A Knowledge Graph for Assessing Aggressive Tax Planning Strategies

August 12, 2020 Β· Declared Dead Β· πŸ› International Workshop on the Semantic Web

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Authors Niklas LΓΌdemann, Ageda Shiba, Nikolaos Thymianis, Nicolas Heist, Christopher Ludwig, Heiko Paulheim arXiv ID 2008.05239 Category cs.AI: Artificial Intelligence Cross-listed cs.DB Citations 9 Venue International Workshop on the Semantic Web Last Checked 4 months ago
Abstract
The taxation of multi-national companies is a complex field, since it is influenced by the legislation of several states. Laws in different states may have unforeseen interaction effects, which can be exploited by allowing multinational companies to minimize taxes, a concept known as tax planning. In this paper, we present a knowledge graph of multinational companies and their relationships, comprising almost 1.5M business entities. We show that commonly known tax planning strategies can be formulated as subgraph queries to that graph, which allows for identifying companies using certain strategies. Moreover, we demonstrate that we can identify anomalies in the graph which hint at potential tax planning strategies, and we show how to enhance those analyses by incorporating information from Wikidata using federated queries.
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