18 April 2024

Regulating AI in the securities markets

 I have a piece in today's Financial Express with Parker Karia on the impact of AI (artificial intelligence) on securities markets. The full piece is as follows:


Fast on the heels of development of AI, which has already resulted in transformations across various industries and professions, the European Union is the first jurisdiction to introduce legislation that regulates AI. Broadly, those AIs which pose an unacceptable risk would be prohibited, whereas minimal risk AI systems are unregulated. The former category would include AIs that affect people’s rights, biometric categorisation systems, scraping of facial images from sources to create a facial recognition database, social scoring, predictive policing, or such AI that manipulates human behaviour or exploits people’s vulnerabilities. Additionally, the EU’s AI Act establishes the EU AI Authority, which will be the nodal agency for implementation and enforcement of the AI Act, which, like the GDPR, has an element of extraterritorial jurisdiction.

What is actually regulated is AIs that fall into neither unacceptable risk, nor the minimal risk category. These are high-risk and limited risk AI systems. High-risk AI systems pose a threat as its uses include deployment in critical infrastructure, education, essential services, law enforcement, dispensation of justice, governance, etc. Such systems would inter alia be required to register with the relevant EU database, assess and mitigate risks, ensure transparency and accuracy, and more importantly, ensure human oversight. Moreover, people would have a right to submit complaints about AI systems and would be entitled to explanations about decisions in relation to high-risk AI systems that affects the right of the aggrieved person. Non-compliances with the AI Act will attract fines ranging from €7.5 million or 1.5 percent of revenue, up to €35 million or 7 percent of global revenue, depending on the violation and the entity.

GPAI

General-purpose AI systems, such as ChatGPT, Gemini, etc., would face new transparency requirements. Such software, including those that create manipulated images such as “deepfakes” would have to make clear that what people were seeing was generated by AI.

AI and the Securities Market

The securities market will not be, or rather, is not an exception to the infiltration of AI. Although recent breakthroughs have been largely in the space of generative AI, gigantic steps are being taken to equip AI with further abilities, as well as expand the data the AI has access to

To put the timeline and development in perspective, till three decades ago, activities related to trading in the securities market, such as research, placement of orders, etc., hardly incorporated technology. The focus on use of technology began with some seriousness upon the introduction of dematerialized shares. From then, to today, India has taken the lead in introducing a ‘T + 0’ settlement cycle. Today, any step or activity relating to trading in the securities market, cannot be imagined without the use of technology. Now, with the introduction of AI, the securities market is set to witness another transformation. Today, AI can analyze vast amounts of data, identify patterns, and make informed decisions in real-time, execute orders at lightning speed, create investment strategies by itself, etc., as a result of which, the manner in which trading is conducted, risk is managed, and investments are made, are rapidly evolving. One of the pertinent concerns in this regard would be around data privacy.

As AI and AI-generated algorithms permeate various sectors, including the securities market, regulators face the challenge of crafting laws that govern these technologies effectively. In the following paragraphs, AI’s impact on the securities market and its regulation, are discussed.

Algo Trading & Robo Advisory

Currently, algo trading is defined as trading carried out through automated means, i.e., order are placed without any human intervention. Recent suggestions by SEBI to regulate algo trading have received mixed reviews, while majority views agree with the need for regulating algo trading, SEBI’s approach towards meeting that end has been the subject of some criticism. It would also be required to be borne in mind that AI can effectively write codes based on instructions fed to it. Thus, creating an algo, in the near future, may not be the exclusive domain of a trained professional in the field of IT systems. In a situation where the deployment of an AI created algo results in a violation of securities laws, the question that arises out of this is on the extent of culpability to be fastened on the person who used AI to create the algo. The principle that the developer of an AI, or the human behind the ‘machine’ is responsible, exists, however, with the advancements in AI, which are unpredictable at this stage, the above principle may have to be revisited. As AI changes the landscape around us, our laws must keep pace to ensure that rights and obligations of the concerned parties are laid down in advance.

Additionally, robo advisory is presumably going to take the center-stage in the distant future. For instance, with the vast amounts of data points analysed in a few moments and investment strategies being created in seconds instead of weeks, it is not too far-fetched to presume a considerable shift in the manner in which investment advisory service is carried out today, which may warrant a revisit to the extant regulatory framework requiring both strengthening and rationalisation of regulations. Strengthening for the reasons described above, and rationalising because some of the restrictions may no longer be relevant with AI generated work product.

Grievance Redressal and Enforcement

AI may eventually be used for dispensation of justice by appropriately (and safely) integrating it in our judicial systems. In fact, it was recently suggested that AI may be used to resolve minor traffic challans, to begin with, upon adequately building up such capability. Similarly, the securities regulator may consider initiating the process to develop AI that can effectively monitor, supervise and assist in the enforcement of securities laws.

Additionally, with the recent focus on online alternative dispute resolution mechanisms for resolution of disputes in the securities market, minor issues, depending on the complexity, quantum of money/ assets and the nature of the dispute, AI can serve as an arbiter or mediator.

Pattern recognition and Predictive Analysis

In a potential game-changer for regulators, developing AI models are becoming increasingly efficient at recognizing patterns, and thus predicting the ‘future’, depending on the data points that the AI has access to, and how it is ‘coded’ to ‘think’. While algos are already deployed by financial sector regulators around the world to identify and/or track suspicious activity, AI can be of immeasurable assistance in this regard. For instance, SEBI has in the recent past issued circulars introducing the use of blockchain to verify information, and to ensure transparency amongst intermediaries and entities. The integration of AI in such systems can lead to predicting any defaults, or preventing violations, thus safeguarding investor interest. However, any such technology should be used with caution, and strict safeguards should be built around such systems to prevent any misuse.

To conclude, while the adoption of AI in the securities market would lead to increased efficiency, reduced costs, and enhanced decision-making capabilities for market participants, it raises significant concerns regarding market manipulation, algorithmic biases, data privacy and systemic risks, which warrants regulatory scrutiny and the need for comprehensive legal frameworks to address the issues emanating out of using AI. As AI continues to evolve and reshape the landscape of securities trading, regulatory authorities must remain vigilant, adaptive, and forward-thinking in their approach, and strike a balance between innovation and regulation, thereby navigating the complexities arising out of the intersection of AI and securities market. While this piece has focused more on the challenges posed, overwhelmingly, the use of AI will be a force for good, bringing speed, productivity, innovation and removal of human errors and biases. Thus, it would be better to delay introducing too many regulations till the dust has settled on the field.

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