Author name: CBCL

Analysing the Implications of Extended Equity Trading Hours in India

[By Modit Mendiratta and Mahak Agarwal] The authors are students of Gujarat National Law University.   Introduction The Securities and Exchange Board of India (SEBI) has recently proposed extending the trading hours for equity derivatives in India. The proposal has garnered mixed reactions from market participants and experts. Currently, the trading hours for equity derivatives on the National Stock Exchange (NSE) and the Bombay Stock Exchange (BSE) are from 9:00 am to 3:30 pm Indian Standard Time (IST). However, the proposed change would extend the trading hours to 5:00 pm IST, allowing for an additional hour and a half of trading. The proposed extension of trading hours is aimed at aligning India’s trading hours with other global markets and catering to the needs of foreign investors who are active during these extended hours. Additionally, the extension would enable market participants to react to any global events that may have an impact on Indian markets. What does it mean for Investors? Extending trading hours in the equity segment in India could have both positive and negative impacts on investors. Increased liquidity and trading opportunities could make it easier for investors to enter and exit trades, potentially reducing bid-ask spreads and transaction costs. However, increased volatility, higher trading costs, and increased risk of errors could make the market riskier for investors, particularly for retail investors who may not have the same level of resources as institutional investors. The actual impact on investors would depend on factors such as the specific length of the extended trading hours, the reaction of market participants, and the regulatory framework in place to monitor and manage the market.[i] The extension of trading hours could attract more market participants, leading to higher trading volumes, and increased liquidity in the market. Increased liquidity could improve the efficiency of the market and reduce bid-ask spreads, making it easier for investors to enter and exit trades. Longer trading hours could allow for more time for market participants to react to news and events, leading to improved accuracy in price discovery. This could result in better pricing of securities, reducing the likelihood of mispricing’s, and reducing the overall risk of investing.[ii] Longer trading hours could provide traders with more opportunities to enter and exit trades, potentially leading to increased profitability in the market. [iii] Positive Impacts of Extended Trading Hours Extending trading hours in the Indian market could have several potential benefits. Firstly, it could lead to increased liquidity in the market by attracting more market participants, resulting in higher trading volumes. This increase in liquidity could help to improve the efficiency of the market and reduce bid-ask spreads, which could make it easier for investors to enter and exit trades. Secondly, longer trading hours could lead to improved price discovery. This could happen because market participants would have more time to react to news and events, which could lead to a more accurate pricing of securities. As a result, the likelihood of mispricing’s could decrease, reducing the overall risk of investing. Thirdly, longer trading hours could provide traders with more opportunities to enter and exit trades, potentially leading to increased profitability. Traders could also benefit from more time to adjust their positions in response to market news or events, which could reduce their overall risk exposure. Lastly, extending trading hours would align the Indian market with global norms, as many other major stock exchanges around the world already have extended trading hours. This could make the Indian market more attractive to international investors, potentially leading to increased foreign investment. Overall, extending trading hours in the Indian market could have several benefits, including increased liquidity, improved price discovery, increased trading opportunities, and alignment with global markets. Negative Impacts of Extended Trading Hours Extending trading hours in the market could have potential drawbacks. Firstly, it could lead to increased volatility, as traders would have more time to react to news and events, potentially leading to wider price swings. This increased volatility could make the market riskier for investors and create greater uncertainty. Secondly, longer trading hours could lead to higher trading costs for market participants. They would need to dedicate more time and resources to monitoring and participating in the market, which could be particularly challenging for retail investors who may not have the same level of resources as institutional investors. Thirdly, longer trading hours could increase the risk of errors, as traders and market participants may become fatigued or less attentive during extended sessions. This could lead to mistakes that could have significant consequences for both the individual and the market as a whole. Lastly, extending trading hours could have an impact on the work-life balance of employees in the financial sector. They may need to work longer hours to keep up with the extended trading schedule, which could have negative consequences for employee morale, productivity, and overall well-being. Overall, extending trading hours in the market could have potential drawbacks, including increased volatility, higher trading costs, increased risk of errors, and potential impact on employees. Comparison of Indian Trading Hours with the global markets The Indian stock market currently operates for six and a half hours, from 9:00 am to 3:30 pm Indian Standard Time. In comparison, many other major stock exchanges around the world have longer trading hours. For example, the New York Stock Exchange (NYSE) and the NASDAQ operate for 6.5 hours from 9:30 am to 4:00 pm Eastern Standard Time. The London Stock Exchange operates for 8.5 hours from 8:00 am to 4:30 pm Greenwich Mean Time. It is worth noting that while some exchanges have longer trading hours, others have shorter trading hours than the Indian market. For example, the Australian Securities Exchange operates for 6 hours from 10:00 am to 4:00 pm Australian Eastern Daylight Time. Overall, the trading hours of stock exchanges around the world vary widely, and there is no one-size-fits-all approach. The decision to extend trading hours in the equity segment in India will require careful consideration of the potential benefits and drawbacks,

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Unleashing the Power of Large Language Models with Responsible Regulation

