Not a week (or sometimes even a day) goes by without news from somewhere around the world relating to the subject of competition law and data; whether it is competition authorities calling for stricter competition laws to tackle potential adverse effects of big data, or experts debating how to apply competition rules to digital markets. However, there seems to be a lack of clear understanding among companies as to what this all means for their businesses.
There is no doubt that the relationship of data and data protection legislation with competition law is currently a hot topic around the world. Data, including personal data, is an increasingly important and necessary asset in almost any business or market. The interrelationship between competition law and data concerns all companies which offer digital services or hold significant data assets – it is not something that only tech giants such as Google and Facebook should be concerned about.
Competition authorities, which frequently address the topic in papers, discussions and public speeches, seem to be worried about effective competition in the data economy. As a result, various different solutions have been proposed, ranging from forced data sharing and vigorous sanctioning to simple cooperation between the data protection and competition authorities.
Companies, on the other hand, are facing uncertainty as to the scope of the relevant legal rules. While waiting for the authorities to issue concrete guidance for companies, we will try to clarify the matter in light of the current regulatory environment. In this article, we discuss data-related abuses of dominant position, pricing algorithms as well as merger control, and the circumstances under which access to or use of data or technology could become an issue under competition law.
Data-related abuses of dominant position
Competition law imposes special obligations on companies which are in a dominant position. Although it is not illegal to be dominant, such companies are required not to abuse their dominance. The way a company uses its data can be one factor leading to a finding of dominance or it can constitute an abuse of a dominant position.
A well-known example of a case where the use and excessive collecting of personal data was investigated as an abuse of a dominant position is the case initiated by the German competition authority (Bundeskartellamt) against Facebook’s data collecting activities (case still ongoing). A central question of the case is whether Facebook’s terms and conditions are in violation of the German data protection laws and whether the use of such allegedly unlawful clauses constitutes exploitative conduct prohibited by competition law.
In addition, potential data-related abuses can concern e.g. data or algorithms being used for anti-competitive price discrimination, concluding exclusivity arrangements or in other ways preventing access to data, or granting access to data in a discriminatory way.
Key issues to consider:
- To understand whether you may be in a dominant position in some market(s) due to your data assets, carry out data mapping and assess whether you hold essential data. The risk of a dominant position is highest if your assets are not replicable or substitutable and they are essential for competing on the market or on one or more neighbouring markets.
- Assess whether your customers are locked in, g. due to strong network effects. If customers are effectively locked in to your service and there are no credible alternative service providers, you may have significant market power.
- Assess whether access to the data poses a relevant barrier for market entrance. Such a situation may exist, for example, if collecting and analysing the data involves high up-front costs but low running costs (e. in case of scale effects). If customers use several service providers to receive the same type of service (referred to as multi-homing), access to data should, however, usually not be a relevant entry barrier.
- Be aware that the validity of your personal data processing activities may be more vigorously assessed if you have significant market power or your customers are locked in to your service.
Pricing algorithms and digital cartels
A key concern for the competition enforcers in relation to pricing algorithms and artificial intelligence (“AI”) is that they may be used as a way to make price-fixing more effective. In addition, competition concerns may arise, e.g. in relation to pricing algorithms that track competitors’ prices and automatically adjust a company’s own prices to match those of the competitor. Such algorithms may reduce companies’ incentives to compete effectively. In the worst case, untracked self-learning algorithms could even lead to unintentional collusion between competitors.
Key issues to consider:
- Keep track of your pricing algorithms and how they work.
- View AI as one of your key employees whose actions need to be law-compliant – companies are held liable for the actions of their automated systems.
- If your company provides software which is used by competing companies, make sure it cannot be used for information exchange or as a way to harmonise pricing between competitors.
- Ensure that adequate technical safeguards are in place to prevent algorithms from self-colluding.
Data and merger control
In merger control, data protection issues have previously been raised in cases involving the provision of free services in data-intensive fields. When pricing is not a relevant issue, competition authorities may turn to non-price concerns, such as data protection.
However, competition authorities have also started to express worries that the accumulation of big data or the combination of different data sets due to mergers may create barriers to entry and restrict competition. It is likely that concerns relating to the access to or use of customer data will be increasingly dealt with in merger control analysis in the future.
Key issues to consider:
- Assess whether either party holds important data sets that are essential in order to compete with the merged entity. It is not required that the parties hold significant amounts of data, but rather whether the data sets are valuable and necessary to compete effectively. However, if the data is easy to duplicate, data assets should generally not constitute a major obstacle for the merger to proceed.
- If the combination of the data assets of the acquirer and the target would impede effective competition within the meaning of merger control rules, consider whether such concerns could be corrected with remedies, such as effective data access commitments.
Companies should be aware that also data-driven businesses may be investigated under competition rules and that practices which would be illegal in the physical world are also prohibited in the digital world. However, competition law assessment requires complex economic analysis every step of the way and this is even more so when it comes to novel data-related issues.
Market dynamics in digital markets are typically fast moving and different from the dynamics of more traditional markets, which is why unambiguous guidance for all situations is not easy. The key is to stay alert and aware of your company’s data assets and your business model’s effects on competition.