Results 21 to 30 of about 6,037 (259)

FraudGraph-X: A Multimodal Graph Neural Framework for Behavioral Fraud Detection [PDF]

ITM Web of Conferences
The complexity and volume of transactional data has expanded due to the rapid growth of digital financial services, which has opened the door to new types of sophisticated fraud.
Yatoo Nuzhat Ahmad, Jishnu M., John Josiah, Babu Ajesh   +3 more
doaj   +1 more source

A Survey of Automated Financial Statement Fraud Detection with Relevance to the South African Context

South African Computer Journal, 2020
Financial statement fraud has been on the increase in the past two decades and includes prominent scandals such as Enron, WorldCom and more recently in South Africa, Steinhoff.
Wilson Tsakane Mongwe, Katherine Mary Malan   +1 more
doaj   +1 more source

Intelligent Fraud Detection in Financial Statements Using Machine Learning and Data Mining: A Systematic Literature Review

IEEE Access, 2022
Fraudulent financial statements (FFS) are the results of manipulating financial elements by overvaluing incomes, assets, sales, and profits while underrating expenses, debts, or losses.
Matin N. Ashtiani, Bijan Raahemi
doaj   +1 more source

FRAUD PENTAGON IN DETECTING FINANCIAL STATEMENT FRAUD

International Journal of Economic Integration and Regional Competitiveness
Objective: This study aims to analyze the influence of the fraud pentagon elements on financial statement fraud in manufacturing companies within the food and beverage sub-sector listed on the Indonesia Stock Exchange (IDX) during the 2016–2020 period. Method: A quantitative approach was employed using secondary data derived from company annual reports.
Fityan Izza Noor Abidin, Riza Arista Firana, Sarwenda Biduri   +2 more
openaire   +2 more sources

Finding Misstatement Accounts in Financial Statements Through Ontology Reasoning

IEEE Access
Finding misstatement accounts in financial statements, is a key problem of fraud detection. Potential applications include external audit, internal controls, investment decision and securities market regulation. However, most existing intelligent methods
Liming Chen, Baoxin Xiu, Zhaoyun Ding
doaj   +1 more source

Powerful transformations: The experiences of higher education teaching staff who were first‐generation university students

British Educational Research Journal, EarlyView.
Abstract Historically, a university education has been seen primarily as a route for the middle classes to achieve professional qualifications while structural barriers have served to restrict entry to individuals from particular demographics. First‐generation students (FGS), often with low socio‐economic backgrounds, face multiple barriers to Higher ...
Helen Williams, Ellen‐Alyssa Gambles
wiley   +1 more source

AI Driven Fraud Detection Models in Financial Networks: A Comprehensive Systematic Review

IEEE Access
Rapid advancements in digital innovation and globalization has significantly increased the complexity of financial networks, making them more vulnerable to fraud.
Nusrat Jahan Sarna, Farzana Ahmed Rithen, Umme Salma Jui, Sayma Belal, Al Amin, Tasnim Kabir Oishee, A. K. M. Muzahidul Islam   +6 more
doaj   +1 more source

From Traditional Methods to Machine Learning: The Evolution of Fraud Detection in Auditing with New Technologies [PDF]

پژوهش‌های تجربی حسابداری
Fraudulent financial reporting is a global issue with significant negative consequences for all stakeholders. However, detecting fraud remains challenging due to its subjective nature.
Zahra Taheri, Saeideh Nazari, Milad Samavat   +2 more
doaj   +1 more source

The Degradation of Access‐Based Business Models: Customer Misbehavior and Shared Mobility

Business Strategy and the Environment, EarlyView.
ABSTRACT Access‐based services are considered one of the strategies to embed sustainability in business models. Yet, because the evolution of these business models has been overlooked, we do not know whether their promise to create triple value is sustained.
Andres Camacho, Carmen Valor
wiley   +1 more source

Cost-sensitive random forest with adaptive threshold optimization for imbalanced financial fraud detection

Frontiers in Artificial Intelligence
BackgroundFinancial transaction fraud detection is a challenging binary classification problem characterized by severe class imbalance, rare fraudulent cases, and asymmetric misclassification costs.
Jafar Ali, Rahman Shafique, Daniel Gavilanes, Daniel Gavilanes, Daniel Gavilanes, Daniel Gavilanes, Manuel Masias Vergara, Manuel Masias Vergara, Manuel Masias Vergara, Isabel de la Torre Diez, Dae Wan Kim   +10 more
doaj   +1 more source