Refinement In Antitrust Regulation Of Big Data

Adv. Subramanya V. Mysore


“Big data” is a buzzword in the technology space of late; its reach is beyond the horizon. To name a few, big data is being devised in healthcare, public administration, sports, financial markets, and now in the legal realm. With increased penetration of big data in business operations and in daily interaction, it is subjecting everything that comes its way to a multidimensional transformation. However, with the change comes certain legal concerns, especially when there is no tangible regulatory mechanism in the domain of antitrust regulation in place and majority of the economies are still at the stage of gauging the broad impact of big data. This situation warrants the necessity of the existing antitrust laws to be tweaked to handle the excesses of big data. That is where this article fits in. It reflects the opinion of experts towards arming the statute for dealing with the ramifications of big data on antitrust territory.


Big data concept; antitrust regulation of big data; changes needed in competition regulation; effect of big data; competition law review committee.


Big data is generally defined as a pool of high volumes of data collected by firms in the data generation, segregation, and/or processing scenarios with high velocity, variety and veracity for value creation. Essentially, big data is a combination of “four V’s” as aforesaid. Big data offers a great opportunity to companies vying to get market dominion as it aids in attaining better profits, saving time, reduction of inefficiency, and providing greater market insight. It is estimated by the European Commission that by the end of 2020, big data would help in creating 100,000 jobs and could lead to 425 million euros in savings in Europe alone.

Data regulation is traditionally a task of data laws. However, when it comes to assessing the impact of data on fair market competition, the anti-trust regulators take the wheel. It’s interesting to look at the business approach of big data firms. They work on a two faceted model. They act as facilitators rather than players, for instance, a search engine will behave as an intermediary between the user and the service provider i.e. upon every click on a search engine, a digital trail is left behind by the user. Then, what the big data firms do is that they comb the trail left behind to assess the user’s choices or tastes and then create a virtual profile unique to that particular individual with the assistance of self- learning algorithms or AI tools. When the profile is created, they study it and offer targeted advertisements tailor made to lure that one user, which essentially renders the marketing strategy of such big data firms foolproof.


Now, the important question is- in the quest of achieving operational growth and greater profit margins, are these big data firms breaching any competition regulations? The answer is in the affirmative. Upon observation, it is quite possible that firms dealing with big data can enter into exclusive agreements to allow access to their reservoir of data for only their clients by excluding other firms who are in the same market. They can even opt for a blanket refusal to allow access to such data. Similarly, if the data is unique and cannot be replicated, the firm with a massive financial & operational outlay can use that distinctive data for its benefit at the cost of other small time entities resulting in foreclosure of competition, high barriers to entry and concentration of power. The algorithm-based AI tools are increasingly being used to collect and process consumer data by firms. If in case such automated technologies are allowed to determine prices and business pathways for profit maximization, the chances of colluding on prices and/or services can increase in parallel, it then becomes tough to fix liability generally and specifically from an anti-trust perspective.

In David Topkins case of U.S., the court penalized David Topkins and his co-conspirators who colluded to implement an agreement to devise specific pricing algorithms for the agreed-upon posters with the intent of making adjacent changes to their assigned prices. In Jet Airways, Spicejet and Indigo airlines case, the Competition Commission of India (CCI) imposed a fine after it was found that these airlines were uniformly overcharging their consumers in the name of fuel surcharge by colluding and behaving in a cartel-like manner with the help of algorithms. It’s possible that big data firms can even use privacy dimension of the consumer data as a currency and increase or decrease the privacy protection levels as per their business judgment and will. With the armor of data, firms can even discriminate consumers in terms of prices and/or quality of their goods by collusion or cartelization with other entities in the similar market. In Microsoft and LinkedIn merger, it was recognized by the European Commission (EC) that, private data of the consumer is a non-price factor in assessment of anti-trust mergers as it is vastly used in provision of services by these entities concerned. On similar lines, the EC fined Facebook after its WhatsApp takeover when it failed to disclose that Facebook could now use data from both the platforms to match their consumer strategy and behavior.


In order to deem an entity as anti-competitive in the data realm, it is necessary to assess factors such as the kind of data held in relevant market by such entities (whether the said data is personal/unique/substitutable and the possibility of the use of such data leading to tied sales in cross markets) or the ownership/control matrix of the said data (whether partly or wholly owned/licensable or non-licensable) or the essentiality factor of the said data for other downstream entities and finally, the “effect study” of the said data (whether the said data can be valued in monetary sense or from a strategic perspective.)


