Algorithmic Global Wealth Chains

Recent work has explored how multinational enterprises take advantage of legal affordances for wealth protection, including the use of legal arbitrage, ambiguity, and absences. Given the complexity of legal systems across jurisdictions, digital technologies are being put to use to search for legal affordances and calculate optimal allocations of economic activity between jurisdictions. Our research asks how the use of these digital technologies changes the dynamics of Global Wealth Chains. We find that while creating integrated and structured datasets of both operations and policies presents a challenge, the data already present in tax departments is becoming valuable as a strategic tool to executive managers as they make the firm ‘legible’ to both executives and algorithms. This paper explores how these algorithms and big data are currently being employed and innovated, and how this changes the market for tax services, the role of tax within corporate strategy, and the career incentives and characteristics of tax professionals. This ranges from automating the manual handling of tax data to algorithms searching for optimal use of tax incentives, as well as machine learning to actively suggest tax planning strategies. In this paper we explore the use of digital tax technologies in the Big Four accounting firms. We explore how algorithms are able to identify legal affordances with implications for wealth distribution and industrial policy, and bring about new practices that permit new temporal ordering in tax planning, with tax technologies integrating financial, operational and legal data and operating in real-time.