Artificial Intelligence and its Impact on Financial Markets and Financial Stability
IMF News, September 6, 2024
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- Published: September 6, 2024
Overview
- Remarks by Tobias Adrian, Financial Counsellor and Director of the Monetary and Capital Markets Department, IMF, at Bund Summit 2024 “Navigating a Changing World”.
- Shanghai, China — September 6, 2024.
- As prepared for delivery: advancements in Artificial Intelligence (AI), particularly Generative-AI, are unfolding rapidly and are poised to impact financial markets and financial stability.
Areas of AI impact on financial markets
- Efficiency
- AI—and in particular Generative AI—is being used to enhance productivity by speeding up and automating many current tasks.
- Finance is particularly ready to take advantage of these advances because efficient processing of data is already central to most activities in finance.
- Expected rapid takeoff across back-office operations, customer-facing interfaces, research, and building analytical models.
- Evolutionary improvements
- Machine-learning and neural networks have been used by cutting-edge investment firms for at least ten years and now play a significant role in automated and high-speed trading in the most liquid and deepest markets.
- Large language models enable processing of very large amounts of unstructured, often text-based, data to enhance analytical tools.
- Implications include:
- Enhancing the power of broad and extensive forecasts.
- Enabling quantitative investors to quickly analyze complex documents such as bond indentures or corporate earnings releases, improving price discovery across asset classes.
- Through AI-assisted coding, data gathering, and investment analysis, Gen-AI is likely to lower barriers to entry for quantitative investors into less liquid asset classes, such as emerging markets and corporate debt.
- Potential improvement of market liquidity in these asset classes, with attendant financial stability challenges.
- Revolutionary transformation
- The much larger jump from AI-generated model inputs to very sophisticated autonomous AI-driven financial agents still seems far off.
- Many envision autonomous AIs that generate and execute trades without human oversight, but market participants are not comfortable with this idea yet.
- Current market participants emphasize human oversight for regulatory, risk-management, liability, and ethical reasons.
- The area is evolving quickly and requires continued attention.
Implications for financial stability
- Potential benefits
- AI can bring productivity enhancements, cost savings, improved regulatory compliance or RegTech, and more tailored offers to clients.
- Technology has historically improved price discovery, deepened markets, and often dampened volatility in times of stress; AI is likely to continue these trends.
- Potential risks
- Limited negative impacts of quantitative trading have occurred in some sudden market dislocations; there are fears these risks could rise with the use of AI.
- AI could exacerbate traditional financial stability channels such as interconnectedness, liquidity, and leverage.
- Specific concern that AI-driven speed and scale of market moves may exceed previous expectations, prompting re-evaluation of leverage and margining practices.
- Notable market episodes referenced
- August 5th selloff in Japanese and US equity markets: an instructive example where turmoil was reportedly amplified by sophisticated hedge funds acting at once when algorithms spotted clear downward trends and volatility spiked.
- Analogies drawn to:
- Flash crash in the US equity market in May 2010.
- Flash rally in the US treasury market in October 2014.
Supervisory, monitoring, and market-structure considerations
- Structural readiness
- Markets continue to move faster; preparedness for even greater speeds due to AI is necessary.
- Considerations include margining requirements, circuit breakers, and the resilience of central counterparties.
- Monitoring and entity oversight
- Regulators need tools to track developments in changing markets and the entities acting in them.
- AI may increase the importance of nonbanks—broker-dealers, trading firms, hedge funds, and related entities—that can take advantage of AI without intrusive supervision.
- Risk of not having a good understanding of who these nonbank entities are, how they are funded, and what they are doing.
- After past flash events, new circuit breakers and reporting and disclosure requirements improved market understanding and functioning.
- Concentration risks and critical AI services
- Provision of critical AI services is concentrated in a handful of third parties, creating interdependencies that deserve regulatory attention, particularly for market functioning in the event of a significant outage.
- Cyber-attacks, manipulation, and sup‑tech
- High-profile cases involving “deep fakes” may be the tip of the iceberg.
- Regulators must invest in supervisory technology (so called sup-tech) that can use AI to process information and spot fraud and other potential troubles.
- Sup‑tech is already effectively used in money laundering and counter-terrorism; as malicious actors get more sophisticated, supervisory capabilities must advance accordingly.
IMF activities and recommendations
- The Fund plays a pivotal role in shaping global financial sector policies and collaborates with international organizations and standard-setting bodies as new potential risks arise.
- The Fund continuously monitors developments; one chapter in the forthcoming Global Financial Stability Report examines how AI is likely to transform capital markets and impact financial stability more broadly.
- The Fund helps member countries build and strengthen capacities to manage financial stability and is incorporating work on AI into this assistance.
- A collaborative approach will be needed to deal effectively with the challenges and opportunities AI will bring in the years to come.
Source: Remarks by Tobias Adrian at Bund Summit 2024, Shanghai, China — September 6, 2024.