Regional Profiles and Methods of Fraud in Ukraine: An NLP Analysis of First-Instance Court Verdicts in 2024

Fraud affects both citizens’ sense of security and the state’s economic stability. The digitalization of financial services, the spread of remote communications, and the rise of “hybrid” deception schemes are reshaping the spatial and substantive patterns of crime. Against this background, a systematic review of first-instance court decisions makes it possible to assess the real “visible” share of accountability practices, trace regional disparities, and outline the features of fraud scenarios. Despite the substantial body of criminological and law enforcement publications in Ukraine, there is a lack of comprehensive, reproducible reviews of court practice based on large corpora of verdicts with clear spatial metrics. A particular practical gap lies in measuring the “centralization” of urban verdicts within a region and identifying concentration effects. The research methodology was based on the analysis of 2,771 first-instance court verdicts that referred to Article 190 of the Criminal Code of Ukraine and were issued in 2024. Modern natural language processing (NLP) methods were applied, enabling the extraction of fraud-related features from verdict texts-data traditionally collected and analyzed manually and fragmentarily. It was established that there are significant regional disparities in the number of verdicts under Article 190 of the Criminal Code of Ukraine: the highest concentration of cases occurred in Dnipropetrovsk, Kharkiv, and Odesa regions, as well as in the city of Kyiv. Both polycentric and monocentric models of law enforcement were identified, along with a high share of urban “magnets” (notably city of Kyiv, Kryvyi Rih, and Kharkiv). The analysis also revealed the dominance of card fraud schemes and the widespread occurrence of social engineering. This study contributes to the broader discourse on the digital transformation of criminological research and law enforcement by combining NLP, statistical analysis, and geospatial metrics. It expands the toolkit of criminal law science, provides a transparent framework for comparative research, and can be applied to other articles of the Criminal Code of Ukraine as well as to subsequent years.