Antitrust law and data processing: With big data comes big responsibi­lity

Dünya Executive - - BUSINESS - TOGAN TURAN PARTNER, PAKSOY [email protected] ILAYDA GUNES ASSOCIATE, PAKSOY [email protected]

Introduct on

Through rapid digitaliza­tion and agile technology, the concept of “data” has become the new raw material of business, regarded as an economic input almost on a par with capital and labor. As modern computing power has expanded, our ability to collect, process, store, and analyze data on a large scale has also raised complex questions about the commercial nature of the accumulate­d “big data” and the implicatio­ns for competitio­n in numerous industries across the global economy. In that same vein, as Artificial Intelligen­ce (AI), Machine Learning (ML), and the Internet of Things (IoT) promise to render big data analytics a central feature of virtually every area of commerce, antitrust experts – lawyers, economists, and agencies – are struggling to define big data in the parlance of antitrust and analyze it in light of the world’s antitrust laws.

What s “data” n the eyes of ant trust enforcers?

Before delving into which characteri­stics of big data are antitrust-related, it is of vital importance to see what exactly “data” is from an antitrust law perspectiv­e. At its simplest, “data” is a product and the same antitrust law analysis can be applied to it as is applied to any other product. In a similar manner, services founded on data can be analyzed in the same way under antitrust laws as any other service. The difficulty is that data is not finite in the same way as most products are, and therefore views differ wildly regarding its relative importance to competitio­n. Some argue that large data sets that require a more sophistica­ted database and software techniques to process (also known as “big data”) is an important barrier to entry because data is difficult to collect, access, replicate, and process. Others assert that “[d] ata-rich companies are not an economic threat but rather an important source of innovation, which policymake­rs should encourage, not limit” because data – especially consumer data – is readily available, non-rivalrous, and ubiquitous, in that multiple entities can collect and use the same data without raising foreclosur­e concerns. In the midst of this hot debate, understand­ing regulatory authoritie­s’ current thinking on the topic is essential for organizati­ons who wish to navigate successful­ly through a rapidly changing commercial landscape.

What s the key regulatory author t es’ current th nk ng on b g data?

A well-accepted truism is that control of large amounts of data raises the possibilit­y of giving companies an unfair advantage over competitor­s, allowing them to use their market power to harm consumers and competitor­s. This is drawing intense scrutiny from antitrust authoritie­s in key jurisdicti­ons around the world. Europe, in particular, has focused significan­t attention on antitrust and big data: In November 2015, the UK’s Financial Conduct Authority issued a call for input in relation to big data in the retail general insurance sector. In May 2016, the French and German antitrust authoritie­s published a joint paper, titled ‘Competitio­n Law and Data’. Following France and Germany, the Italian Antitrust Authority has just launched its first sector inquiry into big data together with the Italian Communicat­ions Authority and the Italian Data Protection Authority. Again, many big data-related issues have arisen during the e-commerce sector inquiry of the European Commission, the final report of which was published on May 10, 2017. Margrethe Vestager, the EU Competitio­n Commission­er, in her January 2016 speech, ‘Competitio­n in a Big Data World’ at the Digital Life Design Conference, acknowledg­ed the growing relevance of data in antitrust law. Later, in another speech on the use of pricing algorithms, she also brought up the issue of collusion risks which may arise from algorithms that are poorly designed or misused by an automated system.

With its antitrust legislatio­n closely modeled on the EU regime, Turkey is also paying ever-increasing attention to the phenomenon. The most recent instance in this respect, the Turkish Competitio­n Authority’s ‘Big Data, Online Platforms and Competitio­n Law Seminar’, organized in conjunctio­n with the Turkish Industrial­ists and Businessme­n’s Associatio­n (TUSİAD) on April 25, 2018, indicated that the Turkish Competitio­n Authority will keep a close eye on big data among a broader set of concerns arising from digitaliza­tion. The event is notable in that it gives insight into the Turkish Competitio­n Authority’s current thinking on the topic, which is essential to know for organizati­ons that aim to capitalize on big data and analytics.

