Indian markets today generate over 550 crore daily order and trade messages in the equity and equity derivative segments. In order to keep pace with the demands and challenges of markets, the Securities and Exchange Board of India (SEBI) is investing in technology to improve its own productivity and speed of response to the market.

With advent of technologies such as machine learning and artificial intelligence, it is essential for a regulator like SEBI to leverage sophisticated algorithms, artificial intelligence and machine learning to address critical challenges for data analytics arising when processing vast amount of data, either structured or unstructured. Further, it is also imperative for it to have resilient infrastructure such as data centres and cloud facilities to safely and effectively manage this ever-increasing data.

An analysis of the latest annual report released by SEBI for the year 2020-21 reveals the following key initiatives in recognition of the power of emerging technologies.

• Adoption of AI for surveillance: The future of surveillance will entail sophisticated deployment of technology to detect more complex and evolving manipulation techniques by fraudsters. It is proposed that the use of AI for data analytics and pattern recognition will aid SEBI in better identifying abnormal or fraudulent behaviour in the market including front running and insider trading. Technology will be used to simulate human intelligence to further refine its alerts system.
• Implementation of data lake at SEBI: This is expected to be achieved through a data lake solution which can support open source analytical tools such as R, Python, etc. with interoperable features. During the year, SEBI completed its tendering process for implementation of the proposed Data Lake. The proposed Data Lake will have characteristics such as visualization, time series/machine learning analytical capabilities, ability to seek and search both structured/unstructured/semistructured data, self-serviced business intelligence capabilities, in memory processing of data etc. The implementation of Data Lake is now underway.
• Setting up a new and modern data centre: SEBI had implemented a large scale tier 3+ data center. The new data center is currently hosting SEBI’s Private Cloud Infrastructure (SPCI). It is envisaged to consolidate infrastructure from other data centers in Mumbai to the new Data Center. The consolidation of all hardware will increase manageability of server side hardware and result in better turn-around times for service requests.
• Setting up private cloud infrastructure to facilitate rapid scaling of all systems: In 2020-21, SEBI implemented its private cloud infrastructure also known as ‘SPCI’. It is proposed that new and upcoming projects will utilize the SPCI and in most cases no separate hardware procurements will be required. Usage of commodity hardware will be encouraged where practicable. The SPCI is already hosting many applications such as Resource Person Portal, File Tracking System (IONS) and Data Lake.
• Academic programmes: The National Institute Of Securities Markets (NISM) is involved in designing and offering academic programmes that focus on creating a cadre of professionals in securities markets. During the academic year 2020-21, NISM has conducted training programmes on various topics including artificial intelligence, cyber security, blockchain etc. A Post Graduate Certificate in Management (Data Science in Financial Markets) was also organised.
• Policy initiatives: With a view to analyse complex bank statements, call data records, internal protocol detail records, hash functions to ensure the sanctity of data, handling of IT digital devices and adoption of data analytics to identify the pattern of relationships for unearthing sophisticated connections while investigating complex cases, a new cell namely ‘Connection Research and Analysis Cell’ (CRAC) under Integrated Surveillance Department was created in December 2020. Further multiple subcommittees were formed for various projects such as Data Lake, Data Analytics, Private Cloud, Network Revamp, etc.
• Employee training and development: Several employees were nominated for various self-paced training programs, largely oriented towards the emerging fields of data science and data analytics.

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