Transcrime e Crime&tech alla XXV Conferenza Annuale dell’ESC

In contemporary capitalist economies, worker exploitation remains a persistent risk, exacerbated by deregulated and flexible labour markets. In particular, labour exploitation is increasingly embedded in global supply chains, where complex networks of subcontracting and outsourcing can obscure accountability and facilitate exploitative practices. Our paper examines the role of lengthy supply chains and subcontracts in enabling workers’ exploitation. By drawing on a number of case studies across key sectors of the Italian economy – including logistics, food retail and luxury goods – the paper investigates the characteristics and risk factors of the companies involved, and highlights the new schemes which combine the typical modi operandi of labour exploitation with emerging forms of tax fraud, false invoicing and other financial crimes. This research draws on insights from the EU co-funded VANGUARD project (Grant Number 101121282). The initial findings of this study contribute to filling a critical knowledge gap by shedding light on the role of companies in exploitative schemes. Understanding these mechanisms is essential for developing effective policies and enforcement strategies to early detect high risk firms and prevent labour exploitation in vulnerable sectors.

Organised crime has been an evolving threat in Europe and worldwide, with criminal networks engaged in multiple and diverse criminal activities. The proposed roundtable brings together experts from four EU-funded projects to discuss their targeted approaches to countering specific forms of organised crime surrounding trafficking activities: Trafficking in Human Beings, Drugs Trafficking, Waste Trafficking, and Trafficking of Cultural Goods.

• The VANGUARD project aims to strengthen the fight against Trafficking in Human Beings (THB) through advanced AI-powered technological solutions, understanding, awareness raising, and training, thus providing an improved THB intelligence picture, enabling the disruption of the trafficking chain (online and offline) at an early stage, while also addressing the culture of impunity.
• The ARIEN project aims to create, through multi-disciplinary research and the development of technical solutions, an investigative and intelligence framework for fighting the entire illegal Drugs Trafficking chain in the EU, using AI techniques to strengthen investigative activities against relevant criminal groups.
• The PERIVALLON project tackles organised environmental crime, including Waste Trafficking, aiming to provide an improved and comprehensive intelligence picture, thus enhancing detection and prevention strategies against environmental crime networks, by leveraging the latest advancements in AI in the fields of computer vision and multimodal analytics.
• The RITHMS project aims to define a replicable strategy to counter the challenges in addressing the illicit Trafficking of Cultural Goods and investigate the mechanisms underpinning it, including its connection with organised crime, through mapping trafficking routes, analysing illicit networks, and developing counter-strategies.

The experts invited in the roundtable will present the findings of the research performed in each project and also delve into a well-rounded discussion, seeking to analyse the connection between diverse criminal activities, outline AI-based solutions, and highlight collaborative multi-agency efforts as key strategies for combatting organised crime and for enhancing security across Europe.

The research project will explore Chinese criminality and Chinese Organized Crime (COC) in Italy, concentrating precisely on what types of structures and activities could be individuated, and what circumstances determined their patterns of mobility and evolution, between 2000 and 2025. Current literature is poor, either outdated, or limited in geographical, substantial, or temporal scopes, or both. Consequently, dynamics related to Chinese criminality in Italy remains generally understudied, and especially the inner relationships established with the Italian society, at different levels (Becucci, 2018). To address this research gap, the study will resort to longitudinal and multidimensional methods to analyse episodes of Law Enforcement Agencies’ (LEAs) operations against Chinese criminal activities reported by media in Italy, in six criminal market domains, between 2000 and 2025. Then, the three most serious cases for each domain will be separately assessed through more in-deep analysis of judicial documents. The results aim at testing existing knowledge on Chinese criminality and COC in Italy, compared to new findings. The research wants to assess whether the recently observable increase of Italian public concern and allegations over COC’s insurgence and sophistication are based on factual, empirically robust premises, or mainly derive from reductive, stereotyped, and moral panic conceptions of Chinese communities, culture, traditions, and criminal dimensions. This research may lead to establish new theoretical and empirical understandings challenging public views that conceptualize the determining factors of Chinese criminality as ethnically confined to their diaspora. Findings want to support public policies aimed at countering Chinese criminality in Italy, by empirically assessing what forms and activities’ modus operandi could be established, what is its mobility over the country, and what relationships it establishes with the Italian society at large. The final aim is to help sensibilizing the public against stereotyped conceptions of the phenomenon.

