{"id":18954,"date":"2026-02-03T11:44:26","date_gmt":"2026-02-03T11:44:26","guid":{"rendered":"https:\/\/www.intelligentcio.com\/latam\/?p=18954"},"modified":"2026-02-03T11:44:26","modified_gmt":"2026-02-03T11:44:26","slug":"ai-capabilities-drive-financial-inclusion-and-revenue-growth-across-latin-america","status":"publish","type":"post","link":"https:\/\/www.intelligentcio.com\/latam\/2026\/02\/03\/ai-capabilities-drive-financial-inclusion-and-revenue-growth-across-latin-america\/","title":{"rendered":"AI capabilities drive financial inclusion and revenue growth across Latin America"},"content":{"rendered":"\n

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.<\/em><\/p>\n\n\n\n

Dyna.Ai, a global provider of Artificial 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.<\/p>\n\n\n\n

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.<\/p>\n\n\n\n

Latin America\u2019s 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.<\/p>\n\n\n\n

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.<\/p>\n\n\n\n

Against this backdrop, AI is emerging as a catalyst for both financial inclusion and competitive advantage.<\/p>\n\n\n\n

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 AI-driven credit decisioning using alternative data, advanced fraud prevention in digital payments and hyper-personalized cross-selling powered by customer analytics.<\/p>\n\n\n\n

Together, these capabilities are allowing banks and Fintechs to expand access, protect trust and generate measurable revenue growth.<\/p>\n\n\n\n

Financial inclusion remains one of the region\u2019s most powerful growth levers. Nearly 45% of Latin America\u2019s population is unbanked – particularly in rural areas and informal sectors where individuals lack formal credit histories.<\/p>\n\n\n\n

Traditional credit scoring models have struggled to reach these segments profitably, limiting access to lending and constraining economic participation.<\/p>\n\n\n\n

AI is changing that equation. By incorporating alternative data such as utility payments, mobile usage, rental histories and behavioral indicators, financial institutions can now assess risk more accurately for thin-file and first-time borrowers.<\/p>\n\n\n\n

Machine Learning models analyze patterns at scale, enabling faster decisions while maintaining credit discipline.<\/p>\n\n\n\n

Early adopters are already demonstrating the impact. In Mexico and Brazil, Fintech lenders using AI-based underwriting have processed billions of dollars in loan applications from customers without traditional credit records.<\/p>\n\n\n\n

Studies cited in the report show that AI-driven credit scoring can outperform conventional models by as much as 85% in predictive accuracy, fundamentally reshaping how risk is evaluated.<\/p>\n\n\n\n

The commercial opportunity is substantial. Estimates suggest that reaching even 10% of the excluded population could unlock tens of billions of dollars in new lending annually across Latin America.<\/p>\n\n\n\n

For banks, this represents not only new revenue but also a pathway to long-term customer relationships that begin with basic credit products and expand over time.<\/p>\n\n\n\n

Beyond lending, AI is also redefining how institutions grow wallet share in competitive retail banking markets. As challenger banks and superapps raise customer expectations, incumbents are turning to advanced analytics to move beyond generic campaigns and toward precise, real-time engagement.<\/p>\n\n\n\n

AI-powered \u2018next best action\u2019 engines process transaction histories, spending behavior and life events to identify the optimal moment to introduce new products.<\/p>\n\n\n\n

These systems enable targeted offers for cards, savings, insurance or credit upgrades – improving relevance while reducing marketing waste.<\/p>\n\n\n\n

According to the report, banks deploying these tools have achieved conversion rate increases of around 25% compared with traditional blanket promotions.<\/p>\n\n\n\n

Executives interviewed for the study note that this shift marks a turning point. AI-driven personalization is no longer viewed purely as a customer experience enhancement but as a core revenue engine.<\/p>\n\n\n\n

By anticipating needs rather than reacting to them, institutions can deepen loyalty and increase lifetime value in markets where switching costs are low.<\/p>\n\n\n\n

Fraud prevention represents the third major revenue-linked application. Latin America\u2019s rapid migration to digital payments has been accompanied by a surge in fraud, with the region accounting for roughly 20% of global e-commerce revenue lost to fraudulent activity.<\/p>\n\n\n\n

Card-not-present fraud and authorized push payment scams have risen sharply, eroding consumer trust and increasing costs for providers.<\/p>\n\n\n\n

To address this, banks and Fintechs are deploying AI-driven fraud detection systems that operate in real time.<\/p>\n\n\n\n

These platforms combine behavioral biometrics, geolocation data and anomaly detection to distinguish legitimate transactions from suspicious activity with greater precision than rules-based systems.<\/p>\n\n\n\n

