The combination of big data with technologically advanced tools, such as pricing algorithms, is increasingly diffused in today everyone’s life, and it is changing the competitive landscape in which many companies operate and the way in which they make commercial and strategic decisions. While the size of this phenomenon is to a large extent unknown, there are a growing number of firms using computer algorithms to improve their pricing models, customise services and predict market trends. This phenomenon is undoubtedly associated to important efficiencies, which benefit firms as well as consumers in terms of new, better and more tailored products and services. However, a widespread use of algorithms has also raised concerns of possible anti-competitive behaviour as they can make it easier for firms to achieve and sustain collusion without any formal agreement or human interaction. In particular, this paper focuses on the question of whether algorithms can make tacit collusion easier not only in oligopolistic markets, but also in markets which do not manifest the structural features that are usually associated with the risk of collusion. This OECD note discusses some of the challenges of algorithms for both competition law enforcement and market regulation. In particular, the paper addresses the question of whether antitrust agencies should revise the traditional concepts of agreement and tacit collusion for antitrust purposes, and discusses how traditional antitrust tools might be used to tackle some forms of algorithmic collusion. Recognising the multiple risks of algorithms and machine learning for society, the paper also raises the question of whether there is need to regulate algorithms and the possible consequences that such a policy choice may have on competition and innovation.
Algorithms and Collusion – Background Note by the Secretariat