Search results

The purpose of this paper is to analyze the obligation of regulated entities to detect unusual and suspicious transactions and to report them to external control bodies, as established by the Financial Action Task Force (FATF) recommendations, the European Community Directive and also the Spanish regulations for the Prevention of Money Laundering. This research paper also aims to create a model to identify and report suspicious transactions to improve financial institutions’ current procedures.

According to the Spanish regulations which comply with the FATF recommendations and the European Community Directive on the Prevention of Money Laundering, regulated entities must detect unusual and suspicious transactions. Within this framework, the present research work analyzes both criteria and procedures used by the regulated entities to report suspicious operations. It also assesses the efficiency of the reports sent to an external control body. For this purpose, both analytical and interpretative methods are used in this research paper.

In Spain, the current procedures followed by regulated entities to analyze unusual transactions are complex. This results in difficulties to report suspicious transactions involving money laundering. As a consequence, the cases of suspicious transactions reported to the external control body are often unclear and the related process is inefficient.

The creation of a harmonized model with the aim of detecting suspicious operations and analyzing them will improve the detection and the effectiveness of the suspicious operations procedure which are reported to the external control body. However, such unified model should take into account the currently used activities proposed by each financial institution.

This study aims to evaluate the suspicious transaction reporting (STR) as a financial intelligence tool to identify the potential strengths and limitations of STR and to come up with the criteria, which will make this tool an effective one in early detection of terrorist financing activities.

Considering the research aim, this research uses the funnelling method for identifying effectiveness criteria. Funnelling is a method of literature review that helps find pertinent literature by refining the search through filtering the available research (Ridley, 2008). Using this method, the researcher first applied the criteria of actionable intelligence to filter the financial intelligence tools to select the most promising and important tool (suspicious transaction reporting) for early detection of terrorist financing activities. The funnelling method was also applied to derive the effectiveness criteria from the operational features, and corresponding limitations, of the suspicious transaction reporting system. The funnelling method was also used to identify those operational features and limitations of suspicious transaction reporting that have the most direct relevance to the early detection problem of suspicious transaction reporting.

There are some operational features of STR that give rise to certain limitations that undermine its effectiveness in terms of early detection of terrorist financing activities. The limitations of STR necessitate a search for criteria that will make STR effective in early detection of terrorist financing activities. Based on the operational features and their corresponding limitations, effectiveness criteria for STR have been derived in this study. It is shown how these effectiveness criteria can remove the limitations of STR.

The list of operational features and the corresponding limitations based on which the effectiveness criteria have been derived may not be exhaustive. There may have other operational features, and corresponding limitations that also make STR largely ineffective in the early detection of terrorist financing activities, and for which more effectiveness criteria should also be derived.

The limitations and the effectiveness criteria will pave the way for redesigning STR in such a way that will make it highly useful for detecting financing activities relating to imminent terrorist attacks.

The society will experience fewer terrorist attacks that will make the society peaceful, happy and vibrant.

In this study, the effectiveness criteria of STR for early detection of terrorist financing activities have been derived in an innovative way by deducing them from the operational features of STR and the corresponding limitations.

The purpose of this study is to make clear the structure of suspicious transaction reporting system in Japan from perspective of knowledge management. Because of the institutionalization of law, suspicious transaction reports in Japan have increased, but most of these reports are from financial institutions. Moreover, it cannot be said that the effect is used completely. It is important to increase the accuracy of the data mining method and incorporate the concept of knowledge management. Furthermore, it is desirable to use suspicious transactions from a global “knowledge management” perspective.

Based on the case of the Japanese transaction reporting system, Global knowledge management of suspicious transaction reporting system would be considered.

It is effective for money laundering countermeasures to deepen knowledge management of data → information → knowledge → wisdom. This brings the refinement of typology at the transaction unit to the upper level. This repetition has become more advanced and generalized knowledge. Knowledge transferred from national stage to international stage is organized as further information → knowledge → wisdom by collecting data based on that knowledge. By repeating this systematization in the process of knowledge management, global prevention measures against money laundering would be disseminated. As the result of these efforts, effective counter measures against money laundering could be sharper than before.

This is the first study about the analysis of suspicious transaction reporting system in Japan linked to the global knowledge management.

This paper proposes to use system integration between customer relationship management (CRM) and anti‐money laundering (AML) suspicious data reporting in commercial banks to increase the initiative of suspicious transaction identification, reduce the false reporting rates, and improve the intelligence quality.

