Detecting money laundering and terrorist financing via data mining

2004 ◽  
Vol 47 (5) ◽  
pp. 53 ◽  
Author(s):  
John S. Zdanowicz
Keyword(s):  
Data Mining ◽  
Money Laundering ◽  
Terrorist Financing

Data Mining in the Investigation of Money Laundering and Terrorist Financing

2011 ◽  
pp. 228-241 ◽  
Author(s):  
Ibrahim George ◽  
Manolya Kavakli
Keyword(s):  
Data Mining ◽  
High Risk ◽  
Decision Tree ◽  
Money Laundering ◽  
Financial Applications ◽  
Counter Terrorism ◽  
Terrorist Financing ◽  
Terrorism Financing ◽  
Operational Data ◽  
Financial Organisation

In this chapter, the authors explore the operational data related to transactions in a financial organisation to find out the suitable techniques to assess the origin and purpose of these transactions and to detect if they are relevant to money laundering. The authors‘ purpose is to provide an AML/CTF compliance report that provides AUSTRAC with information about reporting entities‘ compliance with the Anti-Money Laundering and Counter-Terrorism Financing Act 2006. Their aim is to look into the Money Laundering activities and try to identify the most critical classifiers that can be used in building a decision tree. The tree has been tested using a sample of the data and passing it through the relevant paths/scenarios on the tree. The success rate is 92%, however, the tree needs to be enhanced so that it can be used solely to identify the suspicious transactions. The authors propose that a decision tree using the classifiers identified in this chapter can be incorporated into financial applications to enable organizations to identify the High Risk transactions and monitor or report them accordingly.

Data Mining in the Investigation of Money Laundering and Terrorist Financing

Data Mining ◽  
2013 ◽  
pp. 2193-2207
Author(s):  
Ibrahim George ◽  
Manolya Kavakli
Keyword(s):  
Data Mining ◽  
High Risk ◽  
Decision Tree ◽  
Money Laundering ◽  
Financial Applications ◽  
Counter Terrorism ◽  
Terrorist Financing ◽  
Terrorism Financing ◽  
Operational Data ◽  
Financial Organisation

In this chapter, the authors explore the operational data related to transactions in a financial organisation to find out the suitable techniques to assess the origin and purpose of these transactions and to detect if they are relevant to money laundering. The authors’ purpose is to provide an AML/CTF compliance report that provides AUSTRAC with information about reporting entities’ compliance with the Anti-Money Laundering and Counter-Terrorism Financing Act 2006. Their aim is to look into the Money Laundering activities and try to identify the most critical classifiers that can be used in building a decision tree. The tree has been tested using a sample of the data and passing it through the relevant paths/scenarios on the tree. The success rate is 92%, however, the tree needs to be enhanced so that it can be used solely to identify the suspicious transactions. The authors propose that a decision tree using the classifiers identified in this chapter can be incorporated into financial applications to enable organizations to identify the High Risk transactions and monitor or report them accordingly.

scholarly journals Reconciliation of anti-money laundering instruments and European data protection requirements in permissionless blockchain spaces

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Iwona Karasek-Wojciechowicz
Keyword(s):  
Data Processing ◽  
Money Laundering ◽  
Data Protection ◽  
Task Force ◽  
Policy Instruments ◽  
Personal Data ◽  
General Data Protection Regulation ◽  
Terrorist Financing ◽  
The Government ◽  
High Level

