Results 51 to 60 of about 4,440,100 (389)

The Evaluation of Distributed Topic Modeling Paradigms for Detection Of Fraudulent Insurance Claims In Healthcare Forum [PDF]

MATEC Web of Conferences
Healthcare fraud is the deliberate misrepresentation of the healthcare industry for the purpose of obtaining unjustified financial gain. There are many different types of healthcare fraud, which can influence patients, healthcare professionals, insurers,
Subbarayudu Yerragudipadu, Vijendar Reddy Gurram, Sandhya Meesala, Bhargavi Jammi, Abhilash P.K., Pushkarna Gaurav   +5 more
doaj   +1 more source

Deep Learning for Credit Card Fraud Detection: A Review of Algorithms, Challenges, and Solutions

IEEE Access
Deep learning (DL), a branch of machine learning (ML), is the core technology in today’s technological advancements and innovations. Deep learning-based approaches are the state-of-the-art methods used to analyse and detect complex patterns in large ...
Ibomoiye Domor Mienye, N. Jere
semanticscholar   +1 more source

Spectrum-based deep neural networks for fraud detection

, 2017
In this paper, we focus on fraud detection on a signed graph with only a small set of labeled training data. We propose a novel framework that combines deep neural networks and spectral graph analysis. In particular, we use the node projection (called as
Li, Jun, Lu, Aidong, Wu, Xintao, Yuan, Shuhan   +3 more
core   +1 more source

Trauma‐Informed Practice in Welfare‐to‐Work and Employment Services: A Scoping Review

Australian Journal of Social Issues, EarlyView.
ABSTRACT There is increasing recognition within welfare services, including employment services, that many participants may have histories of trauma. Research suggests that experiences of trauma not only impact individuals' psychosocial health but also vocational elements such as job performance, employability, career progression, and financial ...
Emily Corbett, Michael McGann, Mark Considine, René Rejón   +3 more
wiley   +1 more source

Comparative analysis of binary and one-class classification techniques for credit card fraud data

Journal of Big Data, 2023
The yearly increase in incidents of credit card fraud can be attributed to the rapid growth of e-commerce. To address this issue, effective fraud detection methods are essential. Our research focuses on the Credit Card Fraud Detection Dataset, which is a
Joffrey L. Leevy, John Hancock, Taghi M. Khoshgoftaar   +2 more
doaj   +1 more source

Financial Fraud Detection Based on Machine Learning: A Systematic Literature Review

Applied Sciences, 2022
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 time ...
Abdulalem Ali, Shukor Abd Razak, S. H. Othman, T. Eisa, Arafat Al-dhaqm, Maged Nasser, Tusneem A. Elhassan, H. Elshafie, Abdulgbar Saif   +8 more
semanticscholar   +1 more source

Electronic fraud detection in the U.S. Medicaid Healthcare Program: lessons learned from other industries [PDF]

, 2011
It is estimated that between $600 and $850 billion annually is lost to fraud, waste, and abuse in the US healthcare system,with $125 to $175 billion of this due to fraudulent activity (Kelley 2009).
Hillegersberg, Jos van, Müller, Roland M., Thornton, Dallas, Travaille, Peter   +3 more
core   +3 more sources

‘People Need to Understand That They Are Stealing From Their Neighbours’: A Critical Media Analysis of the Representations and Resistance Throughout the Robodebt Scheme

Australian Journal of Social Issues, EarlyView.
ABSTRACT The Robodebt scheme issued thousand‐dollar debts to an estimated half a million people who had received social security. The debts were largely inaccurate and illegal, with the aim of improving the federal government's budget. The 2023 Royal Commission into the Robodebt Scheme found that the stigmatising political and public language about ...
Ella Kruger, Phillipa Evans
wiley   +1 more source

The Impact of Insurance Fraud Detection Systems [PDF]

The purpose of this paper is to characterize the impact of fraud detection systems on the auditing procedure and the equilibrium insurance contract, when a policyholder can report a loss that never occurred.
Jörg Schiller
core   +3 more sources

A Deep Learning Ensemble With Data Resampling for Credit Card Fraud Detection

IEEE Access, 2023
Credit cards play an essential role in today’s digital economy, and their usage has recently grown tremendously, accompanied by a corresponding increase in credit card fraud.
Ibomoiye Domor Mienye, Yanxia Sun
semanticscholar   +1 more source