Enhancing Money Laundering Investigation Through Analytic Maturity
DOI:
https://doi.org/10.37385/ijedr.v5i2.5348Keywords:
Financial Intelligence Unit, Anti-Money Laundering, Analytic Maturity Model, Financial InvestigationAbstract
Using Analytic Maturity Model (AMM) from the Organisation for Economic Co-operation and Development (OECD) (2022) framework, this study aims to examine the analytic capabilities of Pusat Pelaporan dan Analisis Transaksi Keuangan (PPATK) as Indonesia’s Financial Intelligence Unit (henceforth, FIU Indonesia) in using its resources and getting the most out of its internal and external data to produce financial intelligence reports used by law enforcement authorities to conduct money laundering investigations and/or its predicate offenses. OECD AMM consists of two perspectives: strategic and operational. Each perspective contains indicative attributes that assist in understanding what a given level of maturity means. These indicative attributes were assessed using in-depth interviews and/or results from focus group discussions as primary data and then validated using the triangulated method, with desk review as secondary data. This research found that FIU Indonesia has achieved level 3 out of 5 levels of analytic maturity based on OECD AMM from both strategic and operational perspectives. To encourage money laundering investigations, FIU Indonesia should improve the process of prioritizing cases by enhancing its analytical capabilities.
References
Achim, M. V., & Borlea, S. N. (2020). Economic and Financial Crime. Springer Cham. https://doi.org/https://doi.org/10.1007/978-3-030-51780-9
Akartuna, E. A., Johnson, S. D., & Thornton, A. (2022). Preventing the money laundering and terrorist financing risks of emerging technologies: An international policy Delphi study. Technological Forecasting and Social Change, 179(March), 121632. https://doi.org/10.1016/j.techfore.2022.121632
Aprilia, G. F., & Meiryani. (2023). Exploring detection and prevention of money laundering with information technology. Journal of Money Laundering Control. https://doi.org/10.1108/JMLC-08-2023-0138
Bartolozzi, D., Gara, M., Marchetti, D. J., & Masciandaro, D. (2022). Designing the anti-money laundering supervisor: The governance of the financial intelligence units. International Review of Economics and Finance, 80(March), 1093–1109. https://doi.org/10.1016/j.iref.2022.03.009
Bellomarini, L., Laurenza, E., & Sallinger, E. (2020). Rule-based Anti-Money Laundering in Financial Intelligence Units: Experience and Vision?. CEUR Workshop Proceedings, 2644, 133–144.
Cabinet Secretary of The Republic of Indonesia. (2023). Indonesia Becomes Full Member of FATF. https://setkab.go.id/en/indonesia-becomes-full-member-of-fatf/
Cassara, J. A. (2020). Money Laundering and Illicit Financial Flows. Independently published.
Cheng, X., Liu, S., Sun, X., Wang, Z., Zhou, H., Shao, Y., & Shen, H. (2021). Combating emerging financial risks in the big data era: A perspective review. Fundamental Research, 1(5), 595–606. https://doi.org/10.1016/j.fmre.2021.08.017
Cox, D. (2014). Handbook of Anti Money Laundering. John Wiley & Sons, Ltd. https://doi.org/10.1002/9780470685280
Egmont Group. (2024). Financial Intelligence Units. https://egmontgroup.org/about/financial-intelligence-units/
FATF. (2021a). Digital Transformation of AML/CFT for Operational Agencies (Issue October). https://www.fatf-gafi.org/content/fatf-gafi/en/publications/Digitaltransformation/Digital-transformation-aml-cft.html
FATF. (2021b). Opportunities and Challenges of New Technologies For AML/CFT (Issue July). https://www.fatf-gafi.org/en/publications/Digitaltransformation/Opportunities-challenges-new-technologies-for-aml-cft.html
FATF. (2023a). Anti-money laundering and counter-terrorist financing measures –Indonesia. In Fourth Round Mutual Evaluation Report. http://www.fatf-gafi.org/publications/mutualevaluations/documents/mer-south-africa- 2021.html%0A©2021
FATF. (2023b). International Standards on Combating Money Laundering and the Financing of Terrorism & Proliferation. www.fatf-gafi.org/en/publications/Fatfrecommendations/Fatf-recommendations.html%0A©
FATF. (2024a). Countries. https://www.fatf-gafi.org/en/countries.html
FATF. (2024b). History of FATF. https://www.fatf-gafi.org/en/the-fatf/history-of-the-fatf.html
FIU Indonesia. (2020). 2020-2024 Rencana Stratejik. https://www.ppatk.go.id/publikasi/read/119/rencana-strategis-tahun-2020-2024-ppatk.html
FIU Indonesia. (2023). 2022 Laporan Kinerja. https://www.ppatk.go.id/publikasi/read/191/laporan-kinerja-tahun-2022.html
FIU Indonesia. (2024). 2023 Laporan Kinerja. https://www.ppatk.go.id/publikasi/read/218/laporan-kinerja-ppatk-tahun-2023.html
Garnasih, Y. (2016). Penegakan hukum anti pencucian uang dan permasalahannya di Indonesia. Rajawali Pers.