Globally, major antitrust regulators have already published policy papers and studies on the effect of big data on competition regulation such as the U.K’s Digital Expert Competition Panel and a joint report of Germany’s Bunderkartellamt and France’s Autorité de la concurrence suggest amending their domestic laws to incorporate the changes brought in by big data. In contrast, the CCI had observed, in the case of Vinod Kumar Gupta v. WhatsApp Inc. in 2017, that data protection issues or its breach needs to be regulated under the Information Technology Act, 2000 and the CCI’s purview is not applicable in the data arena. Nonetheless, the Ministry of Corporate Affairs, Government of India published a Report of Competition Law Review Committee in July of 2019. This report sheds light on the adaptations required for the Competition Act, 2002 to deal with big data regulation on the following aspects:

  • Definition of Price – The Committee reported that under section 19(7) (c) the “price of goods or service” yardstick to determine a relevant product market is inclusive of non-monetary parameters such as data and there is no necessity to consider data as a separate tool. The definition of “price” under section 2(o) was held to be wide enough to encapsulate any direct/indirect/relating/ostensible consideration as price.
  • Algorithmic Collusion – The Committee reported that the existing requirements for anti-competitive conduct under section 3 is sufficient for manual algorithmic collusion, however, for autonomous algorithmic collusion such as the ones used in hub and spoke cartels usually in the air transportation industry needs to be dealt with by adding an explanation on hub and spoke cartels in section 3(3). Also, section 3(4) needs to be widened to include such arrangements.
  • Online Vertical Restraints- The committee was of the opinion that, usually such agreements will be hit by section 3(4) (e) or (c). However, they noted that in case of an amendment in section 3(4), it shall include a list of possible agreements under its purview along with MFN (Most Favored Nation) clause bearing agreements which mandate a seller to maintain his sale price uniformly in all online platforms. Nonetheless, the committee reported that section 3(4) shall be devised on the “rule of reason” test by perusing the characteristics of the relevant market to counter any potential price or supply fixation.
  • Widening the Scope of section 3 and section 19(3) for assessing AAEC- The committee indicated that section 3 shall include “other agreements” as a new criterion to determine the anti- competitive conduct, as the vertical or horizontal assessment would be insufficient to detect anti-trust behavior for digital transactions and big data based business models. For section 19(3) the Committee held that, any new factor for inclusively assessing AAEC shall be notified in the regulations including a novel concept of “consumer harm”. For section 19(3) (c), the Committee observed “foreclosure of competition” as sufficient and held that “hindrance to entry” as part of it will narrow the provision’s purpose as it negates barriers to expand and reduction of existing competition. 
  • Data Control and Market Power- Noticing this issue, the Committee observed that with copious amounts of data at disposal, one does indeed provide any entity a competitive advantage in terms of tracing consumer habits and needs. However, it recommended that section 19 need not be amended to include “network effects” as a factor for assessing market dominance as section 19 (4) (b) includes “resources of the enterprise” which is broad enough to assess such data driven dominance.
  • Introduction of New Thresholds in Combination Notification- The committee observed that currently the thresholds of assets and turnovers would remain inadequate to assess the merger impact of data driven firms and suggested that the government come up with a forward-looking approach. In addition, data driven mergers can lead to difficulty in fixing jurisdictions, hence, the committee noted that “deal value” “size of transaction” thresholds needs to be explored under section 20(4).
  • Expansion of Factors Determining the Relevant Product Market and Geographic Market- By highlighting the importance of digital economy, the committee generally opined that, an “any other factor as specified in regulations” be added under section 19(6&7). For relevant geographic market, “characteristics of goods & services” and “costs associated with switching…to other areas” be added under section 19(6). For relevant product market, the committee held that, “switching costs” and “categories of customers” under 19(7) be added to make it more inclusive of the digital considerations.


In all, competition regulators are striving towards recognizing the impact of big data. The authoritative texts and executive observations can be treated as preliminary road maps for a long journey ahead as this field is still nascent and growing each day. Nonetheless, regulation needs to be dynamic and protect the consumer needs in real time, issues in forms of data dominance, data privacy violations, and data dictated business operations are to be dealt in conjunction with AI, smart computing and robotics from an antitrust regulatory dimension. Hence, the study of international best practices, a multi-stakeholder approach and further research on the endeavor of big data in the coming days will be crucial.


1 thought on “Refinement In Antitrust Regulation Of Big Data

  1. Such a useful article. I am reLly impressed by your topic. Thanks for sharing.


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