This paper introduces the structure of CRM in commercial banks, discusses deficiencies of the current AML data reporting system, and designs the layering of CRM and AML transaction identification module.

This paper finds that the functions of customer behavior analysis and customer background investigation of CRM system can be redesigned and used for increasing the quality of AML suspicious transaction reporting in commercial banks.

This paper creatively proposes that system integration of CRM and AML suspicious transaction reporting can make a contribution to reducing the AML cost for commercial banks.

This study aims to use a unique customer-information data set from a Norwegian bank to identify how small changes in firm-specific factors correlate with the risk of a client subsequently being involved in suspicious transactions. It provides insight into the importance of updating client risk based on changes in transaction volume and credit risk to enable effective resource use in transaction monitoring.

Changes in a firm’s bank use and accounting data were tested against subsequent flagged and reported customers to identify which changes led to a significant increase in the probability of engaging in a transaction identified as suspicious. Prioritizing resources to firms that remain suspicious after further controls can improve the risk-based approach and prioritize detection efforts. The main factors were customer probability of default (credit score), size and changes in customer characteristics. The cross-sectional data set contained administrative data on 8,538 corporate customers (219 with suspicious transactions that were subsequently flagged, 64 of which were reported). A binomial logit model was used.

Changes in transaction volume and bank use are significant in predicting subsequent suspicious transactions. Customer credit score changes were significantly positively correlated with the likelihood of flagging and reporting. Change is a stronger indicator of suspicious transactions than the level. Thus, frequent updating of client risk and using a scale rather than risk categories can improve client risk monitoring. The results also showed that the current anti-money laundering (AML) system is size-dependent; the greater the change in customer size, the greater the probability of the firm subsequently engaging in a suspicious transaction.

Client risk classification, monitoring changes in a client’s use of the bank and business risk should receive more attention.

The authors demonstrate that client risk classifications should be dynamic and sensitive to even small changes, including monitoring the client’s credit risk changes.

Directing AML efforts to clients with characteristics indicating risk and monitoring changes in factors contributing to risk can increase efficiency in detecting money laundering.

To the best of the authors’ knowledge, this is the first study to focus on changes in a firm's use of a bank and link this to the probability of detecting a suspicious transaction.

This paper aims to provide information of parameters and techniques used in the automated fraud detection system during online transaction. With the increase in the use of online transactions, the concerns regarding data security have also increased. To tackle the frauds, lot of research has been done and plethora of papers are available on the related topics. The purpose of this paper is to provide the clear pathway for researchers to move in the direction of development of automated fraud detection system to prevent the fraud during online transaction.

This literature review analyses and compares the different types of techniques for detecting fraud during online transaction. An in-depth study of the most prominent journals has been done and the core methodology of the papers has been presented. This article also shed some light on different types of parameters used in fraud detection techniques during online transaction.

There are vast varieties of various fraud detection techniques, and every technique has completed task in its own way. After studying approximately 41 research papers, 14 books and four reports, in total 30 parameters have been identified and a detailed study of the parameters has been presented. The parameters are also listed with their details that how these parameters are used in the security system for detecting online transaction fraud.

This paper provides empirical insight about the parameters and their prominence in the development of automated fraud detection security system of online transaction. This paper encourages the researchers to development of improved fraud detection system.

This paper will pave the way for researchers to do a focused research on the fraud detection methodologies. The analysis will help in zeroing down the most prevalent topic of research in this field. The researchers will be able to understand the internal details of parameters and techniques used in the fraud detection systems. This literature also helps the research to think in a variety of ways that how these parameters will be used in the development of fraud detection system.

This paper is one of the most comprehensive reviews in its field. It tries and attempts to fill a void created because of lack of compilation of the laid fraud detection parameters.

The purpose of this paper is to provide an analysis of the recent Crédit Agricole case outcome, whereby the bank was found to have undertaken insufficient investigation and failed to follow through on reporting suspicious account activity, in line with AML compliance requirements.

The paper uses the two main legal documents in the Michailidis v Crédit Agricole Corporate and Investment (CACI) bank case and analyses the judgement details to discuss the implications for the banking and financial services sector on money laundering and AML compliance reporting requirements.

The main findings from the analysis are that banks have a greater legal responsibility towards detecting and reporting suspicious transactions than they would have previously considered. This includes identifying the source and purpose of fund transfers and establishing the beneficial ownership of recipients.

