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Aida Nahar
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Journal of Business Crime
Published by Generate Digital Publishing
ISSN : -     EISSN : 30904412     DOI : 10.70764/gdpu-jbc
Core Subject : Economy, Science, Social,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Social Sciences
JBC: Journal of Business Crime provides a venue for high-quality manuscripts dealing with economics, accounting, and compliance in its broadest sense. The editorial board encourages manuscripts that are international in scope, articles that are perceptive, evidence-based, and have a policy impact. however, readers can also find papers investigating domestic issues with global relevance. JBC is published by the Publishing Company "Generate Digital Publishing". JBC is an open access journal which means that all contents is freely available without charge to the user or his/her institution. The scope of this journal includes empirical and theoretical articles related to economics, accounting, criminology, criminal justice, control, prevention of financial crime and related abuse.
Arjuna Subject : Umum - Umum
Articles 16 Documents
 1   2 
A Comprehensive Framework to Identify and Prevent Money Laundering in Decentralized Finance Using Big Data Analytics Eva Harmelia Valentina; Kinza Aish
Journal of Business Crime Vol. 1 No. 2 (2025)
Publisher : Generate Digital Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70764/gdpu-jbc.2025.1(2)-11

Abstract

Objective: This research aims to develop a comprehensive framework to identify and prevent money laundering in Decentralized Finance (DeFi) by leveraging big data analytics, integrating advanced machine learning algorithms, and network analysis techniques to address the challenges of pseudonymity and decentralization inherent to this ecosystem.Research Design & Methods: This research utilizes a mixed method approach with machine learning analysis based on Elliptic Dataset and qualitative policy study, applying graph models and classification algorithms to detect illegal transactions with precision in the context of imbalanced data. Findings: The results show that the MLP and GCN models achieve high accuracy (98% and 97.3%) and excellent recall (99.5% and 99.4%) on the Elliptic Dataset, significantly outperforming traditional methods. Exploratory data analysis and graph visualization confirmed that illegal transactions form denser clusters and more complex paths, indicating a layering pattern. Implications and Recommendations: Theoretically, this research extends the application of big data and graph theory to new financial systems, providing a blueprint for future RegTech and FinTech research. Practically, the framework offers tangible tools for regulators, law enforcement, and DeFi platforms to enhance AML capabilities, supporting the development of real-time monitoring tools and risk assessment models. Contribution and Value Added: The main contribution of this research is the development of a robust and adaptive big data analytics-based AML framework, which effectively addresses the unique challenges of DeFi.
Artificial Intelligence and Money Laundering in The Application of International Criminal Law Miguel Abel
Journal of Business Crime Vol. 2 No. 1 (2026)
Publisher : Generate Digital Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70764/gdpu-jbc.2026.2(1)-01

Abstract

Objective: This study examines the legal and theoretical issues related to using Artificial Intelligence (AI) for preventing and enforcing money laundering under international and European law. It highlights the conflict between technological advancements and the safeguarding of fundamental rights, especially regarding the EU's 2024 anti-money laundering regulatory package and the AI Act. This work was financially supported by the PID2024-160160OB-I00 project of the Spanish State Research Agency (Ministry of Science, Innovation and Universities), Operational Program FEDER "A way of making Europe"Research Design & Methods: This research examines how different EU regulations and directives on Artificial Intelligence align with each other. It analyzes key concepts such as the Europeanization of criminal law, the principles of legality and proportionality, and the balance between security and liberty. The study uses secondary data from EU legal documents and academic literature.Findings: This research shows that AI can help detect and combat money laundering, but it also poses risks such as opaque algorithms, bias, and privacy violations. The EU 2024 regulatory framework seeks to make the use of AI more humane and trustworthy, but differences in criminal law across countries and the lack of a unified European Criminal Code make enforcement difficult. Concerns remain about the proportionality and legality of sanctions among Member States.Implications: The study highlights the need for continuous legal changes, close human supervision, and a distinct separation of administrative and criminal law for using AI in anti-money laundering systems. It also emphasizes strengthening the alignment of criminal law across Europe for better legal clarity and fairness.Contribution & Value Added: This paper looks at how international and European criminal law is developing in the digital world. It links AI governance with anti-money laundering policies. The paper critically assesses the EU 2024 regulatory framework and offers suggestions for balancing technological innovation with the protection of fundamental rights in the criminal legal system.
Corporate Compliance as an Alternative to The Criminal Justice System in Resolving Business Crimes Omer Faruk Tekdogan
Journal of Business Crime Vol. 2 No. 1 (2026)
Publisher : Generate Digital Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70764/gdpu-jbc.2026.2(1)-02

Abstract

Objective: This study critically examines whether corporate compliance has evolved from a preventive governance instrument into a de facto substitute for criminal justice in the enforcement of business and economic crimes, particularly through non-judicial settlement mechanisms. Research Design & Methods: Using a doctrinal-comparative qualitative design within a socio-legal framework, this study analyzes international journal literature on corporate compliance, Deferred Prosecution Agreements (DPAs), Non-Prosecution Agreements (NPAs), administrative settlements, and individual accountability regimes in various jurisdictions. Findings: Findings show that corporate compliance increasingly operates as a negotiation-based law enforcement tool that partially replaces formal criminal proceedings. Compliance mechanisms systematically shift law enforcement from public courts to administrative settlements and negotiations, weakening deterrence, judicial transparency, and individual accountability, especially for senior corporate actors. This transformation contributes to selective law enforcement and the emergence of a shadow justice system that favors economically powerful corporations. Implications: Replacing criminal proceedings with negotiated compliance undermines the principle of equality before the law and reduces business crime to operational risk. This study recommends a hybrid enforcement model. In this model, compliance serves as a complement to, rather than a substitute for, criminal prosecution. Contribution & Value Added: This study develops the Compliance Justice Substitution Theory, linking compliance governance with criminal justice outcomes, and provides policy recommendations to prevent the use of compliance as a tool for corporate impunity.
Macroeconomic Dynamics and Institutional Integrity: An Econometric Analysis of The Determinants of Poverty in Indonesia 2005-2024 Agustina Eka Harjanti
Journal of Business Crime Vol. 2 No. 1 (2026)
Publisher : Generate Digital Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70764/gdpu-jbc.2026.2(1)-03

