Guidance on Transfer Pricing In a recent survey, conducted among corporate transfer pricing managers, tax consultants and auditors of German tax authorities, Greil, Müller and Olbert (2019), find that transfer pricing in digital business models is a pressing issue for corporations. They find that traditional transfer pricing methods (i.e. the cost-plus method) are still prevalently used despite the profit split method is recommended as the most appropriate method for digital transactions.15 Based on their survey, the authors conclude that the resolution of uncertainties with regard to transfer pricing guidelines should be a major concern for policymakers.16 In light of the above discussed ‘Data Mining’ process, the first task of allocating profits to legal entities within an integrated company is to identify the activities performed by individual entities along the value chain of the knowledge development process. The next challenge is to determine the value of the specific activities in relation to the overall value creation by ‘Data Mining’ to set transfer prices in accordance with the arm’s length principle. The nature of intra-firm transactions makes it – for traditional and inevitably also for digital business models – extremely difficult and almost impossible to find comparable transactions between unrelated market participants.17 Furthermore, the individual characteristics of digital businesses’ key value drivers, intellectual property and know-how add complexity to the determination of activities’ value. Nevertheless, a conceptual analysis of the functions and risks involved in the ‘Data Mining’ process or other digital business models, with a focus on the specific people functions, can provide benchmarks to set transfer prices in accordance with comparable market prices. Across many industries, companies have evolved that focus on separate steps of the ‘Data Mining’ process, such as the 15
This argument has also been brought up by Hongler and Pistone (2015).
16
Greil et al. (2019), p. 30.
17
20
Keuschnigg and Devereux (2013), p. 432; Olbert and Spengel (2019), p. 21.
collection of raw data, the preparation of data or the provision of information, and sell their services on the market.18 Besides, traditional research and development processes, which have to some extent similar characteristics as data mining activities, could serve as a blueprint for the application of transfer pricing guidelines. If the standard transfer pricing methods are not suitable to allocate profits within an integrated company, the profit split method should be considered to find consistent transfer pricing solutions. The OECD’s recommendations on the residual profit split method can provide guidance for highly integrated business models.19
The OECD Reform Proposals Profit Split Method – The “Unified Approach” (Pillar One) Guidance on the application of the transactional profit split method has already been updated in June 2018 as part of the BEPS-Project: Action 10. These transfer pricing regulations are recommended to highly integrated business models whose transactions involve unique and valuable intangibles and the involved parties share the assumption of economically significant risks.20 Digital corporations, in general, meet these characteristics. The OECD develops a new “Unified Approach” in its most recent public consultation document. In general, the proposed “Unified Approach” introduces a new profit allocation rule that should complement the arm’s length principle. The proposal suggests to calculate a deemed residual profit at consolidated group level using simplified methods and to allocate a fraction of this profit – based on sales – to market jurisdictions. Routine tasks should be remunerated with arm’s length principle based transfer prices.21 18
In addition to raw data providers, such as Thomson Reuters or Bureau van Dijk, many firms provide services along the value chain of data mining such as the German Kendaxa Group that specializes in data intelligence.
19
OECD (2019a), p. 13.
20
OECD (2018b), p. 14 ff.
21
OECD (2019d), p. 6.