AbstractThis article is an attempt to reconcile the requirements of the EU General Data Protection Regulation (GDPR) and anti-money laundering and combat terrorist financing (AML/CFT) instruments used in permissionless ecosystems based on distributed ledger technology (DLT). Usually, analysis is focused only on one of these regulations. Covering by this research the interplay between both regulations reveals their incoherencies in relation to permissionless DLT. The GDPR requirements force permissionless blockchain communities to use anonymization or, at the very least, strong pseudonymization technologies to ensure compliance of data processing with the GDPR. At the same time, instruments of global AML/CFT policy that are presently being implemented in many countries following the recommendations of the Financial Action Task Force, counteract the anonymity-enhanced technologies built into blockchain protocols. Solutions suggested in this article aim to induce the shaping of permissionless DLT-based networks in ways that at the same time would secure the protection of personal data according to the GDPR rules, while also addressing the money laundering and terrorist financing risks created by transactions in anonymous blockchain spaces or those with strong pseudonyms. Searching for new policy instruments is necessary to ensure that governments do not combat the development of all privacy-blockchains so as to enable a high level of privacy protection and GDPR-compliant data processing. This article indicates two AML/CFT tools which may be helpful for shaping privacy-blockchains that can enable the feasibility of such tools. The first tool is exceptional government access to transactional data written on non-transparent ledgers, obfuscated by advanced anonymization cryptography. The tool should be optional for networks as long as another effective AML/CFT measures are accessible for the intermediaries or for the government in relation to a given network. If these other measures are not available and the network does not grant exceptional access, the regulations should allow governments to combat the development of those networks. Effective tools in that scope should target the value of privacy-cryptocurrency, not its users. Such tools could include, as a tool of last resort, state attacks which would undermine the trust of the community in a specific network.

scholarly journals The Effects of Money Laundering (ML) on Growth Application to the Gulf Countries

2020 ◽  
pp. 1428-1441
Author(s):  
Fakhri Issaoui ◽  
Toumi Hassen ◽  
Touili Wassim
Keyword(s):  
Logistic Regression ◽  
Saudi Arabia ◽  
Money Laundering ◽  
Logit Model ◽  
Terrorist Financing ◽  
Positive Effects ◽  
The Third ◽  
Suspicious Transaction ◽  
Gulf Countries ◽  
Strategic Goal

The strategic goal of this paper is to study the effects of the prevention policies against money laundering on growth in the gulf countries (Saudi Arabia, Kuwait, Qatar, Bahrain, UAE and Oman) from 1980 to 2014. Thus, the logistic regression (logit model) had given three fundamental results. The first had shown that the main policies in matter of fight against money laundering (anti money laundering law AMLL, suspicious transaction reporting STR, the criminalizing of terrorist financing CTF) have had positive effects on the increasing of probabilities to realize more growth. The second is that the said policies have had positive effects on the increasing of the degree of openness of the whole sample. The third is that the variable (proximity) had a positive and significant effect on anti-money laundering policies.

scholarly journals FATF and Terror Financing: The Perspective of Pakistan

2021 ◽  
Vol VI (II) ◽  
pp. 1-10
Author(s):  
Shabnam Gul ◽  
Muhammad Faizan Asghar ◽  
Shujat Ali
Keyword(s):  
Money Laundering ◽  
Rule Of Law ◽  
International Organizations ◽  
Third World ◽  
World State ◽  
Terrorist Financing ◽  
Financial Transaction ◽  
The World ◽  
Money Transfers ◽  
And Control

There is a plethora of international organizations that has been formed to maintain peace in the world. FATF is such an organization that has been formed in order to scrutinize and control the menace of money laundering and that of the terror financing. In a third world state like Pakistan where there is dearth of transparent mechanisms of money transfers and where there is no rule of law, it has become easy for the individuals to carry out the illicit activities like money laundering (Dube and Vargas, 2013). Pakistan has been in the grey list from the last few years and it has dramatically affected the economy of Pakistan. Pakistan has established a number of centralized mechanisms that are, without a doubt, on the correct track for monitoring the financial transaction system, which is currently very near to meet the certain much needed criteria for finding and freezing the founded and highlighted money laundering cases and that of the terrorist financing.

Data mining in anti-money laundering field

2017 ◽  
Vol 20 (3) ◽  
pp. 301-310 ◽  
Author(s):  
Noriaki Yasaka
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Money Laundering ◽  
Design Methodology ◽  
Point Of View ◽  
Important Task ◽  
Content Type ◽  
Suspicious Transaction ◽  
Mining Methods ◽  
The Creation

Purpose This report aims to focus on how suspicious transaction report is created with data mining methods and used from the point of view of knowledge management. Design/methodology/approach This paper considers data mining versus knowledge management in the anti-money laundering (AML) field. Findings In the AML field, the information and knowledge gained are not necessarily used for or shared with the related shareholders. Creating and co-evolving the network of “knowledge professionals” is the impending assignment in this industry. The first and most important task is knowledge management in the global AML field. Originality/value The report considers the creation with data mining methods and utilization from the point of view of knowledge management.

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