Abstract

Objective: This study aims to to analyze the effect of corruption on poverty levels by considering key macroeconomic factors as variables that provide theoretical contributions in the form of strengthening empirical evidence on poverty, as well as practical contributions in the form of more integrated policy recommendations to support inclusive, effective, and sustainable poverty reduction strategies.Research Design & Methods: The study used a quantitative approach with multiple linear regression methods on Indonesian time series data for the period 2005–2024. Classical assumption tests, including normality, heteroscedasticity, autocorrelation, and multicollinearity, were conducted to ensure the feasibility of the estimation model.Findings: The analysis shows that economic growth has a positive but insignificant effect on poverty, inflation has no significant effect, unemployment has a positive and significant effect, and CPI has a negative and significant effect on poverty. These findings confirm that structural factors such as unemployment and governance quality play a stronger role than other macro variables in explaining poverty dynamics in Indonesia.Implications: The results of the study indicate the importance of development policies that emphasize inclusive job creation, price stability accompanied by social protection, and strengthening the eradication of corruption in order to increase the effectiveness of poverty alleviation programs.Contribution & Value Added: This study provides latest empirical contributions regarding the simultaneous relationship between macroeconomic variables and corruption on poverty in the context of Indonesia over a long period, and confirms that improving governance and reducing unemployment are key strategies in reducing poverty in a sustainable manner.
Dynamics of International Regulatory and Investigation Cooperation in Handling Crypto-Related Economic Crimes Nadhifah, Isyfa Fuhrotun; Destiny Eze, Agwanwo
Journal of Business Crime Vol. 2 No. 1 (2026)
Publisher : Generate Digital Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70764/gdpu-jbc.2026.2(1)-04

Abstract

Objective: This study aims to evaluate the effectiveness of regulatory models across selected jurisdictions such as the United States, Brazil, China, Thailand, Indonesia, and the European Union and to analyze emerging trends in crypto-related economic crime, particularly in relation to implementation gaps in FATF Recommendation 15, namely the Travel Rule, and the resulting cross-jurisdictional regulatory arbitrage dynamics.Research Design & Methods: This study uses a comparative qualitative approach through document analysis and cross-country case studies. Secondary data comes from FATF, Interpol, UNODC, Chainalysis reports, national regulations, and academic literature, which are analyzed using thematic content analysis and comparative regulatory analysis. Findings: Research findings indicate that regulatory fragmentation and gaps in the implementation of FATF standards create regulatory arbitrage loopholes that are exploited by crypto criminals. Crypto crime in the 2024-2025 period is becoming more professionalized, marked by the dominance of stablecoins, the involvement of state actors, and low asset recovery rates. Network-based international investigative cooperation, has proven to be more adaptive than unilateral repressive approaches. Implications: There is a need for harmonization of cross-border AML policies, acceleration of Travel Rule implementation, and strengthening of informal investigative cooperation mechanisms and public private partnerships with VASPs to improve the effectiveness of asset tracing and recovery. Contribution & Value Added: This study enriches the literature on digital economic crime by linking regulatory arbitrage and FATF networked governance, and provides the latest empirical evidence for the formulation of adaptive AML policies in the era of decentralized finance.
Digital Payment Instruments, Institutional Quality, and Corruption: Evidence from ASEAN El Hasanah, Lak lak Nazhat
Journal of Business Crime Vol. 2 No. 1 (2026)
Publisher : Generate Digital Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70764/gdpu-jbc.2026.2(1)-05

Abstract

Objective: This study analyzes how digital payment methods, institutional quality, and corruption levels relate in ASEAN countries. It examines how digital payment systems and factors such as the rule of law and regulatory quality affect corruption levels, as measured by the Corruption Perceptions Index (CPI).Research Design & Methods: This study uses a quantitative method called Panel Vector Autoregression (PVAR) to look at how variables relate to each other in panel data. It focuses on five ASEAN countries: Indonesia, Malaysia, Thailand, and Singapore, with data collected from 2010 to 2024.Findings: Research shows that in the short term, only bank credit and the quality of regulation have a significant impact on changes in corruption levels. The formal financial sector and high-quality regulation are important for perceptions of corruption. Digital payment instruments such as ATMs and e-money have a dynamic relationship, but do not have a significant direct impact in the short term.Implications: Research indicates that preventing corruption needs improvements in institutions, regulations, law enforcement, and digitized payment systems. Digital transformation in finance should be combined with institutional reforms to boost transparency, accountability, and integrity in the economy.Contribution & Value Added: This study looks at how digital financial systems, the quality of institutions, and corruption are connected in the ASEAN region. It uses a PVAR approach to analyze both short-term and long-term relationships between these factors. The results aim to show how digital transformation and governance quality can help decrease corruption in developing countries.

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