Taxing Data-Driven Business: Towards Datapoint Pricing

Datafied business models avoid traditional taxation in many respects since data, being among the important value drivers of datafied business, are neither priced nor accounted for in a firm’s accounts. From a tax perspective, ignoring the value of data is inconsistent with the data economy paradigm, where it has been claimed that ‘data is the new oil’. The stringent legislative response to datafied business models has been to assign a financial value (a ‘price’) to each datapoint collected, referred hereinto as ‘datapoint pricing’. If the raw material (the data) is thus priced, its use and transfer can be traced by applying traditional accounting methods. For sure, datapoint pricing is no panacea; the inherently political question of who holds taxation rights in a cross-border context remains. Yet, datapoint pricing would make the locus of value creation transparent and facilitate the application of traditional tax assessment and transfer-pricing methods to data-driven business models. As well as bringing about taxable measures, datapoint pricing yields beneficial side-effects in the fields of antitrust law, financial regulation, data protection, anti-money laundering, and criminal enforcement.