India’s securities and commodity market regulator, SEBI, recently shortlisted five companies to implement the data analytics projects for tracking possible market manipulations such as insider trading and front running.
The shortlisted companies include Tata Consultancy Services (TCS), Wipro, Capgemini Technology Services India, Larsen & Toubro Infotech, and NEC Corporation India. The selected companies are expected to build analytical models, including artificial intelligence and machine learning. Besides this, the companies are also required to build custom applications as per SEBI’s requirements.
Why now?
This move is a part of SEBI’s effort to address and handle challenges arising from technological advancements in the markets. In 2020-21, a total of 94 new cases were taken up for investigation by SEBI. The cases were related to securities law violations, including price rigging and market manipulation. According to SEBI, nearly 30 cases of the total were taken up for investigation pertaining to insider trading; 41 cases related to market manipulation and price rigging; three cases were related to takeovers, and the remaining 20 cases pertained to other violations of securities laws.
In 2019-20, a total of 161 cases were taken up for investigation by SEBI, and 170 cases were completed. In contrast, in 2020-21, SEBI had taken up 94 cases and completed 140 cases.
(Source: SEBI)
SEBI initiates investigation based on a reference collected from its integrated surveillance department, exchange reports, external government agencies, media reports and complaints. Such an investigation aims to gather evidence and identify entities behind irregularities and violations so that suitable regulatory action is taken, wherever required.
The steps involved during SEBI’s investigation process include analysing market data like order and trade log, transaction statements, and exchange reports. These are often reactive and time-consuming.
The Need for a Real-time Solution
Recently, the regulator has come up with an in-house delta-based insider trading alert. This new insider trading alert development process involved multiple rounds of development, a short implementation timeline, and a series of iterations in the alert logic. Nevertheless, the alert has boosted SEBI’s surveillance in the complex equity derivatives market of futures and options contracts.
As per the annual report 2020-21, the alert utilises trade data as inputs for all clients trading in the shortlisted scrips and calculates the overall delta positions of the clients. It includes the overall processing of close to 20 million trades daily and the associated details to check the risk probability of an investor indulging in insider trading based on the pattern of their delta position over time. Further, the alerts build a suspect library that allows the system to catch repeat offenders later. The alert is then used for further processing.
Implementation of Data Lakes at SEBI
With the advent of artificial intelligence, machine learning and deep learning, it becomes essential for a regulator like SEBI to leverage sophisticated algorithms to address critical challenges for data analytics arising when processing vast amounts of data, whether structured or unstructured.
It is achieved through a data lake solution that can support open source analytical tools such as R, Python, etc., with interoperable features. As a precursor to this data analytics project and shortlisting of companies, SEBI has already completed its tendering process to implement Data Lake.
According to SEBI, the proposed Data Lake will have characteristics such as visualisation, time series, machine learning analytical capabilities, self-service business intelligence capabilities, in-memory processing of data, and the ability to seek and search structured and semistructured, unstructured data, etc. The implementation of Data Lake by SEBI is already underway.
A Step in the Right Direction
In June 2021, SEBI called for expression of interest (EoI) from established, reputed, and reliable solution providers to implement data analytics projects and build data models.
In terms of eligibility criteria, as per SEBI, the bidding service providers should have been in operations for at least three years. In addition, they should have successfully implemented projects in analytical model development with a certain cost, particularly for a regulatory body or a banking and financial institution over the last seven years.
At the time, SEBI had stated that the interested party should be ‘fit and proper.’ Meaning, it should not be a blacklisted firm due to unsatisfactory performance, breach of instructions, fraudulent or any other unethical business practices.
SEBI is a statutory body that operates within the legal framework of the Securities and Exchange Board of India Act 1992. Its statutory objectives include protection of interest of investors in securities, promotion and development of the securities market, and regulation and supervision of the securities market. However, in March 2021, SEBI put its proposed data analytics projects on hold after most shortlisted firms opted out due to low budgets.
Other Key Technology Initiatives
Keeping up with the challenges and demands of markets, SEBI heavily invests in technology to improve its productivity and speed of response to the market. Here are some of the key technology initiatives taken up by SEBI:
- Installing a new and modern data centre.
- Operationalisation of SEBI’s own network security operations centre (NOC-SOC).
- Setting up private cloud infrastructure to facilitate rapid scaling of all its systems.
- Setting up a data lake for enhancing SEBI’s data analytics capability for both structured and unstructured data.
- Revamping its network and connectivity across all its regional and local offices.
- Workplace productivity is enabled by going mobile with SEBI’s own internal workflow portal and facilitating secure work from home access.
- A new system for digital tracking of all internal files
- Enhancing the end-to-end case management system of SEBI that tracks enforcement actions.
- Enhancing its access to data by entering into a data-sharing memorandum of understanding (MoU) with other government bodies.
- Setting up an innovative internship programme that gives exposure to young people to the technology function in SEBI.
- Streamlining the procurement process of SEBI for greater transparency and better governance, including setting up independent external monitors (IEMs) mechanism.
