Could generative AI be the final disruptor in derivatives?

Key Takeaways

• Generative AI is set to transform the derivatives markets
• ISDA identifies several contributions the technology can make
• Cybersecurity and oversight are major concerns

Generative artificial intelligence (genAI) has been dubbed the most significant change to work since the agricultural and industrial revolutions. The technology, even more than Distributed Ledger Technology (DLT), has the potential to transform governments, industry and the entire financial sector, boosting productivity, advancing public service delivery while fostering more creative and meaningful work for people.

But with such power comes great responsibility and the International Monetary Fund (IMF) raises profound concerns about “massive labour disruptions and rising inequality”.

In a report from June this year, Broadening the Gains from Generative AI: The Role of Fiscal Policies, the IMF states: “The sheer scale and speed of the transformation pose risks to labour markets. While automation and robots have already displaced low- and middle-skill jobs involving routine tasks, genAI’s capabilities extend to more intelligent automation, potentially amplifying job losses in cognitive occupations.”

Promising use cases

Among those likely to be counted in the “cognitive occupations” set to be disrupted by genAI are individuals working in derivatives.

The International Swaps and Derivatives Association (ISDA) published a Future Leaders in Derivatives whitepaper in June setting out guidance for industry stakeholders, regulators and technology providers and “seeking to harness the power of genAI in transforming the OTC derivatives market”.

ISDA is clear that genAI has multiple “promising use cases” for the market, ranging from creating a new language based on precedent and synthesizing data into a human-readable summary to refining contracts and formulating regulation.

For example, genAI can create various jurisdictional regulations and present these in an easy-to-read format, comply with industry or firm standards and provide checks against trades and trade documentation. ISDA notes that while “not a replacement for a human lawyer”, the technology can significantly accelerate the review process and act as an additional regulatory compliance check.

Law firm Allen & Overy (A&O) has been using Harvey, a platform that uses natural language processing, machine learning and data analytics to automate and enhance various aspects of legal work, such as contract analysis, due diligence, litigation and regulatory compliance, since 2023.

The firm says that the output still needs careful review by an A&O lawyer, but Harvey can “help generate insights, recommendations and predictions based on large volumes of data, enabling lawyers to deliver faster, smarter and more cost-effective solutions to their clients”.

A game-changer

This is game-changing for the derivatives industry, which is so heavily reliant on contracts and agreements that are both costly and time consuming to get in place.

Anomalies and inconsistencies between regulatory frameworks and the data needed for compliance are two major issues for market participants, and there is huge potential for genAI to improve the timeliness and accuracy with which regulatory reporting obligations are implemented.

As ISDA states: “A genAI model could consume, process and interpret regulatory rules and guidance, providing a clearly defined set of requirements for market participants to review and apply across product types and jurisdictions. The power of such a genAI model will increase as the reporting rules and underlying data itself becomes ever more standardised through initiatives such as the critical data elements and common domain model.”

Given the volatility of markets thanks to an uncertain geopolitical environment, genAI is set to vastly enhance market insights by analysing huge volumes of structured and unstructured data.

This type of analysis extends the capabilities of traders to gauge and adjust market strategies by accelerating the assimilation of data into meaningful near real-time decision-making.

Finally, ISDA acknowledges the role genAI will play in expanding OTC derivatives to developing and emerging markets. The technology will aid firms in summarising local regulations and market conditions, paving the way for a more efficient entry into new jurisdictions.

Manipulating the system

The technology looks to be profoundly positive for large swathes of the OTC derivative market processes, but what of the risks?

While regulators are attempting to get legislation in place, keeping up with the genAI revolution, never mind pre-empting it, is impossible, meaning it is down to users to ensure effective governance against potential operational threats.

ISDA is clear that without proper security genAI may create “new opportunities for cyberattacks with large impact”.

New forms of cyberattack include malicious attempts to manipulate or deceive the AI system used by a financial institution, its input or output leading to unpredictable behaviour and false output.

Data quality too is a very real issue for genAI advocates. ISDA points out that risks can arise when the data used to train and operate genAI models is inaccurate, incomplete, inconsistent or biased, meaning the interpretations are inadequate or just plain wrong.

Fortunately, for anyone worried about the impact of genAI on the derivatives labor market, ISDA says that genAI decision-making must be supplemented with “sound human judgment and humans need to be held accountable for any final decisions made”.

Similarly, genAI needs to be “reliable and safe” when managing financial functions. This requires rigorous testing during system development and deployment, and consistent oversight and maintenance to protect the system over its lifespan.

GenAI gathers momentum

GenAI is not the only technology that market participants have been considering in recent years. DLT and smart contracts have also gained prominence over recent years in the finance industry due to the tangible gains they provide in terms of efficiencies, transparency, and trust.

In the cleared derivatives industry, blockchain technology’s biggest impacts are widely reported to be concentrated in post-trade processes and collateral management through tokenization. Moreover, there is a receptive audience as buy- and sell-side firms push to control costs through consolidating front-, middle- and back-office systems or through automation.

However, as ION wrote recently, the business case realization of blockchain and budgetary constraints will potentially push derivatives firms to decide to work with proven technologies to develop in-house or with outsourced product providers. Until the DLT case is proven definitively, conventional technology workflows are expected to remain firmly in place, while AI may turn out to be the game-changer in derivatives.

If used appropriately, genAI could provide derivatives market participants with the tools they need to work efficiently and to comply with regulatory regimes in a range of jurisdictions. The outlook is mostly bright for genAI but the users will need to take responsibility for supervisory governance, controls, and safeguards to manage the risks associated with this transition in the use of artificial intelligence.