Financial fraud has expanded rapidly with the growth of the digital economy, evolving from conventional transactional misconduct to more complex and data-intensive forms. Traditional rule-based detection methods are increasingly inadequate for addres...
As the focus of capital market supervision, financial report fraud has shown a development trend of enormous numbers, complex transactions, and hidden means in recent years. To improve audit efficiency and reduce the dependence on non-financial data,...
This paper investigates the effect of female directors on financial fraud, focusing on the role of independent female directors and their demographics, such as experience, financial expertise, and audit committee membership. We find that independent...
In this study, we examine major cryptocurrencies, present notable fraud cases, describe fraud risks, and analyze cryptocurrency financial performance. People debate whether cryptocurrency is an investment opportunity, the new Dutch Tulip Bubble, or a...
With the rapid development of the capital market, financial fraud cases are becoming increasingly common. The evolving fraud strategies pose significant threats to financial regulation, market order, and the interests of ordinary investors. In order...
Financial fraud, considered as deceptive tactics for gaining financial benefits, has recently become a widespread menace in companies and organizations. Conventional techniques such as manual verifications and inspections are imprecise, costly, and t...
The rapid digitalization of financial services in the European Union (EU) has not only enhanced convenience and inclusion but also increased exposure to sophisticated online financial fraud. Digital financial literacy (DFL) is widely promoted as a ke...
Effective financial fraud detection requires systems that can interpret complex transaction semantics while dynamically adapting to asymmetric operational costs. We propose a hybrid framework in which a large language model (LLM) serves as an encoder...
In today’s world, financial institutions (FIs) play a pivotal role in any country’s economic growth and are vital for intermediation between the providers of investable funds, such as depositors, investors and users. FIs focus on developi...
6 September 2019
Over the past few decades, the financial system has engaged in abusive practices that meet the definition of fraud. Our objective is to compare the prevalence of psychological distress and levels of health-related quality of life according to having...
This study aims to establish a rigorous and effective model to detect enterprises’ financial statements fraud for the sustainable development of enterprises and financial markets. The research period is 2004–2014 and the sample is companies listed on...
Transaction Fraud, a type of financial operational risk, remains a major threat to financial sectors and continuously imposes devastating financial impacts. This study comprehensively reviews 41 cutting-edge publications on financial transaction frau...
2 February 2024
This article addresses the pervasive issue of fraud in financial transactions by introducing the Graph Attention Network (GAN) into graph neural networks. The article integrates Node Attention Networks and Semantic Attention Networks to construct a D...
This study examines the relevance of the Fraud Pentagon Theory in detecting fraudulent financial reporting among companies listed on the Bucharest Stock Exchange. While financial reporting is essential for informed stakeholder decisions, requiring in...
10 February 2025
The relationships within a supply chain are crucial for analyzing business transactions and can reveal significant patterns in disclosed financial data. These relationships also aid in the assessment and detection of financial fraud. Recent studies e...
Financial fraud is a serious challenge in a rapidly evolving digital economy that places increasing demands on detection systems. However, traditional methods are often limited by the dimensional information of the corporations themselves and are ins...
Online transactions, medical services, financial transactions, and banking all have their share of fraudulent activity. The annual revenue generated by fraud exceeds $1 trillion. Even while fraud is dangerous for organizations, it may be uncovered wi...
The study utilized Multiple Linear Regression along with advanced classification algorithms such as Logistic Regression, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree, and Random Forest, to detect financial statement fraud. M...
The COVID-19 pandemic had a wide-ranging impact, resulting in a global recession due to weakened purchasing power. This circumstance necessitates business organizations adapting to developments and being more conscious of the risk of financial statem...
In recent years, financial statement fraud schemes have evolved to become markedly more sophisticated and concealed, thereby posing severe threats to both social stability and economic health. Traditional detection methods, which rely primarily on fr...
The increasing sophistication of fraud has rendered rule-based fraud detection obsolete, exposing banks to greater financial risk, reputational damage, and regulatory penalties. Financial stability, customer trust, and compliance are increasingly thr...
This study systematically reviews academic research on artificial intelligence (AI) in financial fraud prevention. Employing a bibliometric approach, we analyzed 137 peer-reviewed articles published between 2015 and 2025, sourced from Scopus, Web of...
This paper proposes a new method that can identify and predict financial fraud among listed companies based on machine learning. We collected 18,060 transactions and 363 indicators of finance, including 362 financial variables and a class variable. T...
This study investigates the determinants of Fraudulent Financial Reporting (FFR) in the banking sector from 2021 to 2024 by integrating the Fraud Hexagon framework within a risk and financial management perspective. Using panel data comprising 140 ba...
The intricate relationship between financial fraud and credit risk, and their combined impact on banking stability, is a vital and under-researched aspect of financial system integrity. To fill this knowledge gap, this study embarked on a thorough bi...
