Digital Commons Network^™

The Role Of Risk-Based Audit Quality In Enhancing Financial Control Efficiency And Mitigating Financial Corruption In Iraqi Banks In Light Of The Ippf 2024 Framework, Nadia Talib Salman

Muthanna Journal of Administrative and Economics Sciences

The study investigates the relationship between risk-based audit quality, financial oversight efficiency and financial corruption reduction in banks listed on the Iraq Stock Exchange in the years 2008–2025 by applying International Professional Practices Framework (IPPF) 2024. A composite risk-based audit quality index was created which included auditor independence, auditor professional qualification, frequency of audit committee meetings, and auditor presence of a formal risk committee. Thirty three hundred annual reports were processed using AI-supported structured extraction with the Gemini API, resulting in an unbalanced final panel of 303 bank-year observations from 20 banks. Random Effects and some robustness and diagnostic tests …

Random Forest Algorithm Vs. Linear Regression For Financial Performance Determinants: Evidence From Iraqi Mixed-Sector Firms, Odaiy Obaid Zeidan, Mustafa Habib Mahdi

Journal of Economics and Administrative Sciences

This paper examines the predictive factors of financial performance among Iraqi mixed-sector firms, comparing the predictive power of traditional Ordinary Least Squares (OLS) regression with the Random Forest (RF) machine learning algorithm. Utilizing annual data from 11 firms over the period 2015–2020, the study measures financial performance using Return on Assets (ROA), Return on Equity (ROE), and Return on Sales (ROS). OLS regression identified the directional relationships and p-values, whereas Random Forest evaluated predictive accuracy and modeled nonlinear relationships. The OLS results indicate that firm size, liquidity, productivity, and cash-to-asset ratio have significant positive effects on financial performance, while the …

Deepfinsec: Advancing Online Financial Fraud Detection Via Structural Similarity-Based Graph Embedding, Diksha Sharma, Robin Prakash Mathur, Manmohan Sharma

Baghdad Science Journal

The frequent use of digital technology has significantly increased the use of online transactions. Most financial activities are conducted electronically. Financial fraud involves deceiving individuals or businesses for monetary gain. The proposed graph node embedding technique, FA-Struc2vec, is applied to the financial transaction network to extract graph node features based on their structural similarity and generate node embeddings. The node embeddings serve as input to DeepFinSec, which classifies transactions into desired classes. DeepFinSec is a proposed DL-based model that is a hybrid of CNN and LSTM. CNN processes transaction data and extracts local and high-level abstract features while LSTM captures …

Programmed To Please, Optimized For Obsession, Ela Ender

Journal of Business & Technology Law

No abstract provided.

Playing Pretend: Why Indigenous Identity Fraud Demands A Crime, Olivia Meier

UBC Law Review

No abstract provided.

Usability Of Bitcoin As Currency In Türkiye: Fourier Shin Approach, İsmail Cem Özkurt, Deniz Özyakışır, Yunus Kutval

The Indonesian Capital Market Review

This paper seeks to assess the feasibility of utilizing Bitcoin as a currency within Türkiye. To achieve this, the research analyzes long-term cointegration relationships between Bitcoin and both the US Dollar and Euro, employing monthly data from November 2017 to February 2025 and utilizing the Fourier Shin cointegration test. The results of the cointegration tests, bolstered by Fourier series analysis, reveal significant long-term cointegration relationships between Bitcoin and both the USD and Euro. The DOLS analysis indicates that a 1% rise in Bitcoin leads to a 14% decrease in the USD price and a 17% increase in the Euro. These …

Static Analysis-Based Android Malware Detection (2021–2026): A Systematic Survey And Taxonomy, Ali Hussein Mohammed Ali, Musaab Riyadh Abdulrazzaq

Al-Esraa University College Journal for Engineering Sciences

Android malware is not only increasing in size and sophistication but is also a challenge to be detected on a large scale. Static analysis is popular due to its ability to detect malware without running applications or tracing run-time events. However, features, datasets, labeling methods, and assessment methodology differ, which makes studying performance difficult. This is a systematic study of 78 peer reviewed articles written between 2021 and 2026 regarding the Android malware detection by static analysis. In each of the studies, the current survey cover the following feature source, feature representation and engineering, learning paradigms, datasets and labeling methods, …

A Systematic Literature Review Of Fraud Research Prevalence, Mohammed Khojah, Nawaf Alzahrani, Saed Eidow, Jawad Alamri, Ibrahim Albassam, Muath Alghamdi, Aseel Atawi, Osama Bayunus, Osama Alhodaly, Osama Rabie

Journal of King Abdulaziz University: Computing and Information Technology Sciences

