AI-Powered Insights on Global Corruption : A Multiview Analysis

Viharos, Zsolt János and Hoang, Anh Tuan and Kálmán, Botond Géza and Huff, Endre Béla and Zéman, Zoltán (2026) AI-Powered Insights on Global Corruption : A Multiview Analysis. REGIONAL STATISTICS, 16 (1). ISSN 2063-9538

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Abstract

Corruption is a major global problem. It undermines economic growth, government efficiency and public trust in institutions. Therefore, predicting the evolution of the corruption situation is a very important goal. However, choosing which indicators to use is difficult. The perception of corruption either measures a subjective corruption perception index or is based on objective, statistical numbers. However, these latter statistics do not show undetected cases of corruption, and therefore underestimate the frequency of the phenomenon. This study uses a machine learning method to select economic and socio-statistical indicators that can be used to estimate corruption. Based on the method, the trend of the relationship between the indicators included in the research and the perception of corruption, or the lack thereof, enriches the knowledge on the subject with a lot of information. The results also bring science closer to developing a reliable forecasting method.

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