Results 51 to 60 of about 131,240 (196)

A survey of outlier detection methodologies [PDF]

, 2004
Outlier detection has been used for centuries to detect and, where appropriate, remove anomalous observations from data. Outliers arise due to mechanical faults, changes in system behaviour, fraudulent behaviour, human error, instrument error or simply ...
Austin, J., Hodge, V.J.
core   +5 more sources

A systematic review and future directions for AI-driven detection of fraud patterns in SACCO transactions

Frontiers in Artificial Intelligence
Fraud in Savings and Credit Cooperative Organizations (SACCOs) remains a major challenge that undermines financial inclusion and sustainability in developing countries.
Dalton Ampumuza, Calorine Katushabe, Micheal Tamale   +2 more
doaj   +1 more source

MEFUASN: A Helpful Method to Extract Features using Analyzing Social Network for Fraud Detection [PDF]

Journal of Artificial Intelligence and Data Mining, 2019
Fraud detection is one of the ways to cope with damages associated with fraudulent activities that have become common due to the rapid development of the Internet and electronic business.
Z. Karimi Zandian, M. R. Keyvanpour
doaj   +1 more source

Cost-based Modeling for Fraud and Intrusion Detection: Results from the JAM Project [PDF]

, 2000
We describe the results achieved using the JAM distributed data mining system for the real world problem of fraud detection in financial information systems.
Chan, Philip K., Fan, Wei, Lee, Wenke, Prodromidis, Andreas L., Stolfo, Salvatore   +4 more
core   +2 more sources

An analytical assessment of credit card fraud detection techniques: Supervised, Unsupervised, and Reinforcement Learning

Вестник Дагестанского государственного технического университета: Технические науки
Objective. Bank card fraud is an increasingly serious problem for individuals, businesses and financial institutions. There is a need for effective fraud detection measures to protect consumers and businesses from financial losses. Method.
Abdourahman Djamal Djama
doaj   +1 more source

Finding Misstatement Accounts in Financial Statements Through Ontology Reasoning

IEEE Access
Finding misstatement accounts in financial statements, is a key problem of fraud detection. Potential applications include external audit, internal controls, investment decision and securities market regulation. However, most existing intelligent methods
Liming Chen, Baoxin Xiu, Zhaoyun Ding
doaj   +1 more source

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   +1 more source

Fraud Evasion Triangle: Why Can Fraud Not Be Detected

journal of accounting finance and auditing studies (JAFAS), 2019
peer ...
Ergin, Emre, Erturan, Ilkay Ejder
openaire   +2 more sources

A comparative analysis of decision trees vis-a-vis other computational data mining techniques in automotive insurance fraud detection [PDF]

, 2012
The development and application of computational data mining techniques in financial fraud detection and business failure prediction has become a popular cross-disciplinary research area in recent times involving financial economists, forensic ...
Bhattacharya, Sukanto, Gepp, Adrian, Kumar, Kuldeep, Wilson, J. Holton   +3 more
core  

Using Graph Attention Networks in Healthcare Provider Fraud Detection

IEEE Access
Healthcare fraud increases healthcare expenses for insurers, premiums for policyholders, and dissatisfaction of legitimate patients and causes severe damage to the health system. Therefore, it is critically important to address healthcare fraud detection.
Shahla Mardani, Hadi Moradi
doaj   +1 more source