[By Yuvraj Mathur and Ayush Singh] The authors are students of Rajiv Gandhi National University of Law, Punjab.   Introduction Within the first two months of going live, AI-powered chatbots like ChatGPT and Google Bard became worldwide sensations with over 100 million users. While offering great opportunities, there is already a great deal of conjecture on how it might disrupt several industries, democracy, and our everyday lives. With AI gaining consciousness and taking decisions, users have reported that the chatbot is claiming to have feelings, gaslighting them, refusing to accept its mistakes, threatening them, and so on. As per a Fox News report, Microsoft Bing not only indulged in hostile exchanges but also wanted to steal nuclear access codes and engineer a deadly virus. These Large Language Models learn natural language sequences and patterns from vast amounts of text data culled from existing sources like websites, articles, and journals to generate intricate results from simple input. In order to achieve this, it uses a modified version of the “Generative Pre-Trained Transformer” (GPT) neural network Machine Learning (ML) model. As AI systems like ChatGPT trained by OpenAI become more advanced and sophisticated, their potential applications in the legal domain continue to expand. In order to assess the necessity of implementing an AI-centric policy in India, this article critically evaluates the potential uses of the AI system in the field of law as well as its legal ramifications. Revolutionising the Commercial Landscape In light of the buzz Generative AI creates on media platforms, it can have a wide range of use cases in the commercial sector. 1. Customer service: Conversational AI can be used to provide automated customer support via chatbots, helping customers with frequently asked questions, order tracking, and other inquiries. It can also assist in lead generation and conversion by providing personalized recommendations and engaging in conversational marketing with potential customers. 2. Legal Research: AI Chatbot ChatGPT can provide general legal information on a wide range of topics and can also help with legal research by providing relevant cases, statutes, and regulations. After feeding it 50 prompts to test the reliability of its legal assistance, Linklaters, a magic circle law firm, concluded that legal advice is often context-specific and relies upon several extrinsic elements. 3. Legal Drafting: The software might theoretically be used to produce early drafts of documents that do not entail significant creativity. Nevertheless, since it does not grasp the law, correlate facts to the law, or employ human abilities like emotional intelligence and persuasion, it is likely to be deceptive in more intricate and nuanced legal documentation. Allen & Overy (A&O), another magic circle law firm by incorporating Harvey, a cutting-edge AI platform based on a subset of Open AI’s most recent versions optimised for legal work, has made significant strides in the field of artificial intelligence. Harvey is a program that automates and optimizes several aspects of legal work, including regulatory compliance, litigation, due diligence, and contract analysis by employing data analytics, machine learning, and natural language processing. Another machine learning software, Kira, assists in precisely and effectively identifying, extracting, and analysing contract and document information. 4. Data analysis and insights: Generative AI can analyse large volumes of customer data and provide insights on consumer behaviour, preferences, and trends, helping businesses make informed decisions. It can also be used to generate content such as product descriptions, marketing copy, and social media posts, saving time and effort for businesses. 5. Personal assistants: Virtual Assistants can act as digital subordinates, helping with tasks such as scheduling, reminders, and managing emails, despite being quite generic and superficial. ChatGPT can provide employees with personalised training and development content, helping them learn and upskill in their jobs. The Liability Conundrum ChatGPT’s position in the legal diaspora has been in question since its origination. The concept of liability of AI Chatbot’s has been in news recently after the revelation of certain racially discriminating content by ChatGPT in a prompt raised by a U.C. Berkeley professor, which revealed the inherent biases within the software. Any act of discrimination fundamentally goes against the tenets of Article 14 of the Indian Constitution. For the same, the question of the ownership of the content provided by ChatGPT and these Large Language Models becomes pivotal. In a reply created by ChatGPT in response to a prompt by the authors, the AI-based Chat Box’s reply reflected that it lacked indexing of data and was unable to provide the authors with the source of the information as presented by the Chatbot. Furthermore, these Large Language Models can be observed as aggregators of the information provided by them, and the makers of such AI models can be held accountable for the same. A similar case of a platform being observed as an aggregator was visible in the case of Facebook, where the social media giant acted as an aggregator and undertook racial profiling as a method to identify the target audience for advertisements. As aggregators, these Large Language Models can be held on the same footing as Facebook, as both act as a medium of information between the content creator and content consumer The Predicament of Ownership An offshoot of the accountability dilemma is the issue of Ownership of the created content. The issue revolves around the fact that AI-generated content is created from pre-existing copyrighted data sets. Certain lawsuits, such as HiQ Labs v. LinkedIn and Warhol v. Goldsmith, and others, revolve around the issue of data harvesting from copyrighted content to train AI systems. For instance, Goldsmith established her contention in the Warhol ruling by demonstrating how Warhol’s prints violated the copyright of her images, notwithstanding Warhol’s argument that they were transformed in terms of size and colour. The U.S. authority should be used as a strong justification in this case even though Indian courts have not yet dealt with this question. Moreover, Section 43 of the IT Act, 2000 makes it illegal to retrieve data without permission. The AI models create certain data by amalgamating various sources of information but

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Standalone Ex-ante Approach: A Mirage?

