Introduction

The report examines how artificial intelligence (AI) is transforming the financial system by enhancing information processing, risk management, and customer service. AI’s integration into finance has made processes more efficient, but it also presents new challenges, particularly regarding financial stability and the need for updated regulatory frameworks.

Decoding artificial intelligence

The financial system has evolved alongside advances in information processing technology. The report traces this evolution from early computational methods to modern AI, focusing on machine learning (ML) and generative AI (GenAI). Historically, financial systems have been early adopters of new technologies, which have significantly impacted commerce and trade.

AI transforming finance

AI is revolutionising four key financial functions: financial intermediation, insurance, asset management, and payments. The report highlights opportunities such as improved credit scoring, fraud detection, and risk analysis through ML and GenAI. However, these advancements also bring challenges, including the opacity of ML models and risks related to cybersecurity and consumer privacy. For example, the report notes that ML can reduce credit underwriting costs by up to 30%, but the complexity of these models may lead to issues with transparency and algorithmic bias.

AI and financial stability

The report outlines the potential risks AI poses to financial stability. Historical examples, such as the 1987 US stock market crash, illustrate how technology can amplify systemic risks. Today, the use of uniform ML models and their reliance on similar datasets increase the risks of herding and market volatility. GenAI, with its capacity for fast and autonomous decision-making, may exacerbate these issues, potentially leading to uniformity in market behaviours and increased systemic risk. Additionally, the data-intensive nature of GenAI raises concerns about privacy and cybersecurity, particularly as these technologies become more embedded in financial systems.

AI use for prudential policy

AI’s potential in micro- and macroprudential regulation is discussed, with an emphasis on its ability to enhance risk assessment and prediction. However, the report cautions against the challenges of aligning AI with regulatory objectives, particularly due to the unique nature of financial crises and the scarcity of relevant data. The report recommends that regulators leverage AI’s capabilities while maintaining human oversight and developing robust frameworks to mitigate associated risks.

Risk of AI disruption

The report presents two scenarios for AI’s impact on the economy: an optimistic scenario where AI boosts productivity with minimal disruption, and a disruptive scenario where rapid AI advancements lead to significant job displacement and economic instability. In the latter case, the financial system could face widespread defaults and increased volatility, exacerbated by the accelerated pace of AI-driven automation.

Upgrading financial regulation for AI

The report calls for proactive and internationally coordinated regulation to manage AI’s risks while fostering innovation. It outlines principles for AI regulation, including transparency, accountability, and fairness, and compares regulatory approaches from the US, EU, and China. The report emphasises the need for global cooperation to standardise AI governance and ensure the financial system’s stability as AI becomes more integrated into its operations.

Conclusion

The report concludes that while AI offers significant benefits to the financial system, it also introduces complex risks that require careful management. The integration of AI into finance should be accompanied by updated regulatory frameworks that address these risks, ensuring that AI’s transformative potential is harnessed for the broader benefit of society.