Introduction

Generative artificial intelligence (AI) is no longer a theoretical possibility at the margins of financial services—it is rapidly becoming a core driver of transformation across the sector. From AI-driven credit decisions and algorithmic trading to infrastructure optimization, generative AI is impacting how financial institutions operate, compete, and scale. The pace of innovation is testing the limits of existing frameworks, creating a widening gap between technological capacity and regulatory readiness. This white paper series is designed to equip policy makers, industry leaders, and regulators with a strategic understanding of both the potential and the perils of this shift. It begins by establishing a shared conceptual foundation for the technologies reshaping finance and concludes by proposing oversight approaches that are not only responsive to today’s use cases but also resilient to tomorrow’s challenges.

In a series of four papers, the Bretton Woods Committee will examine the applications, risks, regulatory challenges, and policy opportunities associated with generative AI in finance. This work is intended to help shape a forward-looking regulatory framework that fosters innovation while protecting consumers, ensuring market integrity, and safeguarding the stability of the financial system.

The first paper establishes foundational concepts, including the distinction between traditional machine learning and generative AI, and maps the adoption of both of these innovations across the financial sector. It surveys current applications—from personalized financial advice and algorithmic trading to credit modeling and compliance tools—and evaluates the capabilities and vulnerabilities that make AI both transformative and potentially destabilizing. It also introduces key considerations such as explainability, governance, and systemic risk.