Search Results (61)

The rise in illicit financial activities across the South Africa–Zimbabwe corridor, with an estimated annual loss of $3.1 billion demands advanced AI solutions to augment traditional detection methods. This study introduces FALCON, a groundbreaking hybrid transformer–GNN model that integrates temporal transaction analysis (TimeGAN) and graph-based entity mapping (GraphSAGE) to detect illicit financial flows with unprecedented precision. By leveraging data from South Africa’s FIC, Zimbabwe’s RBZ, and SWIFT, FALCON achieved 98.7%, surpassing Random Forest (72.1%) and human auditors (64.5%), while reducing false positives to 1.2% (AUC-ROC: 0.992). Tested on 1.8 million transactions, including falsified CTRs, STRs, and Ethereum blockchain data, FALCON uncovered $450 million laundered by 23 shell companies with a cross-border detection precision of 94%, directly mitigating illicit financial flows in Southern Africa. For regulators, FALCON met FAFT standards, yielding 92% court admissibility, and its GDPR-compliant design (ε = 1.2 differential privacy) met stringent legal standards. Deployed on AWS Graviton3, FALCON processed 2 million transactions/second at $0.002 per 1000 transactions, demonstrating real-time scalability, making it cost-effective for financial institutions in emerging markets. As the first AI framework tailored for Southern Africa’s financial ecosystems, FALCON sets a new benchmark for ethical AML solutions in emerging economies with immediate applicability to CBDC supervision. The transparent validation of publicly available data underscores its potential to transform global financial crime detection. Full article

Human trafficking, a grave violation of human rights, frequently intersects with financial crimes, notably identity theft and coercive debt accumulation. This creates complex challenges for victims, survivors, and law enforcement. Victims of human trafficking are often coerced and/or threatened into committing various forms of crime, referred to as “forced criminality.” In recent years, this trend of criminality has moved from violent crimes to financial crimes and fraud, including identity theft, synthetic identity fraud, and serving as money mules. This phenomenon, termed “forced fraud”, exacerbates the already severe trauma experienced by victims (referred to as both victims and survivors throughout, consistent with trauma-informed terminology) trapping them in a cycle of financial instability and legal complications. Traffickers often coerce their victims into opening credit lines, taking out loans, or committing fraud all in their own names, leading to ruined credit histories and insurmountable debt. These financial burdens make it extremely difficult for survivors to rebuild their lives post-trafficking. This paper explores the mechanisms of forced fraud, its impact on survivors, and the necessary legislative and financial interventions to support survivors. By examining first-hand accounts and social and policy efforts from a range of sources, this paper highlights the urgent need for comprehensive support systems that address both the immediate and long-term financial repercussions of human trafficking. Full article

Street crime is a critical public concern, attracting wide social and research attention. Conventional solutions to reduce street crimes are dispatching more police force in patrol and installing more cameras for street surveillance, which, however, suffer from huge manpower and financial consumption and limited performance. Inspired by the wide application of Unmanned Aerial Vehicles (UAVs) in policing and other related missions such as street surveillance, we investigate the use of UAVs in patrolling along high-risk streets to deter street crimes. UAVs significantly outperform police officers and street cameras in terms of cost reduction and deterring performance improvement. Technically, this paper proposes a data-driven framework to schedule the patrol UAVs, including an online patrol path planning module and an offline UAV station siting module. In the first module, the street-level deterring effect of the UAVs is estimated using a prediction-enhanced method, which guides the UAVs to patrol the high-risk streets more efficiently. Evolved from the path planning algorithm, the second module utilizes a data-driven method to estimate the deterring effect of the candidate UAV stations with different numbers of UAVs. Then both the location of the UAV stations and the UAVs at each station are determined. The proposed framework is comprehensively evaluated using a 6-year crime dataset of the Denver city. The results show that the proposed framework improves the deterring effect by 58.49% on average, and up to 157.32% in extreme cases compared to baselines. Full article

The growth of the older adult population, their wealth accumulation, and vulnerabilities from aging have contributed to increasing rates of abuse, fraud, and financial exploitation. However, the current responses and services are fragmented and ineffectual. This paper develops a novel strategy for addressing the variation in response and victim service provision through the development of a problem-solving court that is informed by the principles of restorative justice. Given the unique challenges, cases, and population, a problem-solving court for crimes against older adults will provide tailored interventions, responses, and sanctions while ensuring that older adult victims and their communities are at the center of the criminal justice process and that their needs are prioritized. Research on problem-solving courts; restorative justice; and older adult abuse, fraud, and financial exploitation are integrated with data from a case study of older adult financial exploitation in a large retirement community to develop the model problem-solving court. Consistent with best practices in victim services, the model court will provide comprehensive services in a one-stop location, while simultaneously increasing accountability for offenders who prey on this vulnerable population. The paper concludes with a plan to guide the implementation and evaluation of the proposed model problem-solving court for older adult abuse, fraud, and exploitation. Full article

