The CMA’s Paper on Pricing Algorithms, Collusion and Personalised Pricing | The National Law Review

On 8 October 2018, the UK Competition and Markets Authority (“CMA”) published a Working Paper on the ‘use of pricing algorithms to facilitate collusion and personalized pricing’ (the “Paper”). It follows a number of other initiatives from competition authorities regarding algorithms, including the recent German Monopolies Commission’s proposals regarding pricing algorithms, which was the subject of a Covington Competition Blog post. The CMA’s analysis reflects input from algorithm providers, other competition authorities, and the results of the CMA’s findings from pilot tests. The Paper is economic rather than legal in focus, and assesses the extent to which various algorithm models have the potential to affect competition.

Competition Benefits and Concerns Related to Algorithms
The Paper notes the potential efficiencies generated by pricing algorithms, including reducing transaction costs and improving decision-making of consumers by giving them access to a wealth of information. However, the Paper goes on to discuss the potential for algorithms to harm consumers through explicit or tacit coordination.

Explicit Coordination Concerns
The CMA considers the potential use of algorithms to facilitate explicit agreements. According to the Paper, pricing algorithms could facilitate cartelists increasing the stability of their collusive practice. The CMA explains that, because of the volume of available data and speed of processing, an algorithm would make it easier, quicker and less costly to detect and respond to deviations. High quality data would also reduce the chance of errors. Finally, algorithms can also reduce the incentive of cartelists’ employees to undermine the existing cartel.

Tacit Coordination Concerns
The Paper also considers three possible means by which a pricing algorithm could facilitate tacit coordination. First, it explores tacit collusion in a Hub-and-Spokesetting where several firms employ the same algorithm to determine their pricing behaviour. Second, it discusses the Predictable Agent, where firms unilaterally develop algorithms that are set up to monitor coordination, follow price leadership and punish deviations in order to reach a collusive outcome. Third, it addresses a more complex type of algorithm, namely the Autonomous Machine, which is typically programmed to maximise profit without human intervention, such that it could decide that collusion is the most optimal strategy.