Intelligent CIO LATAM Issue 56 | Page 24

AI CAPABILITIES DRIVE FINANCIAL INCLUSION AND REVENUE GROWTH ACROSS LATIN AMERICA

A new executive insights report from
Dyna. Ai examines how a small number of AI capabilities are helping financial institutions across Latin America unlock revenue while scaling inclusion and managing risk. yna. Ai, a global provider of artificial

D intelligence solutions, has released a new executive insights report developed in collaboration with GXS Partners and Smartkarma, highlighting how financial institutions across Latin America are unlocking new revenue streams through a focused set of AI capabilities.

The report emphasizes that while the technology itself is increasingly proven, the true differentiator lies in the operational conditions required to scale AI from pilot projects into production-level impact.
Latin America’ s financial sector sits at the intersection of urgency and opportunity. More than 200 million adults remain outside formal financial services, while fraud risk and operational costs continue to rise.
At the same time, a young, mobile-first population has driven fintech adoption at some of the fastest rates globally, reshaping expectations for speed, accessibility and personalization.
Against this backdrop, AI is emerging as a catalyst for both financial inclusion and competitive advantage.
Rather than deploying AI broadly, the report finds that successful institutions concentrate investment on a small number of high-impact use cases. In Latin America, these center on AIdriven credit decisioning using alternative data, advanced fraud prevention in digital payments and hyper-personalized cross-selling powered by customer analytics.
Together, these capabilities are allowing banks and fintechs to expand access, protect trust and generate measurable revenue growth.
Financial inclusion remains one of the region’ s most powerful growth levers. Nearly 45 % of Latin America’ s population is unbanked – particularly in rural areas and informal sectors where individuals lack formal credit histories.
Traditional credit scoring models have struggled to reach these segments profitably, limiting
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