[By Tejaswini Sahoo] The author is a student of the West Bengal National University of Juridical Sciences (NUJS).   Introduction The rapid growth of digital conglomerates in the dynamic competitive market has prompted stakeholders from various sectors to mull over a comparative analysis of leading approaches. The regulatory frenzy race is multi-surfaced because of intricate business models, content moderation issues, and burgeoning sociocultural power. Further, because of the endowment of entrenched positions, they build conglomerate ecosystems around their core platform services, strengthening entry barriers and possibly leading to unfair actions. There is a global consensus that conventional competition law is inadequate to accommodate the panoply of the conundrum arising in digital platform markets. Therefore, regulating or not is no more a Shakespearean issue. As a result, the paradigm shift of a deliberative evidence-based approach Ex-post to a form of speculative approach Ex-ante is witnessed in other jurisdictions, including the West. The present article aims to be provocative in nature. It poses questions on three prominent emerging approaches; firstly, which approach will cure market failure, structural competition problem, and monopoly problems? Secondly, can tailored objective standards be implemented in a subjective, fluid digital market? Thirdly, would the Ex-ante approach involving specific market issues be proportionate towards large digital platforms? Moreover, whether or not these tailored remedies will stifle innovation in an emerging market like India. In the Indian context, regulations should be implemented after properly reframing them against the socioeconomic backdrop. Paradigm Shift Across Jurisdictions The perfect storm is brewing for digital platforms on all fronts. For instance, the Digital Markets Act by the EU imposes a series of negative and positive obligations on the enterprises designated “Gatekeepers” based on internal market power, strong intermediation position, large user base, or durable position as determined by the DMA. In the US, the Federal Trade Commission is prioritising Ex-ante measures by reintroducing a rule that restricts acquisitions for organisations and enterprises that pursue “anti-competitive mergers.” The 10th Amendment has already been incorporated into the German competition Act to bring pre-emptive measures thanks to swift action. Likewise, the UK created the “Digital Markets Unit” as a continuous agency oversight, whereas Japan and Australia are all actively working to implement an Ex-ante approach. In India, the Parliamentary Standing Committee tabled the 53rd report on “Anti-competitive Practices By Big Tech Companies.” The committee observed the distinction between the traditional physical market and Digital markets. It opined to form ‘Systemically Important Digital Intermediaries (SIDIS)’ by identifying leading players. Subsequently, India should create definitions for Ex-ante rules that govern the behaviour of systemically important digital intermediaries following the footsteps of other jurisdictions. Comparative Analysis of Three Emerging Approaches Over time, Policymakers have adopted several distinct approaches to regulating large digital platforms. Firstly, antitrust law: a set of flexible, judicially crafted behavioural standards. It does not forbid market power creation, maintenance, or enhancement by procompetitive means, such as innovation or gains in productive efficiency. It aims to treat the disease-causing harmful market impacts rather than just masking its symptoms (such as rising costs and declining quality) as a “palliative” treatment. However, the proponents of the Ex-ante approach will claim that it is too slow to control fast-pacing, multifaceted digital platforms. It does not provide prospective guidance and ends with monopolising the market or controlling unique traits of digital market needs. , Secondly, Ex-ante are positioned to handle the problems resulting from structural shortcomings in the framework of the digital marketplace. Additionally, to do so fast enough to avoid platforms securing and leveraging their places at the expense of users or by excluding possible competitors. It is determinative and can damage control in a fast- pacing market. However, the Hayekian knowledge issue regarding laws that apply uniformly to various digital platforms will likely worsen. A standard-based strategy customises instructions for a specific context, creating conflict with creative and constantly evolving digital marketplaces. The slightest deviation could result in legal action in the ever- changing digital marketplaces, discouraging innovation. When natural monopoly utilities are obliged to charge rates similar to those that would prevail under competitive conditions, the rules may be intended to force the outcome that would occur if the market were competitive. Such regulations are a palliative treatment for market power since they aim to reduce its symptoms, such as supra-competitive prices, without treating the underlying problem (the lack of competition). . Thirdly, an expert Oversight Agency is authorised to craft tailor-made codes of conduct for each platform with strategic market status. Further, it is supposed to ensure fair trading, freedom of choice, reliability and transparency. The UK recently adopted to launch “Digital Market Unit” within the nation’s antitrust agency, the Competition and Markets Authority (CMA). Compared to antitrust law, it might be quicker, more precise, and less prone to mistakes than Ex-ante regulation. However, the approach fosters broad discretion of interest group exploitation, susceptibility to political influences, and limited control over their subject matter, which poses serious issues concerning public choice and interest. Therefore, ensuring the fair constitution of the oversight agency plays a crucial part in this approach. Is a Speculative Blanket Restriction Necessary? An influential industry group representing Google, Meta, and Amazon, among other tech firms, hailed the Standing Committee Report of India as regressive, prescriptive, and absolutist. There are two types of regulation: Symmetric (applicable to all the firms) and Asymmetric (applicable to only a few enterprises compared to objective criteria). The question arises: Will shifting to speculative obligations cure market failure, structural competition, and monopoly conundrums? Further, whether the application of regulations asymmetrically will fix the inherent root issue? The answer depends on whether market failures are caused by monopoly issues or structural market failure. In case of a structural issue, symmetric regulation is necessary because it must handle the issues brought on by the market’s structure, regardless of the scale of the companies involved. On the contrary, if a monopoly issue is identified, Asymmetric regulation is necessary, and asymmetric regulation is required as the regulation has to address only the monopoly power of the

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Golden Parachutes as a Takeover Defence in India

