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‘Screening for Cartels’ in Public Procurement: Cheating at Solitaire to Sell Fool’s Gold?

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)199–211
Number of pages13
JournalJournal of European Competition Law and Practice
Volume10
Issue number4
DOIs
DateAccepted/In press - 20 May 2019
DatePublished (current) - 12 Aug 2019

Abstract

Despite growing global interest in the use of algorithmic behavioural screens, big data and machine learning to detect bid rigging in procurement markets, the UK’s Competition and Markets Authority (CMA) was under no obligation to undertake a project in this area, much less to publish a bid-rigging algorithmic screening tool and make it generally available. Yet, in 2017 and under self-imposed pressure, the CMA released ‘Screening for Cartels’ (SfC) as ‘a tool to help procurers screen their tender data for signs of illegal bid-rigging activity’ and has since been trying to raise its profile internationally. There is thus a possibility that the SfC tool is not only used by UK public buyers, but also disseminated and replicated in other jurisdictions seeking to implement ‘tried and tested’ solutions to screen for cartels. This paper argues that such a legal transplant would be undesirable.
In order to substantiate this main claim, and after critically assessing the tool, the paper tracks the origins of the indicators included in the SfC tool to show that its functionality is rather limited as compared with alternative models that were put to the CMA. The paper engages with the SfC tool’s creation process to show how it is the result of poor policy-making based on the material dismissal of the recommendations of the consultants involved in its development, and that this has resulted in the mere illusion that big data and algorithmic screens are being used to detect bid rigging in the UK. The paper also shows that, as a result of the ‘distributed model’ used by the CMA, the algorithms underlying the SfC tool cannot improved through training, the publication of the SfC tool lowers the likelihood of some types of ‘easy to spot cases’ by signalling areas of ‘cartel sophistication’ that can bypass its tests and that, on the whole, the tool is simply not fit for purpose. This situation is detrimental to the public interest because reliance in a defective screening tool can create a false perception of competition for public contracts, and because it leads to immobilism that delays (or prevents) a much-needed engagement with the extant difficulties in developing a suitable algorithmic screen based on proper big data analytics. The paper concludes that competition or procurement authorities willing to adopt the SfC tool would be buying fool’s gold and that the CMA was wrong to cheat at solitaire to expedite the deployment of a faulty tool.

    Structured keywords

  • LAW Centre for Global Law and Innovation

    Research areas

  • competition, public procurement, screening, commercial secrets, bid rigging, commercial sensitivity, data governance, data ownership, big data, algorithms, artificial intelligence

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  • Full-text PDF (accepted author manuscript)

    Rights statement: This is the accepted author manuscript (AAM). The final published version (version of record) is available online via OUP at https://doi.org/10.1093/jeclap/lpz024 . Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 681 KB, PDF document

    Embargo ends: 12/08/21

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    Licence: Other

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