Information pollution ranges from medical misadvise to darker and more insidious conspiracy theories and hate speech. While the existing literature agrees that information pollution poses a credible threat to societal well-being, the nexus of online content to offline actions is an open debate. Whilst some contend that information pollution creates overall societal distrust and degrades inter-group relations, generally, others believe that the specific narratives and biases within disinformation are transmitted to its consumers. Within the framework of Horizon Europe’s FERMI project, we utilize deep learning algorithms to predict offline crimes, with past crime occurrences and the frequency of online disinformation articles as our primary features. This research endeavor provides greater understanding of the potential online disinformation-offline crime nexus and how AI-driven technologies may help society in countering it.

Through a survey conducted with over 2100 consumers in Italy and Spain, this study examines consumers’ knowledge and attitudes towards online medicine sales, their exposure to online advertising, the prevalence of online medicine purchases, and their ability to distinguish legitimate products from illicit ones advertised online. Respondents were shown images of real advertisements offering medicines online, comprising both legitimate and illicit products. They were then tasked with assessing the legitimacy of these advertisements and identifying the factors that influenced their decision. Furthermore, an analysis of the influence of respondents’ personal characteristics on their attitude and awareness towards potential purchase of illicit products is included. This research provides critical insights into consumer behaviors and perceptions, with implications for policy development in regulating online pharmaceutical markets.

Over the past three decades, policies to combat organized crime have developed across two main areas: prevention and crime control. The former includes administrative, regulatory, and socio-economic measures, while the latter focuses on penal actions and the seizure/confiscation of criminal proceeds. This roundtable will focus on the latter, examining—through a comparative lens—whether and how crime control policies have effectively mitigated organized crime.

Two interrelated questions will be addressed:
– Have crime control policies produced a deterrent effect against organized crime?
– What about asset recovery policies? Have asset seizures and confiscations discouraged the expansion of criminal enterprises?

Regarding the first question, investigative journalism in Italy suggests that convicted mafiosi serving long or life sentences are being released and returning to their criminal activities. The European Court of Justice, followed by the Italian Constitutional Court, has played a crucial role in balancing security with prisoners’ human rights, ruling that life sentences—even for mafiosi—violate human dignity, regardless of cooperation with justice. As a result, many veteran mafiosi are returning home. Some have been re-arrested, others operate covertly, while some remain quiet and enjoy their retirement. In Italy, the interplay between criminal sanctions, penitentiary regulations, and early-release criteria appears ineffective. What about other countries?

Similarly, the international asset recovery system is failing. Recent data from the EU-funded project Recover indicate that cross-border asset recovery remains weak, inadvertently incentivizing organized crime to relocate abroad. How do these measures function in different legal systems? This roundtable will bring together experts from various countries to discuss both the tools (outputs) and the actual impact (outcomes) of crime control policies.

The paper examines the money flows related to different types of high-level corruption through a qualitative analysis of more than 60 case studies. The paper investigates the most frequent schemes and modi operandi employed to transfer bribes and corruption payments (i.e. money dirtying) and subsequently clean corruption proceeds (i.e. money laundering), and also the role of intermediaries in these schemes. Also, the study identifies the key satellite countries that serve as conduits for facilitating and concealing corruption-related financial flows. In particular, it explores their geographical distribution, the role in corruption schemes, and their demographic, social, economic and financial characteristics. The paper suggests the existence of a global market of corruption, where countries commonly identified as highly corrupt often serve as the source of corruption funds, while other developed countries – despite ranking well in Transparency International scores – play a key role as conduits in corruption related flows. The paper is based on the preliminary research carried out as part of the EU co-funded project FALCON, “Fighting Corruption & Organised Crime”.