This study assesses public trust in Bahrain regarding the potential of artificial intelligence (AI) to mitigate the use of cryptocurrencies in financial fraud and terrorist financing. The increasing risks associated with illicit financial activities have been exacerbated by the rapid expansion of e-commerce linked to cryptocurrencies, leading to vulnerabilities in financial technology systems. AI presents a viable solution for detecting, analyzing, and assessing the risks associated with cryptocurrency transactions, strengthening confidence in financial institutions’ regulatory measures. Evaluating public trust is crucial to understanding societal awareness of AI’s role in monitoring and regulating virtual financial transactions to prevent fraud. This research employs a quantitative approach to examine the key factors that enhance confidence in AI-driven auditing and oversight of cryptocurrency transfers. The findings indicate that, while AI offers significant advantages in combating financial crime, certain challenges remain. These include technological complexities, difficulties in accurately identifying users, and weaknesses in electronic financial and legal regulatory frameworks. Such challenges may undermine public trust in AI’s effectiveness in financial oversight. Addressing these concerns is essential to ensuring the successful integration of AI in financial regulation and reinforcing its role in enhancing security and transparency in cryptocurrency transactions. Full article

Human trafficking for forced labour or sexual exploitation often takes the form of forced migration. It is the third-largest crime industry in the world and has severe consequences on the women survivors. Trafficking violates the safety, welfare, and human rights of the victims and forces physical and psychological imprisonment on them. Despite the significant number of women being trafficked, little is known about the best ways to address their needs. This article highlights the understanding developed by social service providers in South Africa regarding the consequences of human trafficking on women survivors. Being aware of the complex challenges faced by women survivors of human trafficking enables social service providers to respond to their needs effectively through appropriate interventions and services. Data for this qualitative study were collected through one-on-one interviews and analysed using thematic analysis. Social service providers understand the following to be related to women survivors of trafficking: involvement in drugs and sex work, dependency on the perpetrator, lack of self-esteem, self-blame and shame, being disoriented, psychological challenges, lack of financial support, health issues, isolation, and loneliness. To be relevant and effective, services should be packaged in a manner that addresses all the challenges faced by women survivors of human trafficking. Full article

In recent years, there has been a sharp increase in the number of online fraud cases. However, research on crime geography has paid little attention to online crimes, especially to the influencing factors behind their spatial distributions. Online fraud is closely related to people’s daily internet use. The existing literature has explored the impact of internet use on online crimes based on small samples of individual interviews. There is a lack of large-scale studies from a community perspective. This study applies the routine activity theory to online activities to test the relationship between online fraud alert data and the usage durations of different types of mobile phone users’ applications (apps) for communities in ZG City. It builds negative binomial regression models for analyzing the impact of the usage of different types of apps on the spatial distribution of online fraud. The results reveal that the online fraud crime rate and the online time spent on a financial management app share the most similar spatial distribution. While financial management, online education, transportation, and search engine app usages have a significant positive association with online fraud, the use of a financial management app has the greatest impact. Additionally, time spent on social media, online shopping and entertainment, and mobile reading apps have a significant negative association with online fraud. As not all online activities lead to cybercrime, crime prevention efforts should target specific types of apps, such as financial management, online education, transportation, and search engines. Full article

Business Process Redesign (BPR) is a fundamental approach to enhancing efficiency, compliance, and digital transformation in public sector operations. Despite extensive theoretical advancements, its application in real-world settings remains limited. This study addresses this gap by applying the BPR Assessment Framework to business processes within the Greek Public Financial Management (PFM) domain, specifically analyzing workflows from the Greek Customs Service and the Financial and Economic Crime Unit (S.D.O.E.). This research employs a structured methodology that integrates internal process metrics with clustering techniques to systematically classify processes based on their redesign potential. The findings reveal that a significant proportion of public sector workflows demonstrate high redesign capacity, highlighting opportunities for efficiency gains and improved regulatory compliance. Furthermore, this study identifies key challenges, such as organizational resistance and technological constraints, that impact BPR implementation. By demonstrating the framework’s applicability in a complex, operational environment, this study provides actionable insights for policymakers and practitioners. Specifically, the results show how structured process evaluation enables targeted redesign initiatives that streamline administrative workflows, enhance compliance with financial regulations, and support digital transformation in public administration. These insights contribute to advancing BPR practices by bridging the gap between theoretical development and real-world application, offering a replicable methodology for improving public sector efficiency. Full article

