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AI enriched journalism to investigate illicit financial flows

Alternative title: Kunstig intelligent journalistikk om skjulte finanstransaksjonar

Awarded: NOK 1.4 mill.

Panama Papers, Paradise Papers, Pandora Papers and other leaks have demonstrated the extent of the problem of illicit financial flows. The UN Sustainable Development Goals emphasize the need to understand better how illicit financial flows happen as well as the societal consequences of such flows. However, journalists investigating illicit flows across borders are often faced with the almost insurmountable task of finding the real owners behind companies being investigated. On the one hand, companies can make use of networks of subsidiaries registered in different jurisdiction, for example so-called tax havens or corporate havens. Additionally, the networks will often consist of numerous layers or leves. Finding the real or beneficial owners have proven to be a time consuming and costly part of many journalistic investigations. Nevertheless, investigations such as Panama Papers and Pandora Papers also demonstrate the potential of investigative journalism to unravel and communicate knowledge of importance to society. This project seeks to contribute to such efforts by developing Artificial Intelligence tools primarily designed to aid investigate journalists investigating illicit financial flows in general and beneficial ownership in particular. The project is interdisciplinary with participants coming from journalism, journalism studies, computer science and economics. In addition to developing tools designed to improve investigative methodologies, the project also contains activities to communicate the results.

Probably the most fundamental ethical issue related to the functioning of financial markets is the prevalence of illicit financial flows, or IFFs. IFFs are by nature hidden, and their disclosure depends to a large degree on whistleblowers and investigative journalism. Yet the tools that journalists and others use to investigate and disclose IFFs are not adequately suited to the complexity of the task. There is thus high demand for new methodologies and ways of working that can be employed by journalists, regulators, and other interested parties. The overall objective of this project is to contribute to improved public knowledge of illicit financial flows. The objective is reached by improving research methodologies of IFFs making use of Artificial Intelligence/ Machine Learning to investigate beneficial ownership. The project will test the research methodologies by investigating how 10 international/multinational companies (with subsidiaries) make use of corporate and tax havens and use the results to provide better understanding of the uses of tax havens as well as corporate havens. Also, the project aims at helping investigative journalists and media to get access to improved research methodologies thereby improving the capacity of the media to investigate illicit financial flows facilitating public debate on financial flows. The project is a cooperation between Nordic Centre for Sustainable and Trustworthy Artificial Intelligence Research (NordSTAR) at OsloMet and the Department of journalism and media studies at OsloMet.

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