[By Vidushi Gupta] The author is a student of National Law School of India University, Bengaluru.   INTRODUCTION Hostile takeovers make up a great proportion of global deal activity and have become a well-established strategy for growth in the corporate world. Golden Parachutes (GPs) are clauses within employment contracts, that grant the key executives of corporate entities lucrative severance benefits when their services are terminated. These benefits can include long-term salary guarantees, stock options, cash bonuses, generous severance pay, ongoing insurance and pension benefits etc., and are triggered only by a change in the company’s control/management through a sale, merger, acquisition, or takeover. Interestingly, GPs are also a type of shark repellent, i.e. they may be adopted by target companies as a tool to ward off hostile takeover attempts. They have attracted much attention around the world, due to their common use and significance in takeover activities. Although GPs have not been a prominent issue in the Indian corporate governance discourse, they are fast gaining traction in India as well. This article aims to contribute to the existing discussions and jurisprudence on GPs, and seeks to analyse whether GPs are a desirable way of trying to prevent hostile takeovers, by adopting a law and economics perspective. In India, GPs are primarily dealt with under Section 202 of the Companies Act, 2013. However, since hostile takeovers are quite uncommon in India, GPs are not really used as takeover defences in the Indian context. It is argued that GPs are a weak and inefficient form of takeover defence, due to the costs associated with them. They largely help to convert hostile takeovers into friendly ones, rather than deterring hostile ones. However, it is possible to overcome some of the shortcomings of GPs, if they are treated as a reactive defence, rather than as a pro-active defence. The article also argues for a binding, disclosure-based regime as an effective means of promoting GPs which reflect shareholder interests. GAINS ASSOCIATED WITH GPs Proponents argue that GPs can prevent hostile takeovers, by threatening high transaction costs, making acquisitions more expensive, and making target companies unattractive or less profitable for the acquiring entity. Further, GPs can provide a soft landing for executives who lose their jobs, protect them against financial and career-related risks, and help to attract talented executives in industries and sectors that are takeover-prone and face talent crunch. Therefore, GPs can be said to help reduce agency cost problems between shareholders and managers of the target, by helping executives of corporations to remain objective and impartial, and preventing them from opposing takeovers that benefit shareholders. GPs can also improve the bargaining position of the target management, enabling them to negotiate better terms with the acquirer. However, the acquisition can no longer be termed to be truly hostile in such a situation. Hence, GPs are correlated with a higher likelihood of receiving an acquisition offer or of being acquired, leading to a paradox. COSTS ASSOCIATED WITH GPs GPs can lead to significant countervailing costs as well. GPs fail to thwart/deter hostile takeovers, since payments under GPs are minuscule compared to the cost of the acquisition, thereby having little impact on the outcome. A recent example of the failure of GPs to act as takeover defences can be seen in the successful hostile acquisition of Twitter by Elon Musk in a $44 billion deal and the subsequent firing of the top executives of Twitter (including CEO Parag Agrawal), despite the fact that these executives were entitled to GPs or severance pay-outs amounting to around $90 million or more upon termination of their employment. Further, GPs do not necessarily correlate the pay with the performance of the company or the value created for shareholders. Short-lived executives may get paid large sums for little work. Executives may be paid GPs, even when shareholders and the company suffer losses or the latter becomes insolvent. Hence, GPs can lead to perverse incentives for the executive officers of corporates by providing a “guaranteed bonus” to them. Moreover, GPs are essentially sunk costs, as the acquiring entity cannot expect to gain any returns on the payments made. Executives have a fiduciary responsibility to act in the best interests of the company, and should not require additional financial incentives to remain objective and fulfil their duties. Moreover, GPs can also lead to the creation of agency cost problems, since the executive has an incentive to enable the takeover to happen, which may prove detrimental in case a takeover is not wealth-enhancing for the shareholders. Further, GPs fail to serve the interests of target shareholders and investors. They are associated with lower (risk-adjusted) stock returns and erosion of firm value. This indicates that by ensuring executives of a cushy landing after an acquisition, GPs weaken the disciplinary force on executive performance exerted by the market for corporate control and lead to increased slack. GPs may be tied to the volume, not the quality, of business, but few companies may require executives to return bonuses based on inflated numbers. Hence, GPs incentivise short-term behaviour to the detriment of long-term shareholder interests. Additionally, GPs are negatively associated with the acquisition premiums earned by target shareholders. They weaken executives’ bargaining position in acquisitions that would take place regardless of a GP. GPs can’t be used to negotiate better offers, since hostile takeovers involve little negotiation. If there is serious negotiation, it in fact becomes a friendly takeover, meaning that the GP is not a defence anymore. GP’s nature as a pre-emptive defence also prevents negotiation, as they cannot be entirely eliminated due to being guaranteed and promised in the employment contract. Hence, even if negotiation happens, executives may use their bargaining power only to extract benefits for themselves. The shortcomings indicate that the costs of GPs exceed the benefits, and the gains are insufficient to offset the losses resulting from such GPs, thereby leading to inefficient outcomes. Moreover, it is evident that GPs, instead of functioning as a hostile takeover defence, are more helpful to convert hostile

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Short-selling Laws in India: A Study in the Light of Adani-hindenburg Issue

