SEBI will use artificial intelligence, big data to monitor market manipulations, says Ajay Tyagi

Securities and Exchange Board of India (SEBI) Chairman Ajay Tyagi on January 23 said the regulator will adopt artificial intelligence (AI), machine learning (ML), big data analytics and natural language processing tools to monitor and analyse spot market manipulation, PTI reported.

"Catching malpractices in the market using the standard tools that analyse only structured data of price and volume is increasingly getting difficult," Tyagi said. As per the plan, a “data lake” project will be created to augment analytical capabilities.

"We want to acquire technology and unstructure data analysis because the structured data analysis is not helping much, manipulators use all sort of things," he noted.

The SEBI chief added that AI and ML tools could bring about a paradigm shift in the securities market landscape. He further said that blockchain could also be used to clear and settle activities.

SEBI is also acquiring capabilities to monitor and analyse social media posts to keep a tab on possible market manipulations, Tyagi said. He added that there have been cases where social media posts have helped in acting against manipulative activities.

He was speaking at the National Institute of Securities Markets at Patalganga.

A tender has also been floated for acquiring the technology. Even in the absence of such a focused tool, Tyagi said SEBI already has capabilities, wherein it screens social media posts after corporate announcements and the changes in price and volumes of a scrip.

AI/ML tools are being increasingly deployed in fund management, trading, supervision and surveillance functions in the capital markets, he added.

Further, Tyagi said there is a need for the technologists to invest time in research in these tools for applications in the capital markets.

Systemic risks are becoming important objectives for financial regulators, Tyagi said, explaining that this requires identification and monitoring of important financial institutions, leverage, inter-connectedness, risk concentrations and market sentiment.

(With inputs from PTI)