Results 71 to 80 of about 2,431 (186)

Institutional Logics as a Resource and Risk: Logic Deviance and Categorical Penalties in US Community Banks

open access: yesJournal of Management Studies, EarlyView.
Abstract Can institutional logics be damaging for the same category of actors they are presumed to benefit? Can firms prevent or reduce this detrimental effect? This study integrates the institutional logics perspective with category research to examine these questions in the context of community banks.
Stephen J. Smulowitz   +2 more
wiley   +1 more source

Neural data mining for credit card fraud detection

open access: yes, 2010
The prevention of credit card fraud is an important application for prediction techniques. One major obstacle for using neural network training techniques is the high necessary diagnostic quality: Since only one financial transaction of a thousand is ...
Brause, Rüdiger W.   +2 more
core  

Machine Learning-Based Cyber Fraud Detection: A Comparative Study of Resampling Methods for Imbalanced Credit Card Data

open access: yesApplied Sciences
The prevalence of online transactions and extensive adoption of credit card payments have contributed to the escalation of credit card cyber fraud in modern society.
Eyad Btoush   +3 more
doaj   +1 more source

When Business Breaks the Rules: The Value of a Criminology‐Informed “Organizational” Perspective for the Regulation of White‐Collar and Corporate Crimes

open access: yesRegulation &Governance, EarlyView.
ABSTRACT This article argues that if the aspiration is to enhance regulatory and governance responses to white‐collar and corporate crimes, consideration of the organization of these offending behaviors must be central to the scholarly, practice, and policy discussion.
Nicholas Lord, Michael Levi
wiley   +1 more source

Real-time credit card fraud detection

open access: yes, 2019
Credit card fraud is growing along with the development of technology in today’s world. Hundreds of researches have been made in the past for more than four decades and still, the problem is critical, affecting large financial and banking companies.

core   +1 more source

Fraud Detection in Credit Card System Using Web Mining [PDF]

open access: yes, 2020
: Now a day the usage of credit cards has dramatically increased. As credit card becomes the most popular mode of payment for both online as well as regular purchase, cases of fraud associated with it are also rising.
Nimesh Patel   +3 more
core  

Enhancing credit card fraud detection: the impact of oversampling rates and ensemble methods with diverse feature selection

open access: yesРадіоелектронні і комп'ютерні системи
The subject matter of this article is enhancing credit card fraud detection systems by exploring the impact of oversampling rates and ensemble methods with diverse feature selection techniques.
Mohamed Akouhar   +3 more
doaj   +1 more source

A novel approach for credit card fraud transaction detection using deep reinforcement learning scheme [PDF]

open access: yesPeerJ Computer Science
Online transactions are still the backbone of the financial industry worldwide today. Millions of consumers use credit cards for their daily transactions, which has led to an exponential rise in credit card fraud.
Abdul Qayoom   +7 more
doaj   +2 more sources

Governing Credit in the Digital Age: Public Perceptions and Engagement in China's Credit Systems

open access: yesRegulation &Governance, EarlyView.
ABSTRACT There is a global trend toward embedding personal credit systems and their scoring mechanisms within broader governance infrastructures. A prominent and controversial example is China's Social Credit System (SCS), which plays a central role in the country's data‐driven financial and social governance.
Mo Chen   +2 more
wiley   +1 more source

Enhanced stacking classifiers system for credit card fraud detection

open access: yes, 2022
Credit cards have been an option for payment method by many people nowadays. Despite that, without handling the usage of credit cards carefully, it may lead to undesirable incidents such as credit card fraud activities.
Ishak, Nur Amirah
core  

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