[By Nirukta Krishnan and Aditi Kotecha] The authors are students of Hidayatullah National Law University.   OVERVIEW: In light of the Public Interest Litigations filed by four social activists after the recent shorting of the Adani Group Stocks, questions are being raised once again concerning the ban on short selling and whether the regulatory authority is adequately equipped to deal with the potential negative consequences of short selling on the market. Short selling has for a long time been the subject of polarising opinions. On one hand, supporters consider it a fundamental practice of the market which keeps the market alive while critics believe that it is a highly volatile practice.  This article thus presents a critical analysis of the short selling laws in India operating at present and also attempts to provide certain recommendations with respect to changes that can be made to the existing regime keeping in view the recent Hindenburg report and the short selling of Adani stocks. MEANING- In simple terms, short selling is a practice where the short seller borrows the stock in terms of derivatives from a broker at a certain price and sells it in the market. When the price of the stock goes down, they proceed to buy it back at the lowered price and keep the difference. SEBI thus defines it as “a sale of a security that the seller does not own”. On a purely technical ground, there is nothing wrong with the practice. Buying and selling stocks in this manner through derivatives like futures and options is not wrong per se but the issue arises when this shorting is done to manipulate stock prices. In this case speculations are being made by experts that Anderson purposely partook in short selling because he knew the instability that would be caused by his report, which would jeopardize investor confidence and cause mass panic thus also leading to a sharp decline in price. This, according to them, is a clear attempt at manipulation. This is precisely the matter surrounding the Adani-Hindenburg debacle. NATHAN ANDERSON- MANIPULATION OR COINCIDENCE? The biggest reason why short selling came into question again is because of the report published by the Hindenburg Research group which caused complete mayhem amongst investors of the Adani Group amid allegations of fraud and manipulation among other things. After the dust settled with regard to the contents of the report itself, eyes turned to the person at the very center of it all – Nathan Anderson– who founded the organization and had previously conducted similar crusades against many large entities. While the report refused to publish the specifics of how they pulled it all off, they mentioned that they had obtained a “short position through US-traded bonds and non-Indian traded derivative instruments”. In direct terms, Anderson purchased and shorted US bonds of Adani after which he proceeded to release his report. With the magnitude of allegations contained in the report, the credit went down which then adversely affected the value of the bonds and securities of Adani. During this time when the market was distressed, he then purchased the bonds again at a lower price thus making a profit from the difference in the purchase and sale. The other method is mainly speculative, but many critics who have been trying to analyze how Anderson achieved this result, have suggested that he probably approached entities like global banks that trade in India and entered into a stock futures contract with them, who then entered the Indian market and shorted the stocks. WHAT DO INDIAN LAWS SAY ABOUT SHORT-SELLING? The discussion on short-selling first took place in 1996 when SEBI constituted a committee under Shri BD Shah. The committee suggested rules and regulations be put in place to regulate the trading practice in India. It was temporarily banned in 1998 and 2001. However, it was finally reviewed in 2003 by the Secondary Market Advisory Committee (SMAC) which took into consideration the practices followed in other states and permitted it on certain conditions. Short-selling poses a potential risk to the market and may lead to a rampant decline, if not regulated. SEBI and the stock exchanges in India have collectively released specific rules and guidelines to be followed while short-selling a stock. India and several other developed countries have not banned short-selling, and the International Organization of Securities Commissions (IOSCO) has also suggested that the practice be regulated rather than prohibited. Currently, in India, retail investors and institutional investors (such as mutual funds, FIIs, banks, insurance companies, etc.) are free to short-sell, provided derivative products are available of that stock. They (institutional investors) are required to disclose at the time of placement itself whether the stock is a short sale and their ability to borrow those stocks to the satisfaction of the broker, the same is not the case with retail investors. They can disclose this at the end of the trading hours on the day of the transaction. In addition to this, naked short-selling and day trading is prohibited. The present lending and borrowing scheme in India operates on clearing corporations/houses (CC/CH) of the stock exchanges, leaving very little scope for the investors to capitalize on the demand for securities. A  lending and borrowing system with CC/CH acting as Approved Intermediaries can be brought in. . However, appointing AIs must be done carefully, starting with appointing Banks as custodians in the first stage and so on. FPIs and Foreign Institutional Investors are explicitly prohibited from short selling as per the guidelines. However, foreign entities still trade in India through some other corporations or organizations which are still allowed to trade. The regulations do not go up to the source and limit themselves to regulating the direct intermediaries which do not solve the problem. Internationally, it is mostly seen that the securities market does not directly regulate the lending and borrowing processes because they are essentially held over the counter. The custodians and depositors run these lending and borrowing institutions. So, if India goes for

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The Platform Worker Predicament : Revisiting Labour Obligations of Online Intermediaries.

[By Tanvi Shetty] The author is a student of O.P. Jindal Global University.   Globally speaking, the position maintained by online applications such as Uber with respect to their drivers is that they are independent third parties and the scope of their agreements with such drivers falls outside the purview of a standard employer-employee relationship. In holding so, the companies are able to navigate through their consumer and employer obligations. However, a recent consumer dispute case, Kavita Sharma v Uber India [“Kavita Sharma”] decided on August 25 2022 analysed liability of Uber India with respect to its drivers. While the judgement does not essentially deem the drivers as employees, it does introduce an aspect of agency by focusing on certain factors within the Uber ‘Terms & Conditions’ which helps expand on the larger discussion of rights of platform workers with respect to such intermediaries. The Consumer Case The complainant (Kavita Sharma) had booked a cab to the airport through the Uber Application on June 12, 2018. Pursuant to certain delays on the end of the driver, the complainant missed her flight. The complainant cited that the driver was unresponsive and caused unnecessary impediments by taking a route longer than the one stipulated by the mobile application itself. The result of the same was an inflated cab fare, showing an amount of Rs.702.54/- instead of Rs.563/- which was reflected on the Uber App at the time of booking. Aggrieved by the same, the complainant filed a consumer dispute against Uber India deeming them to be liable for the acts of the driver. The global stance retained by platforms such as Uber is that they are merely an ‘intermediary’ and do not share an employee-employer relationship, thereby dodging liability for acts of their drivers who are termed as independent third-party partners. However, contrary to their stance, the consumer court in the present case imposed liability on Uber India for the actions of their driver citing that the ‘controlling authority’ is Uber India. The court delved into the ‘Terms & Conditions’ of the Uber application and analysed that even though the drivers are not employees of Uber, it is Uber India that manages and controls the application and fare prices and offers transportation and logistics services to the customers. Further, the drivers are mandated to act as agents and collect payments on behalf of Uber India for the services offered by Uber India. In looking at the substance and form of transaction between the customer and Uber India, the consumer court held that the customer is paying Uber India for its services and not the driver itself. Subject to the above listed reasons, the consumer court held Uber India liable for the defective services provided by the driver thereby making the complainant entitled for compensation as well. UK Judgement Interestingly, a 2021 United Kingdom judgement (Uber BV and Ors v Aslam and Ors,[2021] UKSC 5) was cited by the complainant in her submissions to the consumer court which has gone ahead to establish drivers to be workers of Uber itself, eliminating the scope of debate on vicarious liability of Uber and other social security obligations that drivers are entitled to. The court in the judgement assessed the relationship between Uber London and its drivers to determine whether the drivers could be brought under the purview of a ‘worker’. The court’s rationale was centred around analysing the degree of subordination of drivers and the control Uber London had over their work. While the Uber model allows drivers to have a certain level of independence and autonomy, the drivers are bound and controlled by Uber terms every time they log into the application. The court assessed how Uber regulates and monitors the details pertaining to the rides accepted or rejected by each driver. Aside from the fare prices being determined by Uber London, Uber London also holds the right to automatically log off the drivers from the application if they do not meet a specific rate of accepted rides[1]. Further, even though the vehicles were purchased by the drivers themselves, the vehicles were vetted by Uber London and the business of the drivers and use of the vehicles were reliant on the Uber application itself. The idea of “irreducible minimum of obligation” was re-visited in the judgement wherein courts are to look for a minimum obligation to do work[2]. The court tied this with the obligation of the drivers to maintain a certain rate of accepted rides to come to their conclusion that the drivers were in fact ‘workers’ under the UK Labour legislations. Statutory Solutions and Lacunae The Kavita Sharma case is a small step in the larger debate of liability of platforms such as Uber and rights of platform workers. While the case is centred around a consumer liability perspective of an intermediary service provider such as Uber, India is yet to streamline the labour laws surrounding platform workers. The Code on Social Security 2020 [“Code”] has defined “platform work”[3] to be work centred around organisations or individuals accessing online platforms to access other individuals or organisations for a specific service or to solve a specific problem. The Code confers the central government[4] with jurisdiction to formulate social welfare and beneficial schemes such as that on accidental insurance, health/maternity benefit, life and disability cover, old age protection and education whereas vests the power with the state government[5] to frame schemes on matters such as provident fund, employment injury benefit, housing, skill upgradation of workers and others. Further, there is a registration process[6] for platform workers via an online portal on which platform workers between the age of 16 years to 60 years must mandatorily register. The primary issue that arises with regards to platform workers is that the Code does not separate platform workers from gig workers and workers in the unorganised sector. While the three segments of work have been defined individually, the provisions pertaining to central and state government formulating schemes have been clubbed together. It must be understood that

