experience reinforced the importance of financial transparency, disciplined forecasting, and strategic storytelling.

Building Data Foundations as Strategic Infrastructure

At Kushki, my role centers on gathering the vast amount of information generated within the payments ecosystem and transforming it into meaningful insight. The payments market in Latin America is dynamic and competitive. New features, new players, and now AI-driven capabilities are reshaping the landscape.

The core of a payment technology company today is not simply access to real-time transaction data. It is the ability to standardize, reconcile and structure that data properly. Without a strong data foundation, decision-making becomes fragmented. When data is homologated and centralized within a robust warehouse, it supports operations, reconciliation, accounting, risk management, regulatory reporting, and analytics in a unified manner.

 ​We are in an era where prompting correctly and validating thoroughly are just as important as generating models. Innovation must be balanced with discipline. 

Building that data warehouse has allowed us to understand client behavior more deeply, evaluate product performance, and measure profitability at a granular level. Payments businesses operate with tight margins and multiple revenue streams. Understanding approval rates, processing costs, pricing alignment, and fraud exposure at the transaction level enables better commercial decisions.

Once you truly understand both client performance and product profitability, strategy becomes clearer. You can align what clients want with what creates sustainable value for the company.

Finance as a Strategic Business Partner

I strongly believe that finance and analytics should not function as downstream reporting units. The role must be strategic and integrated.

Building the right team is essential. Technical expertise in managing data pipelines is important, but it is equally important that the team understands how products work, how money flows across the ecosystem, and how margins are generated. That 360-degree perspective transforms analysis into insight.

When we launch a new product, analytics involvement begins early. We track transactional flows and user experience from day one. After launch, we monitor approval rates, merchant adoption, engagement, operational stability, and profitability. We assess whether performance aligns with pricing strategy and whether the product can scale across new segments or industries.

Understanding performance at this level allows us to export insights into forecasting models and cash flow projections. In a payments company, forecasting is not only a planning exercise. It informs liquidity management, capital structure considerations, and long-term growth planning. Accurate forecasting builds resilience in volatile markets.

A data team must therefore work closely with product and sales teams, interacting continuously rather than simply presenting dashboards. Insight should shape decisions before outcomes appear in financial statements.

Integrating AI While Preserving Accountability

Artificial intelligence has become an important tool within our ecosystem. We are developing agents capable of identifying anomalies and capturing operational risks in more automated ways. These tools support faster detection and more efficient processes.

AI also enables more accessible data consumption. Internal agents allow teams to retrieve performance information through natural language interaction, reducing reliance on complex queries and making the organization more data-driven.

However, I strongly believe in maintaining a human in the loop. AI systems can eventually produce hallucinations or misinterpret data. For that reason, we ensure that outputs are validated before being shared broadly. We dedicate time to reviewing automated procedures and verifying that results align with our financial and strategic objectives.

We are in an era where prompting correctly and validating thoroughly are just as important as generating models. Innovation must be balanced with discipline.

Path for Emerging Leaders in Fintech

For leaders aspiring to drive long-term value in fintech ecosystems, my advice is to build deep business knowledge. AI tools are powerful, but they do not replace understanding how the business really works.

Early in my journey, I invested time in learning how money flows through the payments ecosystem, understanding cost structures, identifying key players, and analyzing product mechanics. In markets characterized by tight margins and strong competition, that foundational knowledge is critical.

Strong teams make the difference. Technology amplifies capability, but human expertise determines direction. When teams combine financial literacy, product understanding, and technological fluency, they are able to design frameworks that generate meaningful value.

Ultimately, once we really understand how the business works, we are able to interpret data with clarity and create frameworks that drive sustainable growth. In a rapidly evolving Latin American payments environment, that understanding becomes the foundation for long-term success.