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All Journal AML/CFT Journal The Journal of Anti Money Laundering and Countering the Financing of Terrorism
Alham, Lalu Garin
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Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice

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Pencucian Uang di Negara-Negara APEC: Analisis Model Gravitasi tentang Daya Tarik dan Pilihan Tujuan Ariesiyani, Amarillys Enika Noora; Alham, Lalu Garin
AML/CFT Journal : The Journal Of Anti Money Laundering And Countering The Financing Of Terrorism Vol 1 No 2 (2023): Permasalahan Hukum terkait Tindak Pidana Pencucian Uang
Publisher : Pusat Pelaporan dan Analisis Transaksi Keuangan (PPATK)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (824.875 KB) | DOI: 10.59593/amlcft.2023.v1i2.56

Abstract

This paper has three main contributions. First it attempts to measure which APEC countries are attractive destinations for money laundering to Indonesia. Second it measures and ranks the degree of money laundering attractiveness in-between APEC country members themselves. Third, it tests the variables contributing to a country’s money laundering attractiveness. The attractiveness is measured using the Gravity model derived from Newtonian gravitational equations by utilizing variables ranging from countries’ wealth, government attitude on money laundering, corruption perception index, SWIFT membership, conflict, financial secrecy, and physical & cultural distances. Pearson correlation analysis is also employed to test the statistical interaction & correlation between corresponding variables. Our simulations show that several countries consistently sit on the top 3 (three) most attractive money laundering destinations: Singapore, Hongkong, and the United States. It is also found that financial secrecy and GNI per capita significantly correlate with the degree of money laundering attractiveness. This analysis unveils that an attractive financial regime (beneficial ownership and bank secrecy) and a strong economy attract money launderers to conceal their ill-gotten money in a country.
Pencucian Uang di Negara-Negara APEC: Analisis Model Gravitasi tentang Daya Tarik dan Pilihan Tujuan Ariesiyani, Amarillys Enika Noora; Alham, Lalu Garin
AML/CFT Journal : The Journal Of Anti Money Laundering And Countering The Financing Of Terrorism Vol 1 No 2 (2023): Permasalahan Hukum terkait Tindak Pidana Pencucian Uang
Publisher : Pusat Pelaporan dan Analisis Transaksi Keuangan (PPATK)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59593/amlcft.2023.v1i2.56

Abstract

This paper has three main contributions. First it attempts to measure which APEC countries are attractive destinations for money laundering to Indonesia. Second it measures and ranks the degree of money laundering attractiveness in-between APEC country members themselves. Third, it tests the variables contributing to a country’s money laundering attractiveness. The attractiveness is measured using the Gravity model derived from Newtonian gravitational equations by utilizing variables ranging from countries’ wealth, government attitude on money laundering, corruption perception index, SWIFT membership, conflict, financial secrecy, and physical & cultural distances. Pearson correlation analysis is also employed to test the statistical interaction & correlation between corresponding variables. Our simulations show that several countries consistently sit on the top 3 (three) most attractive money laundering destinations: Singapore, Hongkong, and the United States. It is also found that financial secrecy and GNI per capita significantly correlate with the degree of money laundering attractiveness. This analysis unveils that an attractive financial regime (beneficial ownership and bank secrecy) and a strong economy attract money launderers to conceal their ill-gotten money in a country.
Deteksi Tipologi Pencucian Uang Berbasis Graph Analytics dan Neural Network Alham, Lalu Garin; Tsabitah, Nadia; Zaman, Yusuf Muhammad Nur
AML/CFT Journal : The Journal Of Anti Money Laundering And Countering The Financing Of Terrorism Vol 4 No 1 (2025): Pencucian Uang dan Pendanaan Terorisme: Risiko, Teknologi, dan Regulasi
Publisher : Pusat Pelaporan dan Analisis Transaksi Keuangan (PPATK)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59593/amlcft.2025.v4i1.269

Abstract

Money laundering accounts for an estimated 2–5% of global GDP annually with scale intensified by digital ecosystems. Conventional AML systems using primarily rule-based and transactional patterns struggle to detect relational behaviors of financial crimes. This study introduces an integrated graph-analytic framework to detect structural laundering patterns using graph-derived metrics to neural network pipeline. The paper evaluates eccentricity, degree, closeness measures, and directionality of flow to distinguish laundering activities, supported by Welch’s t-test which confirms statistically significant differences across five of six metrics (p < 0.001). A Multi-Layer Perceptron (MLP) model is further applied to classify 17 typologies with ~80% accuracy. The key contribution of this research lies in demonstrating that financial crime typologies can be extracted from network topology itself instead of sole reliance on transactional features. By linking graph metrics with laundering behaviors including placement, layering, and integration patterns the study provides a scalable, network-aware approach to AML detection. Future work should focus on real-world validation and real-time classification pipelines using graph-neural inference.
Co-Authors Ariesiyani, Amarillys Enika Noora Tsabitah, Nadia Zaman, Yusuf Muhammad Nur