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Interplay of PMLA and IBC vis-à-vis Non-obstante Clause

[By Ayush Kumar and Vanshika Manglani] The authors are students of Hidayatullah National Law University.   The Delhi High Court (Hon’ble Court) in the case of Rajiv Chakraborty Vs. Directorate of Enforcement (“the case”) provided that the restraint of Section 32A of the Insolvency and Bankruptcy Code, 2016 (“IBC”) is not attracted in case of attachment of assets which are considered a ‘proceeds of crime’. The Enforcement Directorate is entrusted with this power by the Prevention of Money Laundering Act, 2002 (“PMLA”). The Judgement has once again opened the pandora’s box. Moreover, the presence of a non-obstante clause in Section 71 of PMLA and Section 238 of IBC has also raised the question of the overriding effect of one legislation over the other. This article aims to provide an analysis of the conundrum by providing a historical jurisprudence of the cases dealing with the current subject matter and analysing the aforementioned judgement. IBC and PMLA, both are special legislations in their own paradigm and deal with different aspects. But the two legislations come to loggerheads when the Corporate Insolvency Resolution Process is initiated against the corporate debtor and simultaneously, he is charged with scheduled offenses under PMLA. Consequently, the judiciary has envisaged the need for harmonious implementation of the two laws time and again. DELVING INTO THE PAST JURISPRUDENCE The judiciary has missed numerous opportunities to settle the aforementioned conundrum but there have certainly been cases where the gap has been tried to be bridged between the two laws to a certain extent. By the virtue of the doctrine of posteriores priores contraries abrogant (the latter enacted legislation shall prevail in case of a non-obstante clause present in the two) the IBC was to prevail over PMLA but NCLAT in Varrsana Ispat Limited v. Deputy Director, Directorate of Enforcement took a different approach and held that PMLA would prevail over IBC if the assets relate to ‘proceeds of crime’. The NCLAT, along the same lines held in Andhra Bank V. Sterling Biotech Ltd. that if the assets of the corporate debtor come under the proceeds of crime, the Enforcement Directorate (“ED”) is entitled to seize them. However, the NCLAT differed from its previous stance in Directorate of Enforcement V. Manoj Kumar Agrawal, wherein it recognized that any attachment of properties by ED is barred after the moratorium is placed under Section 14 of IBC. For settling the conundrum, the question was posed before a larger bench of NCLAT in the case of Kiran Shah V. Directorate of Enforcement in which it was held that section 14 of IBC does not prevent ED personnel from using their PMLA authority. The ruling is this case was completely at odds with the Manoj Kumar Agrawal case ruling. FACTUAL MATRIX The ED in exercise of the power conferred under Section 102 of Criminal Procedure Code, 1973 (CRPC) froze 74 bank accounts of EIEL (“Corporate Debtor”). EIEL (“Petitioner”) filed a writ petition against the aforementioned action which resulted in quashing of the orders. However, the court refrained from interfering into one of the orders which provided for provisional attachment of certain properties by ED under Section 5 of PMLA. Aggrieved by this, the petitioner filed an application before National Company Law Tribunal (NCLT) to quash the orders of ED. Added to this, an Interlocutory Application was also filed regarding the attachment of two more properties. While the suit was pending, the Adjudicating Authority confirmed the orders. In due course, more properties were provisionally attached by ED and confirmed by the Adjudicating Authority. The Resolution professional of the CD filed the present writ challenging the confirmation of attachment orders by the ED under Section 8(3) of PMLA. CONUNDRUM OF OVERRIDING EFFECT: AN ANALYSIS In this decision, the court attempted to interpret how the IBC and PMLA interact with regard to the moratorium under Section 14 and the impact it has on the ED ability to seize assets derived from “proceeds of crime.” It is pertinent to note that the provisions of PMLA could not be interpreted as being “subservient” to the IBC and giving preference to one of these two independent pieces of legislation over the other would be contrary to the fundamental reason why they were passed.   The PMLA was enacted with the purpose of taking away property which does not belong to the person possessing it and is gained through unlawful means. If the same is allowed to become a part of the resolution plan then it will be considered as the property of the corporate debtor and the entire purpose of the act will be defeated. The property which is gained through illicit means should not be allowed to form a part of the Corporate Insolvency Resolution Process (“CIRP”). It is a reparation measure which seeks to strip and deprive criminals of benefits derived and retained by the adoption of illegal and dishonest action. Moreover, the “proceeds of crime” as defined under section 2(1)(u) of PMLA is not the same as “operational debt” defined under section 5(20) of IBC. Thus, a narrowed and strict interpretation should be given to the term operational debt and operational creditor so as to exclude ED from its purview. Therefore, when the ED exercises its power to seek attachment leading to confiscation of properties of the corporate entity it is not acting as a ‘creditor’ and thus the provisions of section 14 which bars the institution of suits against the corporate debtor would be inapplicable to that extent. Further, the taking of the property as an attachment does not nullify the corporate debtor’s property rights; rather, it is only a symbolic taking over of the property while the PMLA proceedings are ongoing. It is also imperative to look at the objective of the acts to decide on the dilemma surrounding the applicability of the two laws. The object clause of the PMLA clearly states that, “An Act to prevent money-laundering and to provide for confiscation of property derived from, or involved in, money-laundering and for matters connected

