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Purpose – This study investigates the nature, types, and methods of fraudulent financial reporting committed by Chinese listed companies with a view to understanding corporate behavior relating to management fraud in China. Such an understanding is important for preventing frauds and achieving better financial reporting compliance.

Design/Methodology/Approach – This study adopts a descriptive research approach using the data based on 182 punishment bulletins issued by the China Securities Regulatory Commission from 2002 to 2006. The study considers three categories of frauds (i.e., false income statements, false balance sheets, and insufficient or false disclosure) and uses these categories to describe and analyze the fraud cases.

Research findings/Insights – Based on the sample of 83 cases over the 5-year period from 2002 to 2006, this study finds that all the frauds in the sample involved the manipulation, alteration, and falsification of reported financial information. Fraud schemes often contained more than one technique to misstate financial statements, typically through overstating revenues and assets, and understating liabilities and expenses. Most of the sample companies committed several frauds simultaneously. This study also reveals that most of the frauds committed by Chinese listed companies lasted more than 2 years, with the longest being 9 years, and common intervals between the initial fraud year and the announcement year of punishment were more than 3 years, with the longest being 11 years.

Theoretical/Academic implications – This study provides an empirical analysis of fraudulent financial reporting cases committed by Chinese listed companies. These cases were rarely studied in the Western literature. This study contributes to the extant literature by providing an insight into management fraud in China. Research into fraudulent financial reporting in the largest developing economy is certainly of interest as prior research into this area is mostly based on developed economies.

Practitioner/Policy implications – The implications drawn from this study could be useful for a better understanding of the management behavior of companies in developing and transitional economies. This study has a potential to assist regulators and accounting professional bodies to set guidelines facilitating corporate compliance of regulated financial reporting.

The need for independent audit goes back to the agency theory, the theory of delegation of power and the issue of trust. Stakeholders delegate power to management to manage the business on their behalf, yet they face the risk of information asymmetry and management motivations to commit fraud. The main aim of having an independent auditor was therefore to reduce the risk of information asymmetry and fraudulent behaviour by management. Auditors are required by the International Auditing Standards to detect material fraud and error, and they are expected to have a duty of care for stakeholders. However, recently independent auditors, whether conducting private or public audit, have been scrutinised for failing to detect material fraud. There have been a lot of discussions in the literature about the role of private auditors in detecting fraud, but very little discussions about the role of public auditors in detecting fraud. This chapter will outline the difference between private audit and public audit; explain the legal liability of public auditors in relation to fraud detection; the role of public auditors in detecting fraud; and will critically review the root causes for auditors’ failure to detect fraud.

Accounting-based financial scandals caused by fraudulent financial reports negatively affect the financial markets and cause loss of confidence in investors. Financial reporting quality needs to be improved in order to build and maintain trust in financial markets. To increase the quality of financial reports, fraudulent financial reporting risks should be defined. At this point, regulators, practitioners, and researchers are in constant search.

There are improved approaches to the detection of financial reporting frauds in the literature. Many studies have been conducted on the “Fraud Triangle Theory” and the “Fraud Diamond Theory” approaches. The Fraud Triangle Theory argues that while fraudulent action is taking place in defining the elements of press, rationalization, and opportunity, the Fraud Diamond Theory approach argues that in order to achieve these three elements, the capability to carry out a fraud in individuals must be improved.

In this study, it is aimed to investigate the effect of Fraud Diamond elements on fraudulent financial reports. For the scope of the research, data of 26 companies from Manufacturing Industry enterprises operating in BORSA ISTANBUL between 2013 and 2017 were used. Financial reports of the companies are divided into two groups: (1) Fraudulent Financial Reports and (2) Non-Fraud Financial Reports. The hypotheses developed within the scope of the research were tested using the Logistic Regression analysis in IBM SPSS Statistic 20 program.

As a result of the study, it has been determined that there is a negative correlation between borrowing level, asset profitability, independent audit firm, auditor exchanges and institutionalization level, and fraudulent financial reports. It was understood that the change in assets and the size of the audit committee did not have any effect on the fraudulent financial reports.

This chapter focuses on a case study of Kareem Exchange Company and its use of big data analysis to detect and prevent fraud and suspicious financial transactions. The chapter describes the various phases of the big data analysis cycle, including discovery, data preparation, model planning, model building, operationalization, and communicating results, and how the Kareem Exchange Company team implemented each phase. This chapter emphasizes the importance of identifying the business problem, understanding the resources and stakeholders involved, and developing an initial hypothesis to guide the analysis. The case study results demonstrate the potential of big data analysis to improve fraud detection capabilities in financial institutions, leading to informed decision making and action.

This study takes the position that the concept of fraud is socially constructed. Moreover, it asks why and how different understandings of fraud have emerged. Insights from the work of Lakoff and Johnson (1999, 2003; Lakoff, 2002, 2004, 2009) are used to analyze language revealing dominant worldviews and metaphors regarding fraud. The research method is a case study (Yin, 2014), and the analytical approach used parallels the one described in O’Dwyer (2004). The research setting is a report issued by the Financial Crisis Inquiry Commission, which provides a context to study different understandings of fraud due to the report’s divided nature. The analysis reveals three alternative worldviews, representing different assumptions about reality, that are at the root of the different understandings of fraud. These worldviews also lead to the usage of different conceptual metaphors which allow the commissioners to interpret facts in a manner that supports each worldview’s assumptions. The paper also concludes by providing a nuanced and critical examination of the results of the commission concerning its understanding of fraud.

The London Interbank Offered Rate (LIBOR) is considered to be the most important interest rate in finance upon which trillions in financial contracts are decided. In 2008, it was revealed that the LIBOR traders were rigging the interest rates. Yet, there is an unresolved question that regulators and banking officials did not address in their quest to seek answers to the fraud: Were the banks under financial strain when they underreported their LIBOR rates? To answer this question, the article posits that the pressure to meet market expectations led the banks to experience financial strain. Data were gathered from 2004 to 2008 on the banks that were involved in the fraud (fraud banks) and matched with a control group of non-fraud banks. The results from a logistic regression model found sufficient statistical evidence to support the claim that fraud will be greater in banks characterized by a higher level of organizational complexity. Variables such as percent of outside directors, board members on the audit committee, and number of employees were all found to be statistically significant. These variables may offer key insights into detecting and preventing frauds in banks.

Purpose: This chapter aims to perform text analysis to investigate the academic area delimitated by economic and financial performance and money laundering.

Need for the study: The findings contribute to the body of literature by providing important insights in terms of money laundering and financial performance.

Methodology: In order to achieve the research objective, further than 640 papers were retrieved from the Web of Science from 1994 to 2022, concentrating on the most referenced documents found in the superior quartile.

Findings: The empirical findings emphasise that the article with the unique words Fraud Detection System: A Survey by Abdallah A., Maarof M. A., and Zainal A., examines a complete and systematic assessment of the concerns and obstacles that impede the performance of fraud detection systems. Furthermore, topic modelling findings highlighted the presence of four main topics: topic 1 – identified by ‘performance’, ‘firms’, ‘financial’, ‘fraud’, and ‘board’; topic 2 – described in terms of ‘fraud’, ‘accounting’, ‘evidence’, ‘audit’, and ‘research’; topic 3 – identified by ‘firms’, ‘fraud’, ‘financial’, ‘CEO’, and ‘results’ while topic 4 – identified through ‘fraud’, ‘detection’, ‘data’, ‘cost’, and ‘card’.

Practical implications: This study will act as a guide for researchers of the financial performance field to explore the scientific publications in the field of money laudering.