Globalization has revolutionized the movement of goods and people, presenting both opportunities and challenges for border security. While facilitating trade and travel, this interconnectedness also amplifies the risk of illicit activities crossing borders undetected. Border Guards (BGs) and Law Enforcement Agencies (LEAs) play a pivotal role in screening passengers and goods to proactively identify potential threats. In this process, adopting a risk-based approach is essential to identifying high-risk passengers while minimizing human and economic costs for both authorities and economic actors. Although passenger data provides a rich source of information, effectively distinguishing passengers based on the risk they pose requires advanced intelligence-based profiling. Moreover, BGs and LEAs often lack the necessary technical skills and tools, and they may overlook the importance of coupling passengers’ data with information about transnational crime patterns related to various forms of serious crime.

The Horizon Europe TENACITy Project addresses this critical gap by pioneering advanced intelligence-based risk assessment models. These models leverage passenger data alongside comprehensive insights into criminal actors, transportation methods, and common routes associated with illicit activities. By integrating state-of-the-art machine learning techniques, this study develops predictive models capable of assessing the risk associated with individual passengers, identifying behavioral patterns indicative of potential criminal involvement. This facilitates the development of precise risk profiles, enabling the early detection of high-risk individuals and enhancing travel intelligence practices.

In recent years, there has been a rise in the global threat of cybercrime. In response, cybersecurity research has increased, focusing on a preventive approach, while criminological research on the subject remains quite limited. Specifically, most existing studies on the topic concentrate on specific types of cybercriminals, such as hackers, or treat cybercriminals as a single homogeneous category. However, there are few studies on who cybercriminals are, what motivations drive their crimes, and how these criminals are organized (Balogun, 2017; Bada, 2021). Furthermore, existing studies on cybercriminals have focused on cyber-dependent crimes (e.g., hacking, malware), neglecting cyber-enabled crimes, in which traditional offenses are amplified through digital tools. The aim of this study is to bridge the existing research gap in the literature by understanding and mapping the cybercrime ecosystem, starting from its key actors. To achieve this, it leverages and compares two competing theoretical approaches: the transformationalist approach, which views cybercrime as a novel phenomenon requiring specific theories (Wall, 2001; Yar, 2005; Choo, 2008), and the continuity approach, which considers cybercrime as an extension of traditional criminal behavior (Grabosky, 2001; McGuire, 2012). Thus, this study aims to shift the focus from crimes to criminals, enhancing the understanding of cybercrime ecosystems.

Firearms trafficking remains a significant security concert across Europe, with challenges in obtaining up-to-date intelligence due to varying data availability. Various studies have demonstrated the effectiveness of utilizing open-source data and text mining techniques in analysing criminal activities such as terrorism, human trafficking and human smuggling. Within the scope of the Horizon Europe CEASEFIRE Project, this study proposes a methodological framework to enhance intelligence on firearm trafficking by leveraging open-source data and large language models (LLMs). The framework focuses on analysing multilingual news sources across Europe to identify incidents involving firearms (seizures and selected firearm-related crimes). Through the extraction of relevant entities such as dates, locations, perpetrators, victims, and firearms used, this approach facilitates a timely and data-driven perspective of the phenomenon. Furthermore, the study integrates a risk assessment model, utilizing both incident data and official statistics, to evaluate risks and inform decision-making. This framework serves as powerful tool for law enforcement to proactively address firearms trafficking. The research highlights the potential of AI-driven methodologies in improving the intelligence landscape and in guiding responses to a growing transnational challenge.

