Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry?

I’m a digital risk and fraud prevention expert with 18 years of experience across Latin America. Recently I've served as Director, LAC Issuing Risk Service Solutions at Visa for almost two years leading regional initiatives to strengthen fraud prevention frameworks for issuing banks and fintech partners.

Previously, I spent over a decade at Mercado Libre, where I specialized in fraud prevention, AML and risk management for one of the largest e-commerce and fintech ecosystems in the region. My background also includes leadership roles in other fintechs and paytechs, driving product strategy, compliance, and digital transformation.

This combination of legal training and hands-on industry expertise allows me to help organizations design user-centric, compliant, and fraud-resilient solutions—grounded in Latin America’s unique regulatory, cultural, and technological landscape, where innovation and compliance evolve in parallel, and trust is a critical asset.

Q2. How is AI transforming fraud detection and prevention in Latin American digital payments?

AI has been used in fraud prevention across Latin American fintechs for over 15 years, especially through machine learning. The current shift lies in the evolution of technology—not in its adoption—and in how generative AI may enhance or complicate well-established models.

The region’s core challenges are strategic: fragmented regulation between banks and fintechs, the need for solid yet non-invasive KYC, and a regulatory framework that is still evolving. In many cases, tech firms are setting the standards ahead of regulators.

Common hurdles include detecting synthetic identities, managing legitimate but complex use cases (like multi-branch businesses), and modeling the behavior of underbanked users.

While mobile devices already apply generative AI, many financial institutions are still catching up. The opportunity lies in integrating AI with strategic foresight, ethical design, and scalable execution, especially in an environment where innovation often moves faster than regulation.

Q3. What is the projected market size and growth rate for AI-powered fraud prevention platforms in Latin America?

The adoption of AI-powered fraud prevention tools in Latin America is expanding steadily, though unevenly. Many issuers rely on tools provided by card networks or prebuilt solutions, with varying levels of internal expertise across countries. Among merchants, only large ones purchase fraud solutions directly.

However, a large portion of the market—especially small and medium merchants—accesses fraud detection capabilities indirectly, through fintechs and paytechs. If these providers choose to granularize and scale their AI-based tools in-house, their reach could significantly increase the effective penetration of such technologies.

Therefore, market growth will likely accelerate through embedded fraud prevention in digital financial products rather than individual enterprise sales. This dynamic favors player who can integrate AI into scalable, compliant, and user-friendly platforms, amplifying reach without relying on deep in-house expertise on the client side.

Q4. What is the scale of financial losses tied to payment fraud in Latin America, and how fast is demand growing for AI-driven anti-fraud solutions?

Global card networks aim to keep fraud rates below 10 basis points of total volume. Still, in Latin America, actual benchmarks vary by country and payment method, ranging between 10 and 18–20 bps depending on the ecosystem’s maturity and depending on transaction type (card present/card not present payments).

Rather than just focusing on minimizing losses, the current push is toward building trust and maintaining approval rates. Issuing banks, in collaboration with card networks and regulators, are implementing increasingly robust authentication systems—leveraging device biometrics and dynamic 2FA to enhance security without adding friction.

Meanwhile, many merchants—particularly SMEs—rely on the advanced fraud controls provided by fintechs and paytechs, benefiting from their evolving AI-driven platforms.

Demand for these solutions is accelerating, driven by the need to balance fraud prevention with seamless user experience across diverse and complex digital payment journeys.

Q5. Which fintechs, paytechs, and banks are setting benchmarks in digital fraud prevention, and what partnerships are enabling innovation?

In Latin America, digital-native fintechs and paytechs are leading fraud prevention innovation by embedding real-time, AI-driven controls into their products. As announced publicly, Pomelo partnered with FICO to offer advanced fraud detection as a service to banks and fintechs in the region. 

On the data side, Experian’s publicly announced acquisition of ClearSale reinforces the strategic importance of e-commerce fraud prevention and local expertise at scale.

Likewise, as announced publicly, Visa acquired Featurespace, integrating adaptive AI into its ARIC Risk Hub and making real-time fraud detection tools available even beyond its traditional network. These alliances highlight a clear trend: innovation is being driven by collaborative ecosystems where global technology meets regional execution. The benchmark is no longer a single player, but a model of shared intelligence, embedded infrastructure, and scalable trust across the payment chain.

Q6. What product features or integrations are fintechs prioritizing to address fraud while supporting seamless, inclusive financial access?

Fintechs in Latin America are prioritizing features that reduce fraud while enabling inclusive and seamless digital access. 

Biometrics—especially via mobile devices—is gradually becoming a standard for user verification, although mobile hardware adoption is still uneven across the region. To bridge this gap, banks, fintechs, and merchants are beginning to combine biometric tools with strong 2FA, device fingerprinting, and identity validation through public data sources. This layered approach helps strengthen the “Persona ID” beyond traditional credentials, enabling better fraud detection without excluding users.

Additionally, adaptive risk segmentation allows lower-friction experiences for low-risk profiles while maintaining stronger controls where needed. APIs with embedded fraud detection also help extend security benefits to smaller merchants who lack dedicated resources.

The focus is shifting toward building trustable, identity-centered user journeys that support both safety and inclusion, recognizing that in Latin America, the challenge is not only catching fraud, but doing so without creating barriers to financial participation.

Q7. If you were an investor looking at companies within the space, what critical question would you pose to their senior management?

• How does your fraud prevention model scale economically as your customer base grows? 
• Specifically, what portion of your cost structure is driven by data storage, model training, and authentication services, especially those provided by third parties?
• I’d want to understand whether the company has visibility and control over these recurring infrastructure costs, and whether they are passed on to clients, subsidized, or absorbed
• I’d also ask how the fraud stack aligns with your customer segments: are you offering enterprise-grade protection to small businesses with thin margins? How do you adapt the model to keep both risk and costs balanced across verticals and markets?
• Finally, I’d look at your roadmap: are you relying on generative AI as a value-add, or is it core to your efficiency? And how are you building cybersecurity fundamentals to ensure operational trust as you scale?