Results 41 to 50 of about 132,324 (298)

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

open access: yes, 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   +3 more
core   +3 more sources

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

open access: yesJournal 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   +2 more
doaj   +1 more source

B/ordering and healthcare access for migrants with precarious status: The role of healthcare workers in counteracting restrictive policies

open access: yesAmerican Journal of Community Psychology, EarlyView.
Abstract In Canada, precarious migration is largely invisibilized. Nonetheless, b/ordering greatly affects people's realities by limiting access to social rights. In Quebec, migrants with precarious status (MPS) do not have access to healthcare, although Quebec has a “universal” healthcare coverage.
Émilie Pigeon‐Gagné   +3 more
wiley   +1 more source

A Credit Card Fraud Detection Method Based on Mahalanobis Distance Hybrid Sampling and Random Forest Algorithm

open access: yesIEEE Access
Currently, the continuous expansion of the credit card business and the increasingly fierce competition have made all kinds of fraud risks in the overall credit card business the biggest threat.
Zhichao Xie, Xuan Huang
doaj   +1 more source

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

open access: yesAustralian 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]

open access: yes
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

The Cost of the National Disability Insurance Scheme: Australia's Print‐Media Discourse

open access: yesAustralian Journal of Social Issues, EarlyView.
ABSTRACT This paper examines the way that Australian newspapers have framed the cost of the National Disability Insurance Scheme (NDIS). Introduced in 2013, the NDIS represented a major change in Australia's disability support policy, moving for the first time to a nationwide universal insurance model.
Meera Chinnappa   +2 more
wiley   +1 more source

Design The Modified Multi Practical Swarm Optimization To Enhance Fraud Detection

open access: yesIbn 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

Spectrum-based deep neural networks for fraud detection

open access: yes, 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   +3 more
core   +1 more source

Medicare Fraud Detection

open access: yesInternational 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

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