The Intersection Of AI, Financial Regulation, And Algorithmic Trading: Evaluating SEBI's Response To Emerging Risks In A Global Market
- IJLLR Journal
- Dec 25, 2025
- 2 min read
Ananya Shrivastava, Symbiosis Law School, Pune
I. Introduction
Algorithmic trading, or algo trading, as commonly called, involves computer programs and algorithms to carry out financial market trades whose speeds and efficiencies cannot be matched by human beings. These algorithms work on a fixed set of rules based on timing, volume and price to issue orders without necessarily involving human interaction. The objective of algorithmic trading is to maximize trading efficiency, reducing the influence of human emotions on trading decisions and the fees associated with enabling the transactions. The use of high-frequency data feeds and sophisticated mathematical models enables algorithmic trading to detect and capitalize on market opportunities in a fraction of a second. This provides an important component of the liquidity of the market and overall market efficiency of the financial markets.
It is the advent of Artificial Intelligence that has gone on to revolutionize financial markets and, in particular, algorithmic trading by incorporating neural networks, machine learning algorithms and predictive analytics with a view to improve the trading strategies. Apart from record speed, precision and automation in transactions, it has also led to serious critical regulatory and ethical issues, such as manipulation of the market, stability of the system and biases by algorithms. The current inefficiencies in marketing, market distortion of financial stability and reinforcement of self-reinforcing biases will be exacerbated by AI-based strategies if they are not monitored. An overall oversight mechanism will be necessary to deal with such emerging risks as the use of AI trading practices increases to make sure there is accountability, fairness and transparency.
Regulators worldwide, including the European Securities and Markets Authority (ESMA), the U.S. Securities and Exchange Commission (SEC) and the Financial Conduct Authority (FCA), have implemented provisions within their regulatory norms which include AI-specific governance structures. Nonetheless, the Securities and Exchange Board of India (SEBI) is depending on conventional regulation regimes like the SEBI (Investment Advisors) Regulations, 2013, which remain silent about AI-specific protections. With the ever-increasing development of AI, there is a critical need to examine the adequacy of the Indian regulatory framework to regulate AI-led financial markets and its conformity with global best practices.
