Machine learning driven pricing could undermine competition, ACCC warns
- 16 November, 2017 13:43
The head of the Australian Competition and Consumer Commission today revealed the organisation has created a specialist unit tasked with analysing algorithms employed by online retailers and other businesses.
The competition watchdog has established a Data Analytics Unit that ACCC chairperson Rod Sims said would aid the efforts of its investigations teams and economists.
In remarks prepared for a speech today, Sims said that although data-driven innovation offers a range of economic advantage, algorithms that leverage “big data” could potentially “facilitate conduct which may contravene Australian competition law”.
The ACCC has identified a number of areas where competition issues may arise, with the most obvious one being the market power of online platforms, Sims said.
“Last year, following an ACCC investigation into the vertical restraints imposed by online travel agents, Expedia and Booking.com agreed to remove contractual requirements restricting Australian accommodation providers from offering better room rates or different inventories to other online agents and through offline channels,” the ACCC chair said.
He said the ACCC will also be scrutinising mergers and acquisitions “where both parties are involved in collecting and selling big data, or they are vertically linked in the big data supply chain”.
“Obviously, the competition issues raised will vary on a case-by-case basis and depending on the market involved,” Sims said.
“Like any valuable asset, the collection and possession of big data may be a decisive factor in certain transactions. For example, this may be the case where a merger is likely to have the effect of foreclosing access to unique data that is essential for competitors to compete or for new rivals to enter the market.
“As another example, it could be argued that the acquisitions of a maverick firm may be more harmful in a market where big data would otherwise facilitate coordination.”
Pricing algorithms can raise the risk of collusion, Sims said.
“It is argued that, in the right market conditions, pricing algorithms may be used to more effectively engage in and sustain collusion, whether ‘tacit’ or not, reducing competition but without contravening competition laws,” Sims said.
“It is said that a profit maximising algorithm will work out the oligopolistic pricing game and, being logical and less prone to flights of fancy, stick to it.”
“To further complicate matters, the development of deep-learning and artificial intelligence may mean that companies will not necessarily know how, or why, a machine came to a particular conclusion.”