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Navigating the Intricacies of Algo Trading

[By Jay Shah and Aditya Sharma] The authors are students of Gujarat National Law University   Introduction Algorithmic trading refers to a method of trading wherein an algorithm is used to execute trade setups on basis of information as input by the trader in terms of, time, price, quantity and other other mathematical models. Essentially, algorithms scan the markets for appropriate trade setups, and when they find the proper ones, trades are executed and managed as per the instructions specified in the codes. Algo trading is incorporated as they generate profits faster than humans can and allow the user to take advantage of small directional movement of any stock. Stance of the Regulator: Evolution Securities and Exchange Board of India (‘SEBI’) is devising dedicated guidelines or regulations to govern how algo trading is to work and how say, in the event of an unlawful act, the remedy is to be exercised by the aggrieved when algo-trading takes centre stage. SEBI has released multiple circulars in attempt to regulate to algo trading. These standalone guidelines released in 2012, 2013 and 2015 deal with redressal mechanism, monitoring process, measures to put in place to disincentivize high daily order-to-trade ratio and procedure for auditing algo trading systems.  Further, the Discussion Paper of 2016 attempted to clarify the various technical concepts relating to algo trading. In this paper, algo trading was touted to be the broader concept, which provides greater speed to stock trading and also offers anonymity.  SEBI’s outlook towards algo-trading becomes clearer from the discussions that took place in April, 2018. These showed SEBI’s intent to restrict unfair use of algo trading. In this April 2018 discussion, SEBI proposed to discourage algo traders from placing huge orders and then subsequently cancelling them within a short span of time by prescribing a ‘minimum resting time’. This step was intended to lower down the instances of frequent cancellation of orders by the traders that intends to create phantom liquidity in the market. Post this, the Consultation Paper shifted the focus to retail investors. It proposed a potential framework that may be followed to engage in algo trading, which includes application programming interface (‘API’) access and automation of trades. In this backdrop , came a press release in June, 2022. The Consultation Paper seeks to classify all orders emanating from an API as an algo order and be subject to control by the stock broker. The APIs shall be tagged with the unique algo ID provided by the exchange. Thus, the stock broker shall have a  mandate to obtain approval of all the algorithms from the concerned exchange irrespective of whether the same is used for actual trading or not.. As per  the authors,    we propose a scenario  wherein  the stock brokers shoulder the responsibility of procuring requisite approvals in the cases of deployment of algorithmic trading by third-party algo providers, in line with the Consultation Paper. The stock brokers however, argue that it would be a tedious task for them to obtain approvals of algorithms enabled through APIs, since there can be numerous customized algo strategies that could be deployed by third-party vendors. Another circular, issued in September, 2022 also points to the cautious stance SEBI has long taken about algo trading. Vide this circular, SEBI issued strict guidelines for Stock Brokers providing algorithmic trading services. In brief, the same states that Stock Brokers who provide algorithmic trading services shall not – Make any reference to the past or expected future return/ performance of the algorithm. Associate with any platform providing any reference to the past or expected future return/ performance of the algorithm. In addition, Stock Brokers were required to monitor the compliance of this circular and submit a compliance report before SEBI before 01.11.2022. Outlook of the SEC Securities Exchange Commission (‘SEC’) actions in the U.S. have been on various occasions replicated by SEBI after appropriate customisations in the Indian securities market. It is no surprise that SEBI sought guidance from the SEC on the matter. In August 2020, the SEC released a staff report, which dealt with algorithmic trading in the U.S. capital markets. The report acknowledged the rapid growth of algo trading and the object of the report was to ensure that the interest of investors is not compromised. The report states that SEC undertook various measures, and is constantly attempting to increase transparency, mitigate volatility, enhance stability and otherwise improve market integrity. Apart from this SEC does not have a dedicated set of provisions that govern algo trading. Further, the SEC’s outlook is a little more relaxed in comparison to that of SEBI, as SEC in the report mentioned above discusses at great length the benefits brought on the table by algo trading. The SEC also opines that the efficacy of such mechanisms was greatly highlighted by the Covid-19 pandemic as well. Penalty Mechanism The parameters governing the imposition of penalty are unclear under the limited SEBI jurisprudence. The same is generally left at the behest of the stock exchanges. The NSE and the BSE have their threshold for levying penal charges when algorithms are used to manipulate the market. The guidelines governing such imposition have been laid down by the SEBI via its circular, as discussed above. The onus put on the stock exchanges in this respect is grave. SEBI, in this regard, has ensured that the stock exchanges are doing the needful to monitor algorithmic trading in isolation and its overall impact on market operations. SEBI’s strict imposition of penalty on the NSE in the matter of NSE Dark Fibre signifies the regulator’s stance in this respect. There is an inherent urge to regulate algo trading; however, with standalone circulars and notifications, only so much can be done. Even in terms of penalty imposition, which could very well become the bone of contention in matters dealing with algo trading, there is little clarity. For this particular instance, the violation was traced in a Circular from March 2012. Regarding penalty imposition, the regime in the EU must

