Financial regulators in emerging markets and developing economies are adopting AI-powered supervision tools at roughly half the rate of wealthy nations, creating a critical oversight gap as artificial intelligence reshapes banking worldwide. While 85% of financial authorities in advanced economies use AI-powered supervisory technology, or SupTech, only 53% of their counterparts in emerging markets and developing economies (EMDEs) have deployed such tools. This disparity matters because financial service providers globally are racing to adopt AI, with 65% already using it actively and another 25% piloting solutions, according to recent surveys.

The stakes are particularly high for emerging markets, where regulators already face stretched resources managing rapid digitization, evolving business models, and geopolitical instability. Without AI-powered oversight capabilities, these authorities struggle to assess whether banks and fintech companies are deploying AI responsibly, especially when it comes to reaching underserved populations. The gap also means regulators cannot effectively detect emerging risks like algorithmic bias, fraud, or market concentration that AI systems can inadvertently amplify.

Why Are Emerging Market Regulators Lagging Behind?

The adoption gap reflects real constraints facing financial authorities in developing economies. Many lack the technical expertise, infrastructure, and budget to build or procure sophisticated AI-powered supervisory systems. Additionally, traditional regulatory frameworks designed for bank-centric, siloed financial systems are ill-suited to the complexity of AI-driven finance, making it harder for regulators to know where to start.

Yet interest is accelerating. A World Bank survey of 27 financial authorities in EMDEs found that AI adoption is now a board-level priority for most, signaling recognition of the urgency. Among 120 surveyed EMDE regulators, 30% are actively piloting or deploying AI-powered tools on a limited basis, suggesting momentum is building.

How Can Emerging Market Regulators Build AI Supervision Capacity?

Financial authorities in developing economies can strengthen their AI oversight capabilities by following a structured approach. Research from the Consultative Group to Assist the Poor (CGAP) outlines five priority recommendations that regulators can implement:

• Legal Foundations: Strengthen laws protecting data privacy and ensuring ethical AI use, creating a clear regulatory framework that guides both regulator and industry behavior.
• Digital Transformation: Pursue an ambitious but realistic agenda to modernize internal systems and processes, avoiding overly complex implementations that exceed organizational capacity.
• AI Risk Management: Enhance governance structures and accountability mechanisms to manage automation bias, algorithmic errors, and technology failures within supervisory systems themselves.
• Organizational Culture: Transform internal mindsets and processes to embrace data-driven decision-making, moving beyond traditional compliance-focused approaches.
• Collaboration: Leverage both domestic partnerships with industry and international cooperation with other regulators to share best practices and avoid duplicative efforts.

What Specific Benefits Can AI Supervision Unlock for Financial Inclusion?

AI-powered SupTech offers three mutually reinforcing advantages that directly support financial inclusion in emerging markets. First, it improves operational efficiency by automating routine compliance tasks and data processing, freeing regulators to focus on complex risk analysis. Second, it expands analytical reach, allowing authorities to monitor larger volumes of transaction data and detect patterns that signal emerging risks or opportunities for underserved populations. Third, it augments decision-making by providing regulators with richer insights into market dynamics and individual institution behavior.

These capabilities have direct and indirect benefits for inclusion. Directly, better regulatory monitoring helps ensure that AI-powered financial services reach low-income individuals and micro and small enterprises responsibly. Indirectly, when regulators can conduct more effective supervision, compliance costs for financial service providers decrease, which lowers barriers to entry for smaller institutions and reduces the cost of financial services for consumers.

Real-world examples illustrate the potential. In Brazil, financial service providers are using AI to expand credit to micro and small enterprises by analyzing transaction data from the fast payment system Pix, leveraging open finance principles. Regulators equipped with AI-powered tools can monitor such innovations in real time, ensuring they benefit intended populations rather than concentrating risk or excluding vulnerable groups.

What Risks Must Regulators Actively Manage?

Adopting AI-powered supervision is not risk-free. Regulators must actively manage three categories of challenges. AI governance and accountability risks arise when algorithms make decisions without clear human oversight or explainability. Automation bias occurs when regulators over-rely on AI recommendations and fail to question their outputs. Operational and technology risks include system failures, data breaches, and the concentration of critical supervisory functions in fragile digital infrastructure.

Additionally, AI itself can amplify financial inclusion risks if not carefully managed. Demographic biases embedded in training data can exclude women, young people, and other vulnerable groups from credit access. Fraud and data misuse threaten consumer trust. Risk concentration and herding behavior, where multiple AI systems make similar decisions simultaneously, can destabilize markets. Regulators need AI-powered tools precisely to detect and prevent these harms.

The urgency is clear. As global AI-related spending in the financial sector grows from $35 billion in 2023 to a projected $97 billion by 2027, the gap between regulatory capacity in advanced and emerging economies will only widen unless action is taken now. For emerging market authorities, building AI-powered supervision is no longer optional; it is essential to maintaining financial stability and ensuring that AI-driven innovation benefits the populations they serve.

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