The impact extends beyond loss reduction. By minimizing false declines, AI-enabled fraud controls allow more valid transactions to proceed, directly boosting payment volumes and customer satisfaction.<\/p>\n\n\n\n

In this context, fraud prevention has evolved from a defensive cost center into a growth enabler, reinforcing trust and encouraging greater usage of digital channels.<\/p>\n\n\n\n

While the business case for AI is increasingly clear, the report underscores that scaling these capabilities across Latin America presents unique challenges.<\/p>\n\n\n\n

Success depends as much on enabling conditions as on algorithms and several structural factors support momentum.<\/p>\n\n\n\n

Payments digitization initiatives have accelerated digital access, while open finance frameworks, particularly in Brazil, are expanding consent-driven data sharing.<\/p>\n\n\n\n

At the same time, the Fintech ecosystem has grown rapidly, increasing both competitive pressure and partnership opportunities that push incumbents to modernize.<\/p>\n\n\n\n

Rising consumer demand from younger, mobile-first populations further reinforces adoption.<\/p>\n\n\n\n

However, significant bottlenecks remain. Infrastructure gaps, including limited broadband and inconsistent connectivity in rural areas, constrain digital engagement and leave data ecosystems incomplete.<\/p>\n\n\n\n

Regulatory fragmentation across countries complicates regional scaling, as privacy and data-sharing requirements vary widely.<\/p>\n\n\n\n

Talent shortages also persist, with limited availability of professionals who combine AI expertise with regulatory and financial domain knowledge.<\/p>\n\n\n\n

Trust represents an additional constraint. High-profile cyber incidents and uneven reliability of digital-only services can undermine consumer confidence, raising adoption risks unless institutions invest in resilience, transparency and governance alongside technology.<\/p>\n\n\n\n

The report highlights execution speed as a critical differentiator. Even when AI use cases are proven, integrating them with legacy core banking systems can take six months or longer, delaying time to value in fast-moving markets.<\/p>\n\n\n\n

Institutions that modernize architectures, streamline decision-making and align business and technology teams are better positioned to capture opportunities ahead of competitors.<\/p>\n\n\n\n

Ultimately, Latin America stands out as one of the most dynamic yet complex testbeds for AI in financial services.<\/p>\n\n\n\n

The region\u2019s combination of unmet demand, digital adoption and competitive intensity creates fertile ground for innovation, but only for institutions that can move beyond experimentation to sustained execution.<\/p>\n\n\n\n

Dyna.Ai\u2019s research concludes that the next phase of value creation will favor organizations that focus on a small set of revenue-linked AI capabilities, invest in scalable foundations and address trust and infrastructure challenges head-on.<\/p>\n\n\n\n

In doing so, financial institutions can extend inclusion, protect customers and unlock durable growth across one of the world\u2019s most promising emerging markets.<\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

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. Dyna.Ai, a global provider of Artificial Intelligence solutions, has released a new executive insights report developed in collaboration with GXS Partners and Smartkarma, highlighting how […]<\/p>\n","protected":false},"author":58,"featured_media":18955,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[71,51,65,2237,91,3],"tags":[6002,7168,112,7169,5834,7170,1827,1522,3383,7167],"class_list":["post-18954","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-banking-finance","category-brazil","category-features","category-latam","category-software","category-top-stories","tag-ai-credit-scoring","tag-alternative-data","tag-artificial-intelligence","tag-customer-analytics","tag-digital-payments","tag-dyna-ai","tag-financial-inclusion","tag-fintech","tag-fraud-prevention","tag-latin-america-banking"],"acf":[],"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.intelligentcio.com\/latam\/wp-json\/wp\/v2\/posts\/18954","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.intelligentcio.com\/latam\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.intelligentcio.com\/latam\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/latam\/wp-json\/wp\/v2\/users\/58"}],"replies":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/latam\/wp-json\/wp\/v2\/comments?post=18954"}],"version-history":[{"count":2,"href":"https:\/\/www.intelligentcio.com\/latam\/wp-json\/wp\/v2\/posts\/18954\/revisions"}],"predecessor-version":[{"id":18958,"href":"https:\/\/www.intelligentcio.com\/latam\/wp-json\/wp\/v2\/posts\/18954\/revisions\/18958"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/latam\/wp-json\/wp\/v2\/media\/18955"}],"wp:attachment":[{"href":"https:\/\/www.intelligentcio.com\/latam\/wp-json\/wp\/v2\/media?parent=18954"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.intelligentcio.com\/latam\/wp-json\/wp\/v2\/categories?post=18954"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.intelligentcio.com\/latam\/wp-json\/wp\/v2\/tags?post=18954"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}