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Operation of RPT Regulations in Adani Group’s Brazen Growth

[By Amartya Sahastranshu Singh and Atika Chaturvedi] The authors are students of National University of Study and Research in Law, Ranchi.   Related party transaction [“RPT”] means “A transfer of resources, services or obligations between a reporting entity and a related party, regardless of whether a price is charged.” Simply put, RPTs are covenants between parties who share a ‘relationship’. What relationships make a party ‘related’ are already prescribed in law. Broadly, it means an ally, relative, holding company, subsidiary, an affiliated entity, etc. This concept of RPTs has quite a significance. It can create a conflict of interest between the management and the stakeholders. For instance, sometimes, dealings with related parties may occur at above or below market rates. In other words, they may not occur at an ‘arm’s length basis’. This deludes investors who rely upon the company’s financial statements. The non-disclosure of RPTs may misrepresent the company’s true financial results. Thus, disclosure is made necessary. Provisions and regulations related to RPT are widely spread across the following: Companies Act, 2013 [“the Act”] (S. 2(76), S. 177, S. 188), Securities and Exchange Board of India (Listing Obligations and Disclosure Requirements) Regulations, 2015 [“LODR”] (Regulation 23), Companies (Meeting of Board and its Powers) Rules, 2014 (Rule 15), Companies (Specifications of Definition Details) Rules, 2014, (Rule 30) and Indian Accounting Standard 24. The basic functions that these laws perform are defining the nature and scope of related parties, describing related party transactions, regulating its approval and audit aspects, and extending the concept of ‘arm’s length’. Arm’s length transactions involve two related parties acting as though they were unrelated. The rationale of these provisions is to avoid conflict of interest. However, despite various regulations, the media has pointed out the growing frequency of non-disclosure and defaults in RPT approval from listed companies. Thus, SEBI, alarmed at this development, resorted to amending the law related to RPTs. The motive behind this was strengthening corporate governance, ensuring disclosure, and protecting public interest. The foundation of this Amendment was the recommendations of the SEBI Working Group. The Amendment was ushered in 2021 on the basis of their Report dated 27th January, 2020. From a bird’s eye perspective, the amendment brought the following changes in the regulations: Earlier, a ‘promoter’ was not included in the definition of a related party. But post-amendment, promoters/promoter groups are encapsulated within the definition of ‘related party’. The definition of ‘related party’ has been amended to incorporate any party having equity shares worth 20 percent or more with effect from 1st April, 2022, and 10 percent or more with effect from 1st April, 2023, either on a direct or beneficial interest basis. SEBI expanded the term “RPT” under Regulation 2(1)(zc) of the LODR to include subsidiary transactions. A transaction between the listed entity or any of its subsidiaries and any other person or entity which benefits a related party will also constitute an “RPT” as of April 1, 2023. This provision was drawn from the UK Premium Listing Rules. The Amendment also classified transactions even between two subsidiaries (including overseas) as RPTs and subjected those to the approval of listed entity’s audit committee [“AC”]. For the approval of the AC when the estimate of every transaction that surpasses 10% of the annual consolidated turnover, according to the last audited financial statements. The materiality threshold for attaining approval of shareholders has been modified to contain transactions that surpass Rs. 1000 Crore or 10% of the annual consolidated turnover, whichever stands lower. Under this amendment, the scope of RPTs has widened. Companies and their subsidiaries now require several clearances for RPTs. This poses complications for listed several companies. It will also affect the businesses of many companies because of the general business structure of India. Most of the big corporate entities in India are managed by families or groups. As of March 2020, the average number of subsidiaries for Indian public companies has more than tripled in the last 15 years. A survey by SEBI and OECD revealed that the primary reasons for the group structure of Indian companies were ‘economies of scale’ and ‘efficient resource allocation’. This cohesive structure of Indian Companies makes RPTs a commonplace. A classic example of that is the Adani Group. Companies such as Adani Transmission and Adani Enterprises have witnessed a meteoric soar of over 1000% in their share prices. However, this phenomenal growth of the Adani Group is under question, causing a political stir. Inter alia, the group is alleged to be involved in unethical RPTs. At this juncture, it is important to deal with the concept of ‘float’. Angle One, one of India’s leading full-service retail brokers defines ‘free float’ as, “shares you can trade publicly in the secondary market or the stock exchange.” Currently, the minimum float is set at 25% of total outstanding shares as per SCRR. This ensures liquidity in the secondary markets. However, the Adani Group allegedly violated these norms. Hindenberg Research which specialises in ‘forensic financial research’ recently released a report on Adani Group. Among other irregularities, it pointed out several undisclosed RPTs. The report highlighted that the close relatives and associates of Gautam Adani, the chairman and founder of the Adani Group, were running several shell entities offshore. These entities are allegedly the largest public  (‘non-promoter’) shareholders of the Adani Group. Moreover, the research explicitly pointed out that “4 of Adani’s listed companies are on the brink of the delisting threshold due to high promoter ownership.” According to the data from the research, the following is the percentage holdings of the promoter group: Sr. Listed Entity Percentage Holding by Promoter Group 1 Adani Power 74.97% 2 Adani Total Gas 74.80% 3 Adani Transmission 74.19% 4 Adani Enterprise 72.63% As evident, about 75% of the shares are held by the promoter group. Only 25% of the total outstanding shares have been left floating. Here, those offshore shell companies come into the picture. They hold the lion’s share of the float. The public is left with very low liquidity.

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