Irene Tello Arista, Mihály Fazekas, Antonina Volkotrub (2024), Using beneficial ownership data for large-scale risk assessment in public procurement. The example of 6 European countries. GTI-WP/2024:02, Budapest: Government Transparency Institute
This paper fills a critical gap in the literature, providing practical insights into employing beneficial ownership data for large-scale corruption risk assessment in public procurement, with potential implications for public policy and practice. Existing literature lacks systematic evidence on using beneficial ownership (BO) data for large-scale corruption risk assessment. Hence, this paper aims to validate common indicators of corruption and money laundering in BO data in relation to public procurement. By doing so it also generates hypotheses on the impact of beneficial ownership registers on the organisation of financial crime. Analyzing administrative datasets of public procurement contracts matched with beneficial ownership registers for 6 countries (Denmark, Estonia, Latvia, Slovakia, Ukraine, and the UK) this paper utilizes ordinary least squares regressions to identify the relation between risk variables of BO with corruption risk indicators in public procurement. We find that BO-based risk indicators capturing unusual and outlier BO features – high company frequency of BO, frequent information change, outlier BO age, and no BO data – all perform in line with expected results. However, BO-based risk indicators relating to BO country such as offshore jurisdictions largely fail to relate to public procurement corruption risks in line with expectations, even though there are notable examples where we find the hypothesized relationships. Finally, BO data-based risk indicators which have already been widely validated in the literature using different data sources – company age and political connections – also turn out to be valid in our regressions. Our findings lend support to the growing use of BO data in research, policy, and investigations.
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