Background: Fraud is a pervasive worldwide problem that is evolving rapidly along with the technological advances and causing significant financial losses in a variety of industries. Traditional detection techniques often fall short in the face of more complex and digitalized fraud schemes. The pressing need for more intelligent detection systems is what motivated this review, which attempts to systematically assess the body of research on fraud detection and pinpoint dominant fraud sectors, types, and methods. Methods: This study employed a Systematic Literature Review (SLR) approach to comprehensively assess the current landscape of fraud detection research across multiple domains. …

Neutrosemigroups Generated By Upside-Down Logic, Aykut Emniyet, Memet S¸Ahin

Neutrosophic Sets and Systems

No abstract provided.

Agentic Ai Approach For Online Financial Fraud Detection, Shadi Saleh, Kelechi Osuji, Wolfram Hardt

Al-Farahidi Expert Systems Journal

As digital payment systems facilitate billions of transactions every day, there is a high probability of fraudulent activities in these systems. Traditional fraud detection systems, including rule-based systems and machine learning-based systems, have three major limitations: lack of explainability in terms of regulatory requirements, lack of contextual reasoning in terms of rare behavioral patterns, and lack of interaction with human experts in fraud analysis. This paper proposes a novel agentic framework in fraud detection systems by integrating Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) in context-aware reasoning based on historical transaction evidence. The framework is designed as a system …

Evaluating Legal Frameworks For The Protection Of Consumers Of Digital Financial Services: Global Trends And Their Significance For Vietnam, Ha Son Nguyen, Lanh Dinh Cao, Nguyen Dinh Phan

International Journal on Consumer Law and Practice

The development of digital financial services (DFS) in the context of global digital transformation poses fundamental challenges for the legal framework for consumer protection, particularly in developing countries such as Vietnam. This article argues that the sectoral approach currently adopted in Vietnam, with rules dispersed across various specialized statutes, has created a structurally significant legal gap, a lack of consistency in protection standards, and limitations on effective coordination among regulatory authorities. It thereby undermines the law’s capacity to protect consumers in the highly cross-sectoral environment of digital finance.

Through an analytical and comparative approach that draws on the experiences of …

A Review On Credit Card Electronic Fraud Detection Methodologies, Titilayo Mary Sayikanmi, Ibrahim Adepoju Adeyanju, Bolaji Abigail Omodunbi

Mansoura Engineering Journal

Credit card fraud remains a critical and escalating challenge within the global financial ecosystem, driving substantial annual losses and necessitating the continuous evolution of detection methodologies. This paper presents a systematic literature review, conducted via the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework, which comprehensively analyzes the state-of-the-art in electronic credit card fraud detection. Through a rigorous examination of 49 high-quality studies, this review maps the methodological evolution from traditional rulebased systems and statistical models to advanced artificial intelligence techniques, including machine learning, deep learning, and graph-based approaches. The analysis reveals that while individual methods possess distinct advantages …

Online Shopping Non-Adoption In South Africa: A Distrust-Centric Framework Integrating Social Exchange, Trust Transfer, And Social Presence Theories, Cleopatra Moipone Matli, Jeevarathnam P. Govender

Journal of Marketing and Consumer Behaviour in Emerging Markets

Online shopping non-adoption remains critically underexplored, especially in emerging markets. Addressing this gap, the authors develop and test a distrust-centric framework that applies the inhibitory logic of social exchange, trust transfer, and social presence theories to explain pre-emptive avoidance. Focusing on South Africa, where only 18.16% of the population engage in e-commerce, data was collected from 414 consumers who have never shopped online. Structural equation modelling reveals that perceived lack of reciprocity directly increases the intention of non-adoption. Moreover, distrust in online payment systems transfers to broader channel scepticism, which in turn drives avoidance. Perceived lack of social presence further …

Classification Of Phishing Data Using Hybrid Mi-An Feature Selection Method, Damodar Patel, Amit Kumar Saxena, Wutiphol Sintunavarat, Abhishek Dubey

Baghdad Science Journal

Web phishing attacks have been continually evolving over the past few years, which has led customers to lose their trust in online services and e-commerce. To identify phishing data, a variety of methods and systems based on a blacklist of phishing websites are used. However, the rapid development of technology has given rise to increasingly complex techniques for creating user-attracting websites. Therefore, current blacklist-based techniques are unable to identify the recently launched phishing data, such as zero-day phishing websites. Machine learning techniques have been used in several recent studies to detect phishing data and function as an early warning system …

Girls On Screens And Boys In The Streets: Afrobeats Dance, Gender, And Waithood In Lagos, Nigeria, Gali Kinkulkin, Moshe Morad, Lynn Schler

