Results 41 to 50 of about 131,240 (196)

What Is Fraud and Who Is Responsible? [PDF]

, 2006
Research shows that fraudulent activity affecting the financial statements is more prevalent than ever despite the increased attention devoted to the prevention and detection of fraud by companies and professional accountants.
Akers, Michael D., Gissel, Jodi L.
core   +1 more source

Intelligent Financial Fraud Detection Practices: An Investigation

, 2015
Financial fraud is an issue with far reaching consequences in the finance industry, government, corporate sectors, and for ordinary consumers. Increasing dependence on new technologies such as cloud and mobile computing in recent years has compounded the
B Bai, B Hoogs, C Holton, C Whitrow, CA Paasch, D Sánchez, D Zhang, E Duman, E Kirkos, E Ngai, FH Glancy, HC Koh, I Yeh, J Pinquet, JE Sohl, JT Quah, L Bermúdez, M Cecchini, M Jans, P Ravisankar, S Bhattacharyya, S Panigrahi, S Viaene, SL Humpherys, V Vatsa, W Zhou, W-S Yang   +26 more
core   +1 more source

FraudDroid: Automated Ad Fraud Detection for Android Apps [PDF]

, 2018
Although mobile ad frauds have been widespread, state-of-the-art approaches in the literature have mainly focused on detecting the so-called static placement frauds, where only a single UI state is involved and can be identified based on static ...
Developers Android, Developers Android, Developers Android, Developers Android, Freier Anne, Jones Brandon, Liu Bin, MARIA, McCoy Damon, Project The Bro, Springborn Kevin, Stevens Ryan, Wang Haoyu   +12 more
core   +2 more sources

Fraud Detection in Payments Transactions: Overview of Existing Approaches and Usage for Instant Payments

Complex Systems Informatics and Modeling Quarterly, 2019
Financial industries are undergoing a digital transformation of their products, services, overall business models. Part of this digitalization in banking aims at automating most of the manual work in payment handling and integrating the workflows of ...
Alexander Diadiushkin, Kurt Sandkuhl, Alexander Maiatin   +2 more
doaj   +1 more source

Design The Modified Multi Practical Swarm Optimization To Enhance Fraud Detection

Ibn Al-Haitham Journal for Pure and Applied Sciences, 2020
     Financial fraud remains an ever-increasing problem in the financial industry with numerous consequences. The detection of fraudulent online transactions via credit cards has always been done using data mining (DM) techniques.
Zainab Khamees Muter, Abeer Tariq Molood
doaj   +1 more source

Medicare Fraud Detection

International Research Journal of Computer Science
This paper explores the development of an intelligent Medicare Fraud Detection System using advanced machine learning and deep learning models. The primary objective is to minimize fraudulent healthcare claims and enhance the efficiency of public fund allocation. The proposed system places a strong emphasis on explainability, transparency, and fairness
Retika D, Vani N
openaire   +1 more source

Financial Fraud Detection

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Detection of financial fraud is now a cause of major concern in the financial and banking industry because fraud techniques are becoming highly sophisticated. Classical rule- based systems are generally ineffective in detecting complex patterns of fraud, which call for more complex machine learning and artificial intelligence processes.
Sai Chandana Y, Rama Devi DP, Neethu Jimmy Joy, Neelam Sanjeev Kumar   +3 more
openaire   +2 more sources

Multi-view graph neural network for fraud detection algorithm

Tongxin xuebao, 2022
Aiming at the problem that in the field of fraud detection, imbalance labels and lack of necessary connections between fraud nodes, resulting in fraud detection tasks not conforming to the hypothesis of homogeneity of graph neural networks, multi-view ...
Zhuo CHEN, Miao ZHU, Junwei DU
doaj   +2 more sources

A Review of Artificial Intelligence for Financial Fraud Detection

Applied Sciences
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 addressing
Haiquan Yang, Zarina Shukur, Shahnorbanun Sahran   +2 more
doaj   +1 more source

The Many Faces of Link Fraud

, 2017
Most past work on social network link fraud detection tries to separate genuine users from fraudsters, implicitly assuming that there is only one type of fraudulent behavior. But is this assumption true?
Beutel, Alex, Faloutsos, Christos, Lamba, Hemank, Shah, Neil   +3 more
core   +1 more source