GenAI is set to redefine the operational landscapes of the derivatives market, according to a new paper from ISDA Future Leaders in Derivatives (IFLD).
In the Episode 41 of the Swap: Exploring GenAI, hosts Nick Sawyer and Scott O’Malia, Chief Executive Officer of the International Swaps and Derivatives Association, talked to IFLD authors Tom Reynolds, Senior Manager of Financial Services at Factor, and Katherine Arden, Head of Solutions Legal – Marex, about the paper’s findings.
The output from Gen AI models is astonishing and often indistinguishable from what a human might create, said Sawyer.
“We’re seeing increasing focus on the potential of generative AI, which can be used to create entirely new content based on patterns learned from existing data, from text to audio, images, video,” he noted.
He said that research from McKinsey suggests Gen AI could add as much as $4.4 trillion to global corporate profits on an annual basis, with banking, high tech and life sciences set to see the biggest impact when it comes to the derivatives market.
Commenting on the findings, Arden said that Gen AI presents both opportunities and challenges.
“It holds great promise for the application in a derivatives industry, but it needs to be approached with caution,” she said.
There is a great potential for new efficiencies, opportunities for innovation, but there are a number of inherent risks which are material and could severely impact financial firms deploying the technology, she said.
According to O’Malia, the paper points out that the derivatives market plays a pivotal role in global finance, but it also grapples with operational inefficiencies and regulatory complexities. He said that the paper identifies a number of potential use cases for Gen AI in the market.
For Reynolds, the most obvious use case is the ability to summarize very long documents, to synthesize thoughts, and the idea for Gen AI to come up with new thoughts, new thinking, and to generate new ideas, and potentially to help lawyers to navigate some of the challenges faced in the derivatives market.
Arden thinks there a lot of scope in the regulatory space. “Hopefully we will see Gen AI providing tools for regulators to help them interpret data and better detect anomalies.”
O’Malia commented that technology offers great promise, but it also comes with significant challenges and risks.
Reynolds agreed, saying that unconstrained AI represent the risk to amplify or to exacerbate market shocks.
Arden added that one of the big risks is concentration risk.
“If we’re relying on a few base data models, given the concentration in big tech, that could lead to systemic risk.”
She thinks misinformation has been an increasing concern over the past few years.
O’Malia added: We certainly want to make sure that we have those checks and controls and certainly the technology solutions that exchanges provide. Making sure you can sandbox and test systems before they go live, is critically important.
Arden further said that there is a regulatory and policy gap at the moment. The Gen AI technology has developed so rapidly, so policymakers and regulators are effectively trying to play catch up with it. “I think there remains a lot to be seen, and they’re talking of a flexible approach, which I think is quite sensible given the state of the industry.”
Experts agreed that it is important for industry stakeholders to engage in continuous dialogue, collaborate on developing best practices, and advocate for regulatory advancements.
O’Malia said: “Trying to figure out how you need to get your arms around this, or what type of regulations are appropriate is a huge problem, but it’s also a huge opportunity.”