Background: Small-town residents face healthcare inequities that result in poorer outcomes compared to those living in urban areas. These disparities are deeply rooted in socioeconomic and demographic factors as well as in access to healthcare services. This study aimed to explore health disparities and community strengths within small towns in Williamson County, Central Texas, intensified by urban spillover. Methods: A qualitative study was designed using the Social Determinants of Health Model as the conceptual framework. We conducted eight in-depth interviews with local stakeholders. Each interview lasted 60–90 min and was audio-recorded, transcribed verbatim, and subjected to thematic analysis by trained researchers. Results: The participants reported that significant population growth, via individuals drawn from the rapidly expanding cities in proximity to their small towns, dramatically impacts lives. Eight main themes emerged: (1) low levels of community and professional health literacy and a lack of healthcare navigation support in schools and community-based support systems; (2) limited funding for healthcare services and limited capacity to support access to them; (3) limited access to food that can support healthy dietary patterns; (4) inadequate transportation services; (5) substance use, violence, and crime; (6) stressful community dynamics and an environment that negatively influences individual and community well-being; (7) financial instability and unreliable and insufficient infrastructure; and (8) community strengths and potential resources. Conclusions: Our findings reveal critical healthcare disparities in these small towns. Harnessing funding support and community unity is vital for developing equitable healthcare solutions and improving the well-being of residents in these rapidly evolving locales. Full article

With rapid urbanization, the spatial layout and functional characteristics of urban facilities have a strong correlation with the spatial distribution of criminal activities. Using Changsha City as a case study, this research analyzes 2023 urban crime data, Point of Interest (POI) data, and socioeconomic data. The Multi-scale Geographically Weighted Regression (MGWR) model and clustering analysis are applied to examine how different types of urban facilities influence the spatial heterogeneity of crimes and propose tailored urban planning recommendations and crime prevention strategies. The findings reveal the following: (1) The spatial distribution of crimes in Changsha’s central urban area demonstrates significant spatial heterogeneity. Property crimes dominate in frequency and spatial distribution, primarily clustering around commercial hubs and transport nodes, while violent crimes are more common in scenic areas and open spaces with high pedestrian flow. (2) The impact of built facilities on crime exhibits spatial variability. Facilities such as Financial Services Facilities (FSF) and Shopping facilities (SHF) significantly contribute to property crime in core urban areas, while Scientific, educational, and cultural facilities (SEC) suppress crime in university towns. Scenic spots and facilities (SPF) are associated with violent crimes near scenic site entrances and transport hubs. (3) Facility resource allocation and preventive strategies should be optimized based on dominant factors in different areas to enhance security management efficiency through precise and differentiated planning, fostering sustainable urban safety systems. This study provides insights into the spatial patterns of crime distribution and its dominant factors from the perspective of urban facilities, offering a scientific basis for improving urban crime management and facility planning. Full article

Practical challenges and special threats from scam-related fraud exist for regional and local communities in Southeast Asia during and after the COVID-19 pandemic. The rise in pig-butchering operations in Southeast Asia is a major concern due to the increased use of digital technology and online financial transactions. Many of these operations are linked to organized crime syndicates operating across borders, posing challenges for law enforcement. As a first study in Vietnam, we combined the primary and secondary databases to unveil the nature of transnational scam-related fraud. Findings show that scammers are using advanced methods such as phishing, fraudulent investments, and identity theft to maximize their sophisticated tactics for achieving financial possession. There are organized crime rings operating in Vietnam and Cambodia, with Chinese groups playing a leading role behind the scenes. Social media and its various applications have become common platforms for these criminal activities. This study also calls for practical recommendations to consider specific challenges in combating these crimes, including building a strong framework with clear policies, encouraging multiple educational awareness campaigns in communities, enhancing effective cooperation among law enforcement and others, and supporting evidence-based approaches in research and application. While we recognized and assumed that pig-butchering operations with scam-related fraud are a complex problem that requires a well-rounded and coordinated response, the exact approach would depend on each country’s specific circumstances. Full article

