Search results

There is increasing international concern about the escalation of fraud and, in particular, financial statement fraud. Detecting financial statement fraud and proving such fraud remains an elusive goal. Red flagging is an early warning system that has been used by auditors to determine the probability of financial statement fraud. The purpose of this research project was to survey investors and lenders in South Africa on their use of red flags and to obtain their opinions on the relative importance of individual red flags. A questionnaire was sent to banks that are registered with the Registrar of Banks (representative of lenders) and to portfolio managers registered with the Financial Services Board (representative of investors). The research findings indicate that lenders and investors in South Africa appear to be aware of the benefits of red flagging as an early warning system. A structured approach (questionnaires/checklists) in using them is to be lacking at present. Respondents rated all red flags in the questionnaire as being important. No distinction was discernable among the different categories that were based on the nature of red flags.

Aims to identify the most important red flags as individually perceived by auditors, and explores whether auditors' demographic factors might impact on their perception of the relative importance of red flags in Malaysia, particularly in the Klang Valley area.

This study employed a mailed survey as a method of data collection. The respondents to this survey are practicing auditors from audit firms in Kuala Lumpur. The sample of auditors is taken from the population of domestic listed audit firms with the Malaysian Institute of Accountants as of 27 March 2003. A simple random technique is applied to construct the sample.

In general, subjects indicated that the operating and financial stability category was judged as most important, followed by management characteristics and influence over the control environment, and then finally by industry characteristics.

It would be interesting to examine whether these fraud risk indicators are indeed helpful in the investigation of reported misconduct and fraudulent cases in Malaysia. The findings may help researchers to develop a new fraud risk indicator that takes into consideration actual instances of fraud in Malaysia.

This study aims to, firstly, develop a red flag checklist for cryptocurrency Ponzi schemes and, secondly, to test this red flag checklist against publicly available marketing material for Mirror Trading International (MTI). The red flag checklist test seeks to establish if MTI’s marketing material posted on YouTube^® (in the form of a live video presentation) exhibits any of the red flags from the checklist.

The study uses a structured literature review and qualitative analysis of red flags for Ponzi and cryptocurrency Ponzi schemes.

A research lacuna was discovered with regard to cryptocurrency Ponzi scheme red flags. By means of a structured literature review, journal papers were identified that listed and discussed Ponzi scheme red flags. The red flags from the identified journal papers were subsequently used in a qualitative analysis. The analyses and syntheses resulted in the development of a red flag checklist for cryptocurrency Ponzi schemes, with five red flag categories, containing 18 associated red flags. The red flag checklist was then tested against MTI’s marketing material (a transcription of a live YouTube presentation). The test resulted in MTI’s marketing material exhibiting 88% of the red flags contained within the checklist.

The inherent limitations in the design of using a structured literature review and the lack of research regarding the cryptocurrency Ponzi scheme red flags.

The study provides a red flag checklist for cryptocurrency Ponzi schemes. The red flag checklist can be applied to a cryptocurrency investment scheme’s marketing material to establish if it exhibits any of these red flags.

The red flag checklist can be applied to a cryptocurrency investment scheme’s marketing material to establish if it exhibits any of these red flags.

The study provides a red flag checklist for cryptocurrency Ponzi schemes.

In 2009, the research team of Unger and Nelen was requested to study the scale of entwinement between money laundering activities and the Dutch real estate sector. For this, the team developed a data mining framework to detect real estate property at risk of being part of a money laundering scheme. Part of this study involved a criminological testing of the developed framework which resulted in the statement that improvements and alterations are necessary to increase the framework's validity and reliability. This paper aims to review this framework and generate refinements.

This paper is concerned with a review – on the basis of data mining theory – with respect to the original framework in order to generate refinements for a future model.

In general, three major shortcomings were identified, being: the use of unspecified detection clusters; the theoretical nature of some of the risk indicators in combination with data integrity issues; and the use of speculative/arbitrary risk indicators.

Addressing these shortcomings in a future data mining framework will very likely increase its effectiveness and so, increase the ability of law enforcement agencies to counter money laundering activities more effectively and efficiently.

According to the Association of Certified Fraud Examiners, financial statement fraud represents the smallest amount of fraud cases but results in the greatest monetary loss. The researcher previously investigated the characteristics of financial statement fraud and determined the presence of 16 fraud indicators. The purpose of this study is to establish whether investors and other stakeholders can detect and identify financial statement fraud using these characteristics in an analysis of a company’s annual report.

This study analyses a financial statement fraud case, using the same techniques that were previously applied, including horizontal, vertical and ratio analysis. These are preferred because stakeholders have relatively easy access to them.

The findings show several fraud characteristics, with a few additional ones not previously found prevalent. Financial statement fraud thus tends to differ between cases. It is also easier to detect and identify fraud indicators ex post facto.

This study is a practical case showing that financial statement fraud can be detected and identified in the financial statements of companies that commit fraud.