The research topic is new, and therefore, analysis papers and other academic writing on this topic are limited.

The research paper has identified a number of implications to the banking sector on addressing AML deficiencies, especially the detection and reporting requirements of suspicious transactions.

This paper has implications for the corporate social responsibility of banks and other financial services towards monitoring the source and use of money that is in their organisation. The paper identifies areas of legal responsibility that banks now have to manage, as part of their commitment to support the prevention of money laundering.

The originality of this paper is the current example of the Crédit Agricole case and the future legal implications for banks and financial services on suspicious transaction reporting and money laundering risk assessment.

In 2019, FIU-the Netherlands celebrated its 25th anniversary. This study takes the occasion to reflect on the role of the FIU in financial surveillance and to describe its core practices of collecting, analysing and disseminating financial intelligence.

Because FIU practices are often secret and its transaction data classified as state secrets, the FIU’s daily operational activities remain obscure. Drawing on interviews, public reports and an online training course, this study encircles secrecy and offers a fine-grained analysis of the FIU's core activities.

The article finds that the FIU plays a pivotal role in financial surveillance because it can operate at various intersections. An FIU operates at the intersection of finance and security, in between the public and private sector and at the national and international domain. This pivotal role makes the FIU indispensable in the surveillance of payment systems and spending behavior.

The article poses that the desirability and effectiveness of financial surveillance has to date not received sufficient consideration, while it affects (the privacy of) anyone with a bank account. The article asks: is it ethically justifiable that transaction information is declared suspect, investigated, and shared nationally and internationally, without the individual or entity concerned officially being notified and legally named a suspect?

This case-study is not only relevant for the study of finance/security, AML/CFT and financial surveillance, but also to policy makers and the broader public who merit an understanding of how their financial behaviour is being surveilled.

The purpose of this paper is to use statistical techniques to mine and analyze suspicious transactions. With the increase in money laundering activities across various sectors in some of the world’s leading democracies, the ability to detect such transactions is gaining grounds with more urgency. Regulators and practitioners have been calling for an approach that can mine the large volume of unstructured data form suspicious money laundering transactions to inform public policies.

By deducing from the results of empirical studies in the field of money laundering detection, this paper presented an overview of data mining technology for detecting suspicious transactions.

After chronicling the data mining process, the paper delves into an analysis of the statistical approaches that can be used to differentiate between legitimate and suspicious money laundering transactions. The different stages of the data mining process are carefully explained in relation to their application to anti-money laundering compliance. The results indicate that statistical data mining methodology is a very efficient and useful technique to detect suspicious transactions.

The paper is of relevance to regulators and the financial service sector. A discussion of how data can be mined to facilitate statistical analysis can be used to inform regulatory policies on the detection and prevention of money laundering activities in the financial service sector.

The paper discuss approaches that illustrate how analysts can use statistical techniques to analyze data for suspicious money laundering transactions

Reporting suspicious transactions under anti‐money laundering (AML) laws creates a major dilemma for banks. On the one hand, failure to report suspicious transactions is an offence under the laws. On the other hand, if they report the transaction, they may breach their duty of confidentiality to their customer or could be liable for tipping off the suspected customer. More importantly, it can also undermine customers' trust. The purpose of this paper is to look into these issues and analyse them against the background of the Malaysian AML laws.

This paper mainly relies on statutes as its primary sources of information. As such, the relevant Malaysian AML that affect the reporting obligations will be identified and analyzed. It will be necessary to examine not just the provisions of the Malaysian Anti‐Money Laundering and Anti‐Terrorism Financing Act, but also its regulations and guidelines which affect banks in detail, as this is the most important legislation for the purpose of this paper.

It is apparent that the reporting suspicious transactions regime has had a significant impact on the operations of banks in Malaysia. While the regime is based on sound principles, the effectiveness of the regime is still unknown. As such, only time will tell whether the banks will be able to cope sufficiently with the increased AML obligations. Obviously, it is critical at this stage, to establish effective coordination between legislators, regulators and the banking industry, in order to minimize problems faced by the banks and thereby to ensure effective implementation of the regime.

This paper provides an examination of the impact of the reporting suspicious transactions regime on Malaysian banks. It is hoped that the study would provide some insight into this particular area for academics, banks, their legal advisers, practitioners and policy makers, not only in Malaysia but also elsewhere. In view of the international nature of money laundering and banking, there will be significant interest in how the AML laws affect banks operating in Malaysia.