Results 1 to 10 of about 4,440,100 (389)

Enhancing Fraud Detection in Banking With Deep Learning: Graph Neural Networks and Autoencoders for Real-Time Credit Card Fraud Prevention

IEEE Access
Under the umbrella of artificial intelligence (AI), deep learning enables systems to cluster data and provide incredibly accurate results. This study explores deep learning for fraud detection, utilizing Graph Neural Networks (GNNs) and Autoencoders to ...
Fawaz Khaled Alarfaj, Shabnam Shahzadi
doaj   +2 more sources

A machine learning based credit card fraud detection using the GA algorithm for feature selection

Journal of Big Data, 2022
The recent advances of e-commerce and e-payment systems have sparked an increase in financial fraud cases such as credit card fraud. It is therefore crucial to implement mechanisms that can detect the credit card fraud.
Emmanuel Ileberi, Yanxia Sun, Zenghui Wang   +2 more
doaj   +2 more sources

Healthcare insurance fraud detection using data mining. [PDF]

BMC Med Inform Decis Mak
Healthcare programs and insurance initiatives play a crucial role in ensuring that people have access to medical care. There are many benefits of healthcare insurance programs but fraud in healthcare continues to be a significant challenge in the ...
Hamid Z, Khalique F, Mahmood S, Daud A, Bukhari A, Alshemaimri B.   +5 more
europepmc   +2 more sources

Assessing and Improving Data Integrity in Web-Based Surveys: Comparison of Fraud Detection Systems in a COVID-19 Study [PDF]

JMIR Formative Research
BackgroundWeb-based surveys increase access to study participation and improve opportunities to reach diverse populations. However, web-based surveys are vulnerable to data quality threats, including fraudulent entries from ...
Stephen Bonett, Willey Lin, Patrina Sexton Topper, James Wolfe, Jesse Golinkoff, Aayushi Deshpande, Antonia Villarruel, José Bauermeister   +7 more
doaj   +2 more sources

Hyperparameter Optimization with Genetic Algorithms and XGBoost: A Step Forward in Smart Grid Fraud Detection. [PDF]

Sensors (Basel)
This study provides a comprehensive analysis of the combination of Genetic Algorithms (GA) and XGBoost, a well-known machine-learning model. The primary emphasis lies in hyperparameter optimization for fraud detection in smart grid applications.
Mehdary A, Chehri A, Jakimi A, Saadane R.   +3 more
europepmc   +2 more sources

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
semanticscholar   +3 more sources

Financial Fraud Detection Using Value-at-Risk With Machine Learning in Skewed Data

IEEE Access
The significant losses that banks and other financial organizations suffered due to new bank account (NBA) fraud are alarming as the number of online banking service users increases.
Abdullahi Ubale Usman, Sunusi Bala Abdullahi, Yu Liping, Bayan Alghofaily, Ahmed S. Almasoud, Amjad Rehman   +5 more
doaj   +2 more sources

Role of analytical testing for food fraud risk mitigation – A commentary on implementation of analytical fraud testing

Current Research in Food Science, 2021
Food fraud is of high concern to the food industry. A multitude of analytical technologies exist to detect fraud. However, this testing is often expensive.
Francis Butler, Niels Lucas Luijckx, Hans J.P. Marvin, Yamine Bouzembrak, Vahid Mojtahed   +4 more
doaj   +1 more source

Transformative Leadership, Locus Of Control On Fraud Detection And Environmental Performance

Jurnal Akuntansi, 2022
This study aims to determine the effect of transformative leadership, and locus of control on fraud detection with environmental performance as a moderating variable.
Agus Bandiyono
doaj   +1 more source

Analysis Of Factors Influencing The Occupation Of Fraud Detection

Jurnal Akuntansi, 2023
This study analyzes the influence of Forensic Accounting, Investigative Audit Capability and Auditor Experience on Fraud Detection in the Perspective of BPK and Central BPKP Auditors.
Gen Norman Thomas, Lely Indriaty
doaj   +1 more source