The European Union’s Recovery and Resilience Facility (RRF), designed to support post-pandemic recovery, has also created opportunities for fraudulent actors, including organized crime (OC) networks. This research investigates whether increased EU spending has led to a rise in the foundation or infiltration of companies for fraudulent purposes, with a particular focus on organized crime’s strategic adaptation. Building on organizational crime theory (Needleman & Needleman, 1979) and rational choice theory (Paternoster & Simpson, 1993), the study examines how structural vulnerabilities in fund allocation enable fraud. It distinguishes between OC and non-OC actors, analyzing their methods, motivations, and effectiveness in exploiting these funds. The research employs a risk-scoring model based on logistic regression and Maximum Likelihood Estimation (MLE) to assess fraud risk in three company categories: newly founded firms, firms with ownership changes, and stable firms. The analysis incorporates financial anomalies, ownership opacity, and regional crime density to detect fraud patterns. Findings are expected to show that organized crime employs more sophisticated infiltration strategies, leveraging financial secrecy and professional networks, while non-organized actors engage in more opportunistic fraud. This study aims to inform anti-fraud policies, strengthening oversight mechanisms and enhancing risk detection in large-scale public funding programs.

Studying waste trafficking flows at a global level is essential due to the inherently transnational nature of waste crime, which exploits regulatory gaps, enforcement disparities, and economic inequalities between countries. A global perspective allows for a more comprehensive assessment of how illicit networks adapt to policy changes and enforcement efforts, ultimately informing more effective international cooperation and regulatory responses to combat this growing environmental and economic threat. This study examines the evolution of transnational waste trafficking over the past 15 years, analyzing global flows of illegal waste shipments. Using data on detected cross-border waste movements, the research aims to identify trends and transformations within the global waste trafficking network. The primary objective is to assess how enforcement levels have evolved over time and how major historical events, such as the China Ban in 2018, have influenced the illicit trade. Key questions guiding this analysis include: Which countries have been the main importers and exporters of illegally traded waste? Has enforcement improved in certain regions? How have waste flows shifted in response to critical disruptions like the China Ban? To explore these dynamics, the study employs an original longitudinal dataset to track the evolution of waste flows and enforcement efforts over time. The added value of this research lies in its unprecedented longitudinal approach to analyzing global waste trafficking, a perspective largely overlooked in existing studies. Additionally, it sheds light on cross-country differences in enforcement strategies and investigative practices over the years—another critical yet under-explored aspect of the literature.

Previous research on criminal network disruption has often overlooked how drug trafficking organizations (DTOs) adapt to law enforcement interventions. This study examines the impact of such interventions under realistic conditions where multiple members are arrested simultaneously, and DTOs respond with varying adaptive strategies. Using an empirically informed agent-based model, we simulate the drug trafficking activities of a large criminal organization, drawing on data from a law enforcement operation against an Italian DTO and existing literature. Our analysis evaluates how different law enforcement interventions influence the resilience and resistance of DTOs that adopt varying efficiency/security trade-off strategies. Our results reveal that efficient DTOs are highly resilient to isolated disruption attempts. However, in more realistic scenarios where law enforcement actions are sustained over time, their vulnerability increases. In contrast, secure DTOs are less able to recover from immediate disruptions but exhibit greater long-term resistance by minimizing exposure and avoiding continuous targeting. These findings underscore the critical role of the efficiency/security trade-off in determining DTO survival following law enforcement interventions. While efficient DTOs can withstand individual enforcement actions, their adaptability is limited under sustained pressure. Conversely, secure DTOs, despite their weaker immediate response, can persist over extended periods by evading detection. By highlighting the distinct vulnerabilities and advantages of different organizational strategies, this study provides valuable insights for policy makers seeking to design more effective interventions. Tailoring enforcement strategies to the specific organizational structure of DTOs can enhance law enforcement’s ability to disrupt criminal networks with lasting impact.

