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Artificial intelligence and the fifth phase of political risk management: An application to regulatory expropriation
Author(s) -
Hemphill Thomas A.,
Kelley Keith J.
Publication year - 2021
Publication title -
thunderbird international business review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.553
H-Index - 37
eISSN - 1520-6874
pISSN - 1096-4762
DOI - 10.1002/tie.22222
Subject(s) - expropriation , political risk , risk management , politics , context (archaeology) , identification (biology) , relevance (law) , business , multinational corporation , economics , political science , law , finance , paleontology , botany , biology
Using the context of regulatory expropriation, this article extends political risk management theories, forecasting methodologies (employing artificial intelligence, machine learning, and data analytics), and human intelligence evaluation tools useful for multinational enterprise executives in their planning and decision‐making responsibilities. The article identifies three key areas where artificial intelligence will specifically assist managers in analyzing and mitigating risks: (a) earlier identification of risks, (b) precision in risk assessment, and (c) identification of unknown unknown risk correlations. These three categories also represent how artificial intelligence and its application to political risk assessment will evolve in the fifth phase of political risk management, and why it is of particular relevance to risks such as regulatory expropriation. Using the example of an oil exploration joint venture between Russian TNK and BP, and reflecting political and public policy indicators of regulatory expropriation, this political risk management framework and its hypothetical development are illustrated.