The purpose of this paper is to highlight the intelligence and investigatory challenges experienced by law enforcement agencies in discovering the identity of illicit Bitcoin users and the transactions that they perform. This paper proposes solutions to assist law enforcement agencies in piecing together the disparate and complex technical, behavioural and criminological elements that make up cybercriminal offending.

A literature review was conducted to highlight the main law enforcement challenges and discussions and examine current discourse in the areas of anonymity and attribution. The paper also looked at other research and projects that aim to identify illicit transactions involving cryptocurrencies and the darknet.

An optimal solution would be one which has a predictive capability and a machine learning architecture which automatically collects and analyses data from the Bitcoin blockchain and other external data sources and applies search criteria matching, indexing and clustering to identify suspicious behaviours. The implementation of a machine learning architecture would help improve results over time and would be less manpower intensive. Cyber investigators would also receive intelligence in a format and language that they understand and it would allow for intelligence-led and predictive policing rather than reactive policing. The optimal solution would be one which allows for intelligence-led, predictive policing and enables and encourages information sharing between multiple stakeholders from the law enforcement, financial intelligence units, cyber security organisations and fintech industry. This would enable the creation of red flags and behaviour models and the provision of up-to-date intelligence on the threat landscape to form a viable intelligence product for law enforcement agencies so that they can more easily get to the who, what, when and where.

The development of a functional software architecture that, in theory, could be used to detected suspicious illicit transactions on the Bitcoin network.

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.

Partnerships between the public and private sectors represent one of the strongest means to detect, deter, disrupt and deny terrorist and other criminal organizations illicit profits and material support required to fuel their evil acts. The purpose of this paper is to discuss and illustrate through case study, the importance of public and private sector partnership in combating terrorist financing and other financial crimes.

Two case studies are presented demonstrating how the public and private sectors can collaboratively work to target how criminal organizations earn, move and store their illicit profits. Highlighted is US Immigration and Customs Enforcement's (ICE's) outreach and partnership program, Cornerstone. Through working partnerships with US financial, trade, manufacturing and transportation sectors, Cornerstone's goal is to eliminate systemic vulnerabilities that could be exploited by terrorist and other criminal organizations.

ICE provides the private sector with information on trends, patterns, and “red flag” indicators that are identified during criminal investigations. This information can be used by the private sector to assist in establishment of internal controls and systems designed to protect their institutions from criminal exploitation.

Sharing identified vulnerabilities and information with trusted private sector partners, is the first line of defense against financial crimes, and the cornerstone of private/public partnership.

The paper stresses that all nations must recognize that any criminal act – whether driven by profit or ideology – threatens a nations economic security and integrity. In today's global economy, this impact can have devastating consequences transcending many borders.

This paper aims to start with the assumption that money laundering through the use of investments will continue to occur and will become increasingly more complex to try and avoid detection. The paper aims to explore some of the theoretical factors that would need to be considered in any risk based framework and also to consider how an empirical model can try and prioritise the information and intelligence gathered through existing beneficial ownership and customer due diligence (CDD) systems.

This paper uses an empirical example of money laundering with investments and highlights the red flag indicators that led to its eventual discovery. The theoretical framework considers the difficulties of information overload and suggests that any empirical model of risk-based assessment would need to be able to discern between the various types of risk information gathered. The paper has developed one empirical model that could be used.

The paper suggests a model that breaks down beneficial ownership and CDD information into three areas: beneficial ownership for all major players, transparency of transactions and accountability of companies involved.

The paper has implications for the banking, regulatory and law enforcement sectors working in Anti-Money Laundering (AML).

The paper analyses a particular type of money laundering activity which it terms “investment laundering” using an empirical case study. It then develops a new theoretical and empirical risk assessment model to illustrate how risk-based approaches need to be able to discern between the different types of information gathered and the application to overall risk.

The purpose of this paper is to raise awareness about internal fraud in small businesses among small business owners, managers, and consultants.

Recent statistics from international fraud surveys are presented, and the theory of why people commit fraud is described. The most common internal fraud schemes as identified in the international fraud surveys are explained, as well as some of the related red flags and preventative measures. Examples of actual internal frauds perpetrated in small businesses are discussed.

This paper summarizes pertinent facts that repeatedly show small businesses are most vulnerable to fraud and suffer a disproportionate median loss when compared to larger businesses. External audits by Certified Public Accountants cannot be relied upon to detect fraud. Owners, managers, and advisors are strongly encouraged to have knowledge of how fraud can affect their organizations in order to prevent or detect fraud and avoid the devastating effect it can have on the small business’s viability.

Fraud knowledge can help owners, managers, and advisors prevent small businesses from falling victim to fraud.

This paper addresses a critical issue to small businesses, but has so far been largely neglected in the literature. While large financial statement frauds receive widespread publicity, they are relatively uncommon compared to asset misappropriation fraud schemes suffered by small businesses.