The open-source structure and ease of development in the Android platform are exploited by attackers to develop malicious programs, greatly increasing malicious Android apps aimed at committing financial fraud. This study proposes a machine learning...
Financial statement fraud remains a substantial risk in environments marked by weak regulatory oversight and information asymmetry. This study develops a decision-centric framework that integrates machine learning, explainable artificial intelligence...
Detection of financial fraud remains a constant challenge due to the dynamic and highly imbalanced nature of transaction data. This paper proposes the Graph-Temporal Contrastive Transformer (GTCT) framework for modeling both structural dependencies b...
Information asymmetry is everywhere in financial status, financial information, and financial reports due to agency problems and thus may seriously jeopardize the sustainability of corporate operations and the proper functioning of capital markets. I...
This study aims to develop a better Financial Statement Fraud (FSF) detection model by utilizing data from publicly available financial statements of firms in the MENA region. We develop an FSF model using a powerful ensemble technique, the XGBoost (...
This study investigates the influence of corporate governance on reducing financial statement fraud (FSF) in Jordanian service and industrial companies listed on the Amman Stock Exchange from 2018 to 2022. To achieve this, the study employed the Bene...
Financial statement fraud is a socio-technical risk that arises from coupled organizational, informational, and regulatory processes. To address the Identification Paradox in financial fraud detection, where existing models cannot simultaneously reco...
22 January 2022
While the majority of studies on the fear of crime focus on the impact of violent and property crimes at the population level, financial fraud against senior citizens is often under-investigated. This study uses data collected from 1061 older citizen...
This study intends to identify the motives that lead to increasing or fighting the fraud risk in the Financial Statements (FSs) of industrial companies whose shares are traded in regulated and unregulated markets at the Amman Stock Exchange (ASE) bas...
Financial fraud detection is an important field in financial technology, and strong and effective machine learning (ML) models are needed to detect fraudulent transactions with high accuracy and reliability. Conventional fraud detection models, like...
Financial fraud detection is a critical application area within the broader domains of cybersecurity and intelligent financial analytics. With the growing volume and complexity of digital transactions, the traditional rule-based and shallow learning...
This article proposes a structured framework for financial statement fraud in five dimensions, nature of fraud, execution, participation, organizational impact, and environment, which are broken down into variables and subvariables to describe and an...
1 June 2025
The rising complexity of financial fraud in highly digitalized regions such as the Gulf Cooperation Council (GCC) poses challenging issues owing to class imbalance, adversarial attacks, concept drift, and explainability requirements. This paper sugge...
Reliable financial reporting is critical for maintaining market confidence and guiding stakeholders’ decision-making, yet traditional audit methods often fail to detect sophisticated fraud schemes that are hidden within large volumes of transac...
This research primarily explores the application of Natural Language Processing (NLP) technology in precision financial fraud detection, with a particular focus on the implementation and optimization of the FinChain-BERT model. Firstly, the FinChain-...
The rapid expansion of mobile financial services (MFSs) has brought about benefits in terms of financial inclusion in developing countries; however, threats have also emerged on the sides of cybersecurity and privacy. Traditional fraud-detection stra...
In recent years, financial fraud of listed internet companies has emerged one after another. Under the strategic goal of full audit coverage, the problems caused by audit failure have attracted more and more attention in China. We use the bounded rat...
This study assesses public trust in Bahrain regarding the potential of artificial intelligence (AI) to mitigate the use of cryptocurrencies in financial fraud and terrorist financing. The increasing risks associated with illicit financial activities...
The purpose of this study was to examine the potential for fraudulent financial reporting using the fraud hexagon theory factors such as stimulus (financial target, financial stability, and external pressure), capability (change in director), collusi...
This study analyzes the ability of machine-learning algorithms to detect financial statement fraud using four financial ratios as inputs: the Altman Z-Score, Beneish M-Score, Montier C-Score, and Dechow F-Score. It also evaluates whether the Wirecard...
More reliable and intelligent detection systems are required because of the rise in fraudulent activities brought on by the volume of digital financial transactions. In this work, the data used is from a publicly accessible dataset with more than a m...
The COVID-19 pandemic has provided a unique opportunity for fraudsters to innovatively swindle money through the trade of necessary goods and services. Although several incidents of financial fraud were reported during the pandemic, there is a lack o...
According to the literature, the advancement of information and communication technology (ICT) has increased individual exposure to scams, turning fraud victimization into a significant concern. While prior research has primarily focused on socio-dem...
This paper examines the uptake of AI-driven fraud detection systems among financial institutions in the UAE and Qatar, with a special focus on trust, transparency, and perceptions of fairness. Despite the promise of AI operations in identifying finan...
Financial fraud detection is critical to modern economic security, yet remains challenging due to collusive group behavior, temporal drift, and severe class imbalance. Most existing graph neural network (GNN) detectors rely on pairwise edges and corr...
of 6