This study examines some of the documentation tools and techniques that forensic accountants, internal auditors, external auditors, and others can use to document accounting and financial reporting systems under investigation. While prior research has addressed these items piecemeal, this study is the first to incorporate them, along with current related research and theoretical foundation, and relate them in aggregate to the work of forensic accountants, internal auditors, external auditors, and others. Inputs, processes, and outputs of modern accounting and financial reporting systems are often difficult to fully grasp, with weaknesses obscured by the complexities of the system. These weaknesses make a system vulnerable to fraudsters, embezzlers, hackers, and others who will take advantage of system weaknesses to perpetrate financial fraud, embezzlement, or other financial crimes. Documentation tools and techniques examined in this study will be useful to forensic accountants, internal auditors, external auditors, and others for identifying the components, processes, and potential weaknesses of accounting and financial reporting systems. Full article

This study examines factors influencing Ghanaian banks’ compliance with anti-money laundering (AML) legislation. Drawing upon institutional, compliance, and dynamic capability theories, the study identifies the interplay of organisational, regulatory, and employee factors influencing compliance outcomes. A mixed methods approach was used to collect data from 23 universal banks, 9 local and 14 foreign, in Ghana, focusing on experienced managers and employees in risk, legal, operations, compliance, and business development departments. The findings show that employee characteristics like due diligence and moral involvement have a positive relationship with compliance with AML regulations; however, contrary to expectations, effective AML/CFT programs did not significantly impact banks’ adherence to these regulations. The association between moral engagement, an innovative culture, and AML compliance is weakened by normative power and an innovative culture acting as negative moderators. This study contributes empirical evidence to the literature on AML compliance in emerging markets and offers practical implications for policymakers, regulators, and banking professionals seeking to boost regulatory effectiveness and mitigate financial crime risks. This study provides a foundation for targeted interventions and strategic initiatives aimed at strengthening the AML regulatory landscape in Ghana and other countries. Full article

The criminalization of abuse, neglect, and financial exploitation of older adults did not begin until the late 1990s in the United States. During this time, a number of states enacted laws criminalizing certain abusive and exploitive behaviors committed against older adults and added punishment enhancements to existing laws if victims were over a certain age. These laws and policies, and the impetus for them, mirrored those enacted decades prior as part of the child welfare movement, with connections drawn between the vulnerability of younger and older victims. Despite passage of these various abuse and exploitation laws for older adults, significant challenges remain in the identification, investigation, and prosecution of crimes committed against this population. Further, the population of older adults has been rapidly expanding along with rates of victimization, elevating the importance of this escalating social problem. This paper identifies limitations in the prior research by describing the past, present, and likely future of U.S. law and policy intended to effectively respond to crimes against older adults and concludes with a research and policy agenda. Full article

This study examines the applications, benefits, challenges, and ethical considerations of artificial intelligence (AI) in the banking and finance sectors. It reviews current AI regulation and governance frameworks to provide insights for stakeholders navigating AI integration. A descriptive analysis based on a literature review of recent research is conducted, exploring AI applications, benefits, challenges, regulations, and relevant theories. This study identifies key trends and suggests future research directions. The major findings include an overview of AI applications, benefits, challenges, and ethical issues in the banking and finance industries. Recommendations are provided to address these challenges and ethical issues, along with examples of existing regulations and strategies for implementing AI governance frameworks within organizations. This paper highlights innovation, regulation, and ethical issues in relation to AI within the banking and finance sectors. Analyzes the previous literature, and suggests strategies for AI governance framework implementation and future research directions. Innovation in the applications of AI integrates with fintech, such as preventing financial crimes, credit risk assessment, customer service, and investment management. These applications improve decision making and enhance the customer experience, particularly in banks. Existing AI regulations and guidelines include those from Hong Kong SAR, the United States, China, the United Kingdom, the European Union, and Singapore. Challenges include data privacy and security, bias and fairness, accountability and transparency, and the skill gap. Therefore, implementing an AI governance framework requires rules and guidelines to address these issues. This paper makes recommendations for policymakers and suggests practical implications in reference to the ASEAN guidelines for AI development at the national and regional levels. Future research directions, a combination of extended UTAUT, change theory, and institutional theory, as well as the critical success factor, can fill the theoretical gap through mixed-method research. In terms of the population gap can be addressed by research undertaken in a nation where fintech services are projected to be less accepted, such as a developing or Islamic country. In summary, this study presents a novel approach using descriptive analysis, offering four main contributions that make this research novel: (1) the applications of AI in the banking and finance industries, (2) the benefits and challenges of AI adoption in these industries, (3) the current AI regulations and governance, and (4) the types of theories relevant for further research. The research findings are expected to contribute to policy and offer practical implications for fintech development in a country. Full article