Neural Network Predictor for Fraud Detection: A Study Case for the Federal Patrimony Department

2012 ◽  
Author(s):  
Antonio Serrano ◽  
João Costa ◽  
Carlos Cardonha ◽  
Ararigleno Fernandes ◽  
Rafael Sousa Júnior
Keyword(s):  
Neural Network ◽  
Fraud Detection ◽  
Study Case

scholarly journals Tax Fraud Detection through Neural Networks: An Application Using a Sample of Personal Income Taxpayers

2019 ◽  
Vol 11 (4) ◽  
pp. 86 ◽  
Author(s):  
César Pérez López ◽  
María Delgado Rodríguez ◽  
Sonia de Lucas Santos
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Income Tax ◽  
Fraud Detection ◽  
Personal Income ◽  
Personal Income Tax ◽  
Tax Returns ◽  
The Neural Networks ◽  
Tax Fraud ◽  
Efficiency Rate

The goal of the present research is to contribute to the detection of tax fraud concerning personal income tax returns (IRPF, in Spanish) filed in Spain, through the use of Machine Learning advanced predictive tools, by applying Multilayer Perceptron neural network (MLP) models. The possibilities springing from these techniques have been applied to a broad range of personal income return data supplied by the Institute of Fiscal Studies (IEF). The use of the neural networks enabled taxpayer segmentation as well as calculation of the probability concerning an individual taxpayer’s propensity to attempt to evade taxes. The results showed that the selected model has an efficiency rate of 84.3%, implying an improvement in relation to other models utilized in tax fraud detection. The proposal can be generalized to quantify an individual’s propensity to commit fraud with regards to other kinds of taxes. These models will support tax offices to help them arrive at the best decisions regarding action plans to combat tax fraud.

Neural network and wavelets in prediction of cosmic ray variability: The North Africa as study case

2010 ◽  
Vol 66 (7-8) ◽  
pp. 1008-1016 ◽  
Author(s):  
Neïla Zarrouk ◽  
Raouf Bennaceur
Keyword(s):  
Neural Network ◽  
North Africa ◽  
Cosmic Ray ◽  
The North ◽  
Study Case

From Conventional Methods to Contemporary Neural Network Approaches: Financial Fraud Detection

2021 ◽  
pp. 215-228
Author(s):  
Mustafa Reha Okur ◽  
Yasemin Zengin-Karaibrahimoglu ◽  
Dilvin Taşkın
Keyword(s):  
Neural Network ◽  
Fraud Detection ◽  
Financial Fraud ◽  
Conventional Methods ◽  
Network Approaches
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