A few months ago, we considered whether pricing algorithms might be the European Commission’s next antitrust target (here). The Commission had warned companies about the risks of using algorithms to collude, and indicated that pricing software formed part of its investigation into consumer electronics.

Since then, the Commission has published its Final Report on the E-commerce Sector Inquiry (“Final Report”, see our commentary here). This specifically identifies the wide-scale use of pricing software as something that may raise competition concerns, noting that the “availability of pricing information may trigger automatised price coordination” (13). The Final Report also claims that comments from retailers point to manufacturers making use of retail price maintenance. It suggests that pricing software may make it easier for manufacturers to retaliate against retailers that deviate from desired pricing, which may even limit the incentive for retailers to deviate from pricing recommendations in the first place. The Final Report also considers that pricing algorithms could facilitate or strengthen collusion between retailers – the algorithms make it easier for retailers to detect any deviations from prices implemented under a collusive agreement (33).

At the start of this month the Commission announced an investigation into whether the clothing manufacturer and retailer Guess illegally restricts retailers from selling cross-border within the EU. It seems likely that this investigation arose out of information the Commission received through the E-commerce Sector Inquiry. Bearing in mind the Commission’s comments on pricing algorithms in the Final Report, there is real potential for subsequent investigations into their use.

OECD Roundtable

Further insights into the Commission’s current thinking can be drawn from the OECD Roundtable currently taking place on ‘Algorithms and collusion’ (see here). The Commission’s contribution paper identifies the potential harmful effects that pricing algorithms may have in both vertical and horizontal contexts, namely by facilitating collusion and making collusion easier to enforce. It expands upon the concerns identified in the Final Report, offering by way of example a scenario where retailer A is adhering to retail price maintenance, and retailer B is monitoring and matching retailer A’s prices using pricing software (16). This is said to show how artificially high prices caused by retail price maintenance can easily spread to other ‘innocent’ retailers through the use of pricing software.

The paper notes that where firms are using algorithms to engage in explicit collusion, it is clear that the firms are still liable for their behaviour. It suggests that to a large extent, pricing algorithms can be analysed under traditional EU competition law. However, it also spends some time discussing the issue of tacit collusion, where there is no anti-competitive agreement involved and therefore the conduct of non-dominant companies acting independently falls outside the EU competition law framework. Does algorithmic pricing make tacit collusion more pervasive and more effective? If so, how should competition authorities respond?

As the paper recognises, this is an area of on-going debate. Nevertheless, it considers potential options such as whether the market itself may correct ‘algorithm-enabled tacit collusion’ through the development of ‘consumer algorithms’ that could track prices and even identify ‘maverick’ sellers not engaging in algorithmic pricing that consumers could purchase from. It also explores whether changes to the law on tacit collusion might be effective, or whether the interpretation of ‘communication’ should be expanded in order to bring algorithm-enabled price matching within the scope of Article 101 TFEU.

The UK CMA’s contribution to the Roundtable has less of a focus on pricing algorithms. It identifies a few potential theories of harm that may apply to the use of algorithms more broadly:

• Facilitating the implementation or maintenance of a collusive agreement.
• Facilitating behavioural discrimination (e.g. price discrimination where consumers are set individual prices based on algorithmic assessment of the highest price that consumer is likely to pay).
• Reinforcing dominance or raising barriers to entry (relating to the typical requirement for large volumes of data to make an algorithm effective).

The CMA recognises that algorithms can give rise to many consumer benefits. However, it also notes that they could lead to competitive or consumer harm in novel, untested ways, and that it is challenging to detect and understand the exact effect of complex algorithms, particularly given that they rapidly evolve (whether through constant refinement from developers or via ‘self-learning’).

Despite this, the CMA appears to be more comfortable than the Commission in its ability to combat this sort of issue. It notes that “the flexible, principles-based UK competition law framework has to date shown itself able to accommodate technological change, and to be capable of flexible and effective use to tackle a wide range of novel competition harms” (43). It plans to invest in in-house technological expertise and new digital forensic tools in response to the challenges posed by the use of algorithms.

Conclusion

These two OECD contribution papers were prepared for a Roundtable discussion – they do not reflect the Commission’s or the CMA’s official stance on pricing algorithms. However, they provide an interesting insight: these authorities are clearly paying a good deal of attention to the potential competition issues raised by algorithms. Coupled with the increasing enforcement activity by the Commission in the e-commerce sector, pricing algorithms continue to be one of the trending topics in competition law in Europe.