Advertisement
Over the past few years, the regulator has been betting big on technology to address and handle challenges arising out of technological advancements in the markets.
Data lake is a system that stores vast amount of data in its native form at any scale. To provide ‘data lake’ solution, the markets regulator had issued a notice in May, 2019 – inviting expression of interest (EoI) from the interested parties.
The regulator in September last year had shortlisted seven companies – Infosys, Wipro, Accenture Solutions, Capgemini Technology Services India, Hewlett Packard Enterprises (India), EIT Services India, Infosys, Wipro and Larsen & Toubro Infotech – “for further process.”
Related Articles
Advertisement
It, further, said responses will be entertained only from the shortlisted bidders.
“Responses and bids from bidders other than the shortlisted ones will not be opened and will summarily be rejected,” it added.
The capital markets watchdog plans to leverage artificial intelligence, machine learning and deep learning to address critical challenges for data analytics impacted by the processing of vast amount of data, either structured or unstructured. As part of this project, the bidder is expected to build a data lake with analytical capabilities.
The data lake will contain large amount of structured (order, trade data among others), unstructured (annual reports and Sebi orders) and semi-structured data (XML – a markup language designed to store and transport data). It encodes documents in a manner that is both human and machine-readable.
As the trading volumes are growing at an astronomical rate, a need is felt to build a data lake which can handle structured, semi-structured and unstructured data from multiple sources.
In January, Sebi chairman Ajay Tyagi had said that the regulator is acquiring capabilities to monitor and analyse social media posts to keep a tab on possible market manipulations. Further, he said new plan involves creating a ‘data lake’ project to augment analytical capabilities.
“Catching malpractices in the market using the standard tools that analyse only structured data of price and volume is increasingly getting difficult. “We want to acquire technology and unstructure data analysis because the structured data analysis is not helping much, manipulators use all sort of things,” Tyagi had said.