This research pioneers a methodological innovation in the study of transnational cocaine and heroin trafficking by integrating multiple data sources into a comprehensive network, for subsequent social network analysis. It employs datasets from the United Nations Office on Drugs and Crime (UNODC) individual drug seizure reports, the United States International Narcotics Control Strategy Reports, and purity adjusted price correlation networks, in order to map the narcotics trade across all UN Member States. Specifically, the study constructs three cross-sectional network maps for the periods 2007-2009, 2010-2012, and 2013-2015, analysing both cocaine and heroin flows. The methodology enables a detailed examination of network dynamics by correlating social network analysis metrics with various macro and micro-level factors identified in literature as influences on drug trafficking. These factors include education, legal trade, policing, and corruption among several others, providing a multi-dimensional analysis of how such variables interact with drug trafficking routes. Conducting this analysis across multiple time frames and a broad array of countries offers original insights into the global patterns and shifts in drug trafficking. The integration of diverse and traditionally segmented data sources facilitates a novel approach that enhances the granularity of the analysis and broadens the scope of understanding the dynamics of transnational drug trafficking flows. This study aims to contribute to the broader discourse by exploring the relationships between a range of influencing factors concurrently, rather than isolating a single region or theoretical framework.

Is the consumption of online conspiracy theories linked to real-world hate crimes? By analyzing online search trends for 36 racially and politically charged conspiracy theories in Michigan (2015–2019), we employ a one-dimensional convolutional neural network (1D-CNN) to predict hate crime occurrences offline. A subset of theories—including Rothschilds, Q-Anon, and The Great Replacement—improves prediction accuracy, with effects emerging two to three weeks after spikes in searches. However, most theories showed no clear connection to offline hate crimes. Aligning with neutralization and differential association theories, our findings empirically link specific racially charged conspiracy theories to real-world violence. This study underscores the potential of machine learning in identifying harmful online patterns and advancing social science research.

False invoicing – i.e. the issuance of invoices for services that do not exist, or whose value does not correspond to the actual value of what is exchanged – is one of the most neglected crimes by criminological research. However, it has become a key offence in most of nowadays organised and financial crime schemes, including mafia-type ones. False invoicing serves for multiple purposes – reduce tax burden, reduce corporate costs, create slash funds, launder money. By carrying out an empirical analysis of several dozens of cases of false invoicing detected in Italy, this paper provides a sociological and criminological interpretation of why this offence is employed, by whom it is exploited and who provides these criminal services. The analysis reveals the existence of dedicated providers, including foreign individuals and organizations, who are specialized in money laundering-as-a-service through false invoicing. Eventually, false invoicing has been radically changing not only the future perspectives of the money laundering market, but also the nature of predicate crimes themselves, including traditional mafia behaviors.

Criminal organizations rely on external actors—especially professionals—to infiltrate the legal economy. Yet many questions remain about how professionals become involved in organized crime. Their participation is often conceptualized as a “gray area” in Italian literature or a “middleground” in international scholarship, but the empirical data we have are sparse and inconsistent. This leaves important issues unresolved: What opportunities for contact emerge between professionals and mafia members in this sphere of collusion? How do professionals help mafia groups acquire human and social capital? And how does their role change based on the extent of mafia infiltration in a given region? To address these questions, this study systematically examines cases of the ’Ndrangheta’s economic infiltration across Italy using qualitative methods, including content analysis and ideal-type analysis. Preliminary results suggest a profit-driven, economically oriented logic in Northern Italy—where accountants often play a key role—and a more socially embedded approach focused on territorial control in Southern Italy. These differences give rise to markedly different functions and roles for professionals, influencing how they come into contact with mafia members, the nature of their exchanges, the activities they undertake, and the extent of their involvement in decision-making.

This special panel celebrates the 25th anniversary of the European Society of Criminology (ESC). Past Presidents will reflect on the development of criminology in Europe, the role of the ESC in shaping the field, and future challenges for research, policy, and practice.