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By Isaac Mills
In 2023, artificial intelligence, especially generative AI crossed a tipping point in its influence on global finance. Major players in developed markets began deploying AI at scale across asset management, retail banking, compliance, and customer service.
At the same time, emerging market fintechs continued to push boundaries not by replicating advanced AI frameworks, but by cleverly adapting them to leapfrog traditional financial infrastructure.
The two trends are deeply interlinked. While AI’s biggest R&D budgets reside in New York, London, and Frankfurt, some of its most agile, purpose-driven applications are sprouting in Lagos, Nairobi, Jakarta, and São Paulo. This article explores how developed markets and emerging markets are harnessing AI and fintech innovation differently, and why their interplay is shaping the future of financial services.
AI in Developed Markets: From Cost Savings to Competitive Edge
In the U.S., U.K., and Western Europe, the past year saw AI move from theory to execution.
Large banks like JPMorgan, HSBC, and BNP Paribas expanded their use of AI in operational workflows. Generative AI models, such as OpenAI’s GPT-4, became embedded in customer service interfaces, report generation, and even internal compliance checks. Goldman Sachs piloted code-generation tools to accelerate internal software development, cutting months off deployment timelines.
Wealth and asset management firms embraced AI-driven portfolio construction. BlackRock and Fidelity deepened their investments in machine-learning-based forecasting models that blended traditional macroeconomic indicators with alternative data ranging from satellite imagery to social sentiment.
Regulatory tech (regtech) saw a parallel surge. AI was increasingly used to automate anti-money laundering (AML) detection and Know-Your-Customer (KYC) workflows. Natural language processing (NLP) helped banks analyze legal documents, detect risk exposure, and summarize compliance updates across jurisdictions.
Yet for all its promise, AI in developed markets was not without caution. Concerns around explainability, model bias, and data privacy slowed deployment in sensitive areas. European regulators proposed new transparency requirements under the AI Act, signaling that compliance costs would rise in parallel with innovation.
Nonetheless, 2023 marked a turning point: AI was no longer a proof of concept in developed market finance, it became a foundational capability.
Fintech in Emerging Markets: Innovation Out of Necessity
While developed markets raced to optimize, fintechs in emerging economies innovated to include.
In Africa, Asia, and Latin America, fintech companies continued to redefine what financial inclusion means. Their approach wasn’t to match the sophistication of Wall Street but to solve local problems using available tools often inspired by AI advancements, but adapted to mobile-first, low-bandwidth realities.
In Nigeria, banks and fintechs have increasingly turned to AI-powered chatbots to improve customer engagement and reduce operational strain. Major players like Access Bank and UBA deployed virtual assistants; Tamara and Leo, respectively to handle routine banking queries, such as checking balances, transferring funds, and resolving transaction issues. These chatbots, integrated into platforms like WhatsApp and Facebook Messenger, enabled customers to access 24/7 service without waiting in queues or visiting branches. By mid-2023, AI-driven customer support had become a core part of digital banking strategy, offering faster resolution times and freeing up human agents for more complex issues.
Kenya’s Tala and Brazil’s Nubank integrated machine learning for fraud detection and customer personalization, with real-time responses built into their mobile apps. These tools were not built in-house but adapted from open-source AI frameworks—proving that innovation in emerging markets doesn’t always mean invention. It often means intelligent adaptation.
In Southeast Asia, platforms like Gojek and Grab blurred the lines between fintech and commerce, using AI to cross-sell financial products to gig workers and vendors. Micro-insurance, buy-now-pay-later, and micro-investing tools became embedded within everyday apps.
What distinguished these fintechs was not their tech stack but their context sensitivity. In markets where traditional banks remained inaccessible or distrusted, trust was built on user experience, speed, and localized financial products. AI-enabled insights allowed these firms to scale that trust quickly and securely.
Leapfrogging with Hybrid Models
An emerging pattern in 2023 was the convergence of fintech agility with AI scalability. Some fintechs in emerging markets began experimenting with hybrid AI-human models particularly in areas like customer support and credit underwriting.
Take India’s CredAvenue, which uses AI to screen thousands of SME borrowers, flag high-risk profiles, and pass them to human analysts for final vetting. The result was faster turnaround times without compromising judgment.
In Ghana and Rwanda, banks partnered with AI startups to integrate voice-based banking services in local languages, using lightweight speech recognition models to help users access accounts or check balances via feature phones. These were not multimodal AI breakthroughs but they mattered more because they reached more people.
Meanwhile, global tech firms noticed. In 2023, Stripe and PayPal made strategic acquisitions of emerging market fintechs, not just for market access but for their models of scalable, AI-informed inclusion. The frontier of fintech wasn’t just expanding, it was being redrawn.
Challenges and Tensions
Both developed and emerging markets faced headwinds.
In the West, AI raised thorny questions about systemic risk. Could algorithmic trading models amplify volatility in times of stress? Could black-box AI decisions introduce liability in lending or insurance underwriting? Boards began demanding AI governance frameworks before greenlighting deeper adoption.
In emerging markets, data access and quality remained key hurdles. AI models are only as good as the datasets that train them and in many countries, those datasets were fragmented or biased. Some governments were slow to enact digital identity or data protection laws, leaving innovation in a grey zone.
Additionally, fintechs in markets like Nigeria and India faced tightening regulations as central banks attempted to balance innovation with systemic stability. In some cases, compliance burdens forced consolidation, limiting the ability of smaller players to scale.
Looking Ahead: Interdependent Futures
By mid-2024, one thing had become clear: AI-driven finance and fintech-led inclusion were not parallel trends, they were converging forces. Emerging markets increasingly viewed AI not as a luxury but as a utility. Developed markets, in turn, began seeing emerging market fintechs as innovation laboratories with valuable lessons in lean design, agile regulation, and user-centricity.
This mutual learning loop may define the next phase of global finance. AI will continue to reshape how capital is deployed, risks are measured, and services are delivered but its full potential will only be realized if it reaches the billions still outside the financial system.
And that’s where emerging markets have the edge: in building systems for people who need them the most, with or without the perfect infrastructure.
