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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.

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 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.

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 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.

Apart from presenting an overview and background on anti-money laundering (AML) rules and procedures for casinos in both Macao and the USA, this paper aims to examine the differences in their regulatory approaches with regard to their existing AML reporting processes and discusses possible weaknesses in their respective regulatory regime.

Given that the regulations and statistics on the AML issues may not all be publicly available, the authors managed to secure some data from the bureaus concerned through published reports and interviews with government officials. Regarding the AML procedures in casinos, the authors attempted to go over the annual reports published by the casinos for submission to the Hong Kong Stock Exchanges and Clearing Limited because all these casinos are listed companies in Hong Kong.

This paper analyzes the trends in reporting numbers and the categorization of the types of suspicious activity reports filed both in Macao and the USA. While the US suspicious activity reporting focuses on efforts to avoid currency reporting, Macao emphasizes improper or inadequate documentation and identification.

This paper is one of the few articles comparing the AML rules and procedures between casinos in the USA and Macao. It seeks to highlight the differences in their regulatory approaches and discusses the expected future direction of AML legislation.

The purpose of this paper is to develop, describe and validate a machine learning model for prioritising which financial transactions should be manually investigated for potential money laundering. The model is applied to a large data set from Norway’s largest bank, DNB.

A supervised machine learning model is trained by using three types of historic data: “normal” legal transactions; those flagged as suspicious by the bank’s internal alert system; and potential money laundering cases reported to the authorities. The model is trained to predict the probability that a new transaction should be reported, using information such as background information about the sender/receiver, their earlier behaviour and their transaction history.

The paper demonstrates that the common approach of not using non-reported alerts (i.e. transactions that are investigated but not reported) in the training of the model can lead to sub-optimal results. The same applies to the use of normal (un-investigated) transactions. Our developed method outperforms the bank’s current approach in terms of a fair measure of performance.

This research study is one of very few published anti-money laundering (AML) models for suspicious transactions that have been applied to a realistically sized data set. The paper also presents a new performance measure specifically tailored to compare the proposed method to the bank’s existing AML system.

Anti-money laundering has attracted much global attention, driving banks to invest in the establishment of suspicious transaction report mechanisms for the declaration of suspicious transactions. However, very few studies discuss how to influence bank employees to proactively declare suspicious transactions. Therefore, the purpose of this study is to, based on an organizational commitment perspective, establish a causal model that can assist banks to identify key factors affecting the intention to declare suspicious transactions.

This study first summarized five factors – regulatory focus, organization climate, situational constraints, personality traits and role stress – and their composition constructs as the basis for measurements. An interview-based survey of nine Taiwanese banks was conducted. Then, this study adopted the decision-making trial and evaluation laboratory method to analyse the interplay between the five factors to identify the causal model and to explore the differences in the effects of the key factors, arising from the different organizational and job patterns, on the intention to declare suspicious transactions.

The results show that regulatory focus and organizational climate are the most important causal factors affecting employees’ intention to declare suspicious transactions, whereas role stress and personality traits are the most influenced effect factors. In addition, this study also confirmed that under different organizational and job patterns, the understanding of employees will change.

This paper provides insight into the interplay between the five factors based on an organizational commitment perspective. The findings can assist banks in managing and monitoring the implementation of the suspicious transaction report mechanism.

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.