What could be the potent al ant trust r sks ar s ng from b g data?

The accumulati­on of data is not problemati­c per se under antitrust law. However, could owning a significan­t data set make you a dominant player and therefore subject to added scrutiny? Or can a post-merger combinatio­n of data increase your market power, or increase barriers to entry? Does conduct in relation to big data seem to be exclusiona­ry (e.g. exclusive contracts, tied sales, refusal to provide access to data, discrimina­tory access, discrimina­tory pricing)? These competitiv­e analysis questions should be answered on a case-by-case basis, combining sector-specific market dynamics with legal knowledge. Still, an effective antitrust case analysis would always require questions in relation to the characteri­stics of the collected data as well, such as (i) who is collecting the data, how, and on what subjects; (ii) whether comparable data are available from multiple sources; (iii) what is the marginal value of additional data; and (iv) what is reduction in data’s value over time.

Antitrust authoritie­s in key jurisdicti­ons fear that big data can lead to abuse of dominance, especially where undertakin­gs hold unique datasets that cannot be replicated by competitor­s. This might lead to anticompet­itive exclusiona­ry conduct, typically in the form of exclusive contracts for the use of data or otherwise refusal to grant competitor­s access to certain data. Also, big

data can reinforce an undertakin­g’s dominant position in another market, for instance in markets where access to a particular data set is essential to enable competitio­n in an upstream/ downstream/neighborin­g market.

Alternativ­ely, in the applicatio­n of big data-related technologi­es (e.g. pricing algorithms), there might be room for collusion among competitor­s. Partnershi­ps can use algorithms to implement their agreement and fix certain price levels. In other words, pricing algorithms can function as a cartel instrument. Or, partnershi­ps may unilateral­ly decide to create comparable algorithms aimed at maximizing their profit, leading to parallel market behavior. Although parallel market behavior does not constitute an illegal action per se, it may yield the effect that competitor­s agree on common price levels more quickly. In relation to merger control, big data acquired entirely by a single company may increase barriers to the entry of new players in a relevant market. The biggest dilemma here is that merger control enforcemen­t in key jurisdicti­ons is triggered based on transactio­n parties’ turnover, but in the context of a growing digital economy and the increasing numbers of digital start-ups, tech companies often fail to generate high turnovers at first. Although their corporate value may be significan­t as a result of their degree of innovation, the data sets they have owned, or their market presence in the eyes of sophistica­ted customers, a merger involving such undertakin­gs may not trigger a merger control review due to their low turnover.

Conclus on

In recent years, the dramatic change in the magnitude and scope of data accumulati­on and organizati­ons’ increasing ability to process it through modern computing power have put the notion of big data in the spotlight of the antitrust law world. Many authoritie­s have already started to inquire into the sectors that are related to or mostly influenced by big data. Although big data’s actual impact on competitio­n among undertakin­gs is not clear yet, the general consensus is that the ability to generate and process large data sets can be associated to market power, and therefore an antitrust analysis should take account of its impacts (either pro- or anti-competitiv­e).

The traditiona­l antitrust approach can already address many data-related anti-competitiv­e practices, yet there are still uncertaint­ies and regulatory grey zones worth examining in the future. In the interim, undertakin­gs (especially tech companies) should watch out for granting exclusive licensing of or exclusive access to important data sets. Dominant market players should tread carefully when operating their business in order not to face new categories of abuse of dominance claims. On the merger control front, transactio­n parties should make sure that their ability to accumulate and process large data sets does not lead to the emergence or increase of entry barriers.

Ultimately, companies should use big data as an asset, similar to their use of more traditiona­l assets. In planning strategic big data-related transactio­ns, they must be aware of the characteri­stics of their specific data (e.g. how, by whom, and on what subjects the data is processed), together with the dynamics of the markets in which they operate. If a particular use of big data might be perceived as having anticompet­itive effects, companies must be prepared to justify their conduct to antitrust authoritie­s.

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