Journal of International Women's Studies

The global success of the musical genre of Afrobeats has generated substantial scholarly interest in the experiences of singers and musicians within the industry. Scholars of this genre have examined an array of topics, including cultural identity, gender disparities, socioeconomic impact, and the global music industry. However, few studies focus on the experiences of Afro dancers despite the critical role of dance in the genre’s international popularity; those that do centralise dance concentrate primarily on how women dancers navigate an industry that both empowers and objectifies women. This study departs from these earlier studies by examining the lived experiences of …

Policing The Perils Of Online Dating: Harassment, Scams, Dark Patterns, Monopoly, And Perverse Incentives, Kevin Chamow

The University of Cincinnati Intellectual Property and Computer Law Journal

No abstract provided.

Fraud Protection - How To Protect Your Practice From Financial Fraud, Jennifer Nieto

Virginia Dental Journal

No abstract provided.

Va Dent J July, August And September 2019

Virginia Dental Journal

No abstract provided.

The Impact Of Quantum Computing And Distributed Ledger Technology On Accounting/Auditing/Finance Systems, Ulingeta O. L. Mbamba

Business Management Review

The integration of Quantum Computing (QC) and Distributed Ledger Technology (DLT) is poised to fundamentally reshape modern accounting by transforming how financial data is processed, secured, and verified. QC, utilising qubits, will exponentially enhance data analytics, risk assessment, and real-time financial forecasting, accelerating complex auditing tasks far beyond the capabilities of classical systems. In parallel, DLT, such as blockchain, provides a decentralised, immutable record of transactions, significantly increasing transparency and trust. This synergy may enable real-time analysis, continuous auditing, and intelligent automation, converting traditional static, centralised processes into dynamic, transparent ecosystems. Together, this convergence may redefine accounting, auditing, and finance, …

Patient Privacy In The Digital Age: Reimagining Health Data Laws To Protect Patients’ Constitutional Rights, Adriana Almeida Mehtani

Barry Law Review

No abstract provided.

The Impact Of Forensic Accounting On The Effectiveness Of Fraud Detection In Private-Sector Banking And Merchandising Companies: Evidence From Sulaymaniyah City, Kurdistan Region, Iraq, Barham Khalid Hassan

Journal of Economics and Administrative Sciences

This study examines the impact of forensic accounting techniques, challenges, and accountants' skills on fraud detection effectiveness in the private sector of Sulaymaniyah City, Kurdistan Region of Iraq. The study employed a quantitative research design, with preliminary semi-structured interviews conducted to inform questionnaire development. In the qualitative phase, purposive sampling was used to interview eight forensic accountants with experience handling multiple fraud cases in Sulaymaniyah. Insights from these interviews guided the creation of a structured questionnaire, which was subsequently distributed to Seventy-four accounting professionals from private banks and merchandising firms for the main data collection. Data were analysed using SPSS …

Clawing Back Fraudulent Profits—Investor Protection Or Regulatory Overreach: The Disgorgement Dilemma In Securities Law, Jessica Sun

The Journal of Business, Entrepreneurship & the Law

This comment explores the legal complexities surrounding the Securities and Exchange Commission’s (SEC) use of disgorgement as an enforcement tool, specifically addressing the tension between investor protection and regulatory overreach. Sun examines the evolution of disgorgement from a court-created equitable remedy to a power formally codified by the National Defense Authorization Act of 2021, while highlighting the significant limitations imposed by Supreme Court rulings in Kokesh v. SEC and Liu v. SEC. The comment centers on a current circuit split between the Second Circuit’s decision in SEC v. Govil—which requires a showing of "pecuniary harm" to victims before awarding disgorgement—and …

Crossed Wires: How Current Federal Laws And Regulations Are Inadequate At Protecting Consumers From Sophisticated Wire Fraud Schemes, Emily Brafman

University of Miami Business Law Review

The shift to digital banking has redefined the financial services industry, allowing consumers to conduct everyday transactions, such as wire transfers, at the touch of a button. However, this convenience comes at a steep price: as digital banking becomes the norm, consumers are increasingly exploited by sophisticated cybercriminals, enabled by a legal system that is ill-equipped to handle modern phishing and wire fraud schemes, ultimately draining consumer accounts. Unfortunately, existing protective measures, such as the Electronic Funds Transfer Act (EFTA) and the Uniform Commercial Code (UCC), have proven to be outdated and inadequate to address the unique risks posed by …

A Tale Of Two Credits: The Post-Nestlé Alien Tort Statute And Carbon Credit Externalities, Stephanie Mao