Grossman, R. L. (2018). A framework for evaluating the analytic maturity of an organization. International Journal of Information Management, 38(1), 45–51. https://doi.org/10.1016/j.ijinfomgt.2017.08.005
Halper, F. (2022). TDWI 2022 Analytics Maturity Model Assessment Guide. TWDI (Trasforming Data With Intelligence).
Han, J., Huang, Y., Liu, S., & Towey, K. (2020). Artificial intelligence for anti-money laundering: a review and extension. Digital Finance, 2(3–4), 211–239. https://doi.org/10.1007/s42521-020-00023-1
International Monetary Fund, & World Bank. (2004). Financial Intelligence Units: An Overview International Monetary Fund World Bank 2004. https://www.imf.org/external/pubs/ft/FIU/fiu.pdf
Jaleel, A., Syed Mustapha Nazri, S. N. F., Zolkaflil, S., Omar, N., & Shafie, N. A. (2021). The Effectiveness of Maldives’ Financial Intelligence Unit in Combating Money Laundering. Asia-Pacific Management Accounting Journal, 16(3), 409–435. https://doi.org/10.24191/apmaj.v16i3-16
Jayasekara, S. D. (2022). Administrative model of financial intelligence units: an analysis of effectiveness of the AML/CFT regime. Journal of Money Laundering Control, 25(3), 511–525. https://doi.org/10.1108/JMLC-05-2021-0048
Jensen, R. I. T., & Iosifidis, A. (2023). Fighting Money Laundering With Statistics and Machine Learning. IEEE Access, 11(December 2022), 8889–8903. https://doi.org/10.1109/ACCESS.2023.3239549
Jullum, M., Løland, A., Huseby, R. B., Ånonsen, G., & Lorentzen, J. (2020). Detecting money laundering transactions with machine learning. Journal of Money Laundering Control, 23(1), 173–186. https://doi.org/10.1108/JMLC-07-2019-0055
Król, K., & Zdonek, D. (2020). Analytics maturity models: An overview. Information (Switzerland), 11(3), 1–19. https://doi.org/10.3390/info11030142
Lagerwaard, P. (2022). Financial surveillance and the role of the Financial Intelligence Unit (FIU) in the Netherlands. Journal of Money Laundering Control, 26(7), 63–84. https://doi.org/10.1108/JMLC-09-2022-0134
Meiryani, M., Soepriyanto, G., & Audrelia, J. (2023). Effectiveness of regulatory technology implementation in Indonesian banking sector to prevent money laundering and terrorist financing. Journal of Money Laundering Control, 26(4), 892–908. https://doi.org/10.1108/JMLC-04-2022-0059
Nance, M. T. (2018). The regime that FATF built: an introduction to the Financial Action Task Force. Crime, Law and Social Change. https://doi.org/10.1007/s10611-017-9747-6
OECD. (2022). Analytic Maturity Model. https://www.oecd.org/tax/forum-on-tax-administration/about/maturity-model-series.htm
Prastuti, G., & Lasmin. (2021). Assessing Analytics Maturity Level in the Indonesian Tax Administration: the Case of Compliance Risk Management. Scientax, 2(2), 199–217. https://doi.org/10.52869/st.v2i2.157
Rengganis, F. D., & Susanto, D. S. (2023). Evaluation of the anti-money laundering programs implementation in Indonesia. Integritas: Jurnal Antikorupsi, 9(2), 229–240. https://doi.org/http://dx.doi.org/10.32697/integritas.v9i2.973
Law of The Republic of Indonesia Number 8 Year 2010 regarding Countermeasure and Eradication of Money Laundering, (2010). https://centralauthority.kemenkumham.go.id/images/PDFmedia/5_Law_No_8_Year_2010_on_Countermeasure_and_Eradication_of_Money_Laundering.pdf
Sari, A. N. (2021). Akuntansi Forensik dalam Menelusuri Dana Hasil Kejahatan. Universitas Indonesia.
Surkovic, A. (2021). Criminal Investigation of Money Laundering in the Practice of the Financial Intelligence Unit of the State Investigation and Protection Agency. Praxis International Journal of Social Science and Literature, 4(2), 42–52. https://doi.org/10.51879/pijssl/4.2.10
United Nations. (2024). GoAML Approach and Benefits. https://unite.un.org/goaml/content/approach-and-benefits
Ünvan, Y. A. (2020). Financial Crime: A Review of Literature. In S. Grima, E. Boztepe, & P. J. Baldacchino (Eds.), Contemporary Issues in Audit Management and Forensic Accounting (Vol. 102, pp. 265–272). Emerald Publishing Limited. https://doi.org/10.1108/S1569-375920200000102019
Yusoff, Y. H., Azlan, N. A. F., Zamzuri, N. N. M., Sufian, N., Rudy Kurniawan, S. N., & Hassan, R. (2023). Areas of Technology That Helps in Combating Money Laundering: A Concept Paper. International Journal of Academic Research in Business and Social Sciences, 13(5). https://doi.org/10.6007/ijarbss/v13-i5/16588