Northwestern University Law Review

As companies increasingly embrace carbon-neutrality commitments, many rely on the voluntary carbon market to offset their emissions rather than reduce them directly. Regulatory and consumer scrutiny has focused on the widespread use of “phantom” carbon credits, i.e., credits that fail to produce meaningful climate benefits. But less attention has been paid to what this Note terms “colonial” carbon credits: those that may technically reduce emissions but do so at the expense of communities abroad. These projects may contribute to land dispossession, human rights abuses, and threats to public and environmental health. Yet, current regulatory and legal frameworks, with their focus …

Can Ai Fix Anti-Money Laundering? The Case For Federated Intelligence In Financial Crime Prevention, Matthias Connelly

Student Journal of Information Privacy Law

The global anti-money laundering (AML) regime is failing. Trillions of dollars are laundered each year, yet governments detect only a fraction of that activity, even as financial institutions spend hundreds of billions on compliance. In the United States, AML regulation has evolved from a retrospective, prosecution-oriented framework into an expansive, preventative regime that measures inputs rather than enforcement outcomes. Although artificial intelligence has demonstrated potential to improve detection, firm-siloed AI systems introduce substantial financial, technological, and systemic risks, including prohibitive development costs, data- privacy constraints, and market concentration among third-party service providers. This Article argues that federated learning offers a …

Combatting Authorized Push Payment Fraud: Which Regulatory Approach Should The United States Adopt?, Garrett S. Grewal

North Carolina Banking Institute

No abstract provided.

Abuse Of Contract: A Proposal For A New Cause Of Action, Miriam A. Cherry

William & Mary Law Review

With the growth of online commerce and the platform economy, many companies are including provisions in their online terms and conditions that extend far beyond what reasonable consumers would expect. Some terms and conditions purport to bind customers to separate contracts in future transactions that have little to do with the first contract. Other boilerplate purports to cover family members of the customer who created an account. Some retailers have argued that people shopping in their brick-and-mortar stores are subject to terms and conditions because those shoppers had at some point previously created an online account. For example, Disney argued …

Money Over Everything: Reimagining Health Care Enforcement, Jacob T. Elberg

Missouri Law Review

Annual press releases from the Department of Justice trumpet billions of dollars in annual recoveries and optimism that its health care enforcement regime deters even more fraud than it addresses. Yet DOJ’s consistent recoveries can be seen as a sign that fraud continues unabated. While some scholars have questioned the deterrent value of the government’s model of enforcement through civil settlements, little attention has been given to what may be the most important aspect of DOJ’s effort—its focus on money both as the sole measure of harm and the sole means of deterrence.

Leveraging Blockchain Technology In Mining Supply Chain Management: Vietnam Coal Mining Case Study, Thu Hang Nguyen, Nguyen Trung Tuan, Hong Anh Le

Journal of Sustainable Mining

The global economy heavily relies on the mining industry for essential resources such as coal, oil, gas, and metal ores. However, the intricate nature of mining operations poses significant challenges in supply chain management (SCM). This research investigates how blockchain technology can address these challenges within mining supply chain management (MSCM). Through a systematic review of existing research and projects, a conceptual blockchain model is proposed to improve mining supply chains’ transparency, traceability, efficiency, and sustainability, specifically focusing on coal supply chain management in Vietnam. The model integrates distributed ledgers, smart contracts, IoT devices, identity management, and consensus mechanisms to …

Applying Total Quality Management And Auditor Size Theories To Audit Quality: Evidence From Tanzanian Auditing Firms, Freddy Chaula, Henry Zeno Chalu, Paul Ambege

Business Management Review

Amid mixed global findings on the determinants of audit quality, particularly in emerging markets, the role of engagement team competence and audit firm size remains underexplored. This study investigates the relationship between engagement team competence, audit firm size, and audit quality in Tanzanian auditing firms. The hypotheses were tested using PLS-SEM based on data obtained from a cross-sectional survey of 147 Tanzanian audit partners. Audit firm size (β = 0.309, p < 0.01) and engagement team competence (β = 0.567, p < 0.01) were found to have significant positive effects on audit quality. These results suggest that audit quality is significantly enhanced by audit firm size and engagement team competence, thus supporting total quality management and auditor size theories. These findings highlight the need for regulators to strengthen auditor competence and to support the growth of small auditing firms, thereby enhancing their capacity, resources, and the overall audit quality. For auditing firms, the findings underscore the need to develop engagement team competence through initiatives such as professional training, mentoring, and knowledge-sharing programs. Additionally, firms should expand their capacity to strengthen audit quality. While focused on the Tanzanian context, the findings offer broader insights for improving audit quality in developing economies.