Machine Learning - Special issue on learning with probabilistic representations
A classification-based methodology for planning audit strategies in fraud detection
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Data Mining and Knowledge Discovery
Synthesizing Test Data for Fraud Detection Systems
ACSAC '03 Proceedings of the 19th Annual Computer Security Applications Conference
A survey of kernel and spectral methods for clustering
Pattern Recognition
Uses of artificial intelligence in the Brazilian customs fraud detection system
dg.o '08 Proceedings of the 2008 international conference on Digital government research
Exploratory multilevel hot spot analysis: Australian taxation office case study
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
Expert Systems with Applications: An International Journal
Detecting Management Fraud in Public Companies
Management Science
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
Application of the recurrent multilayer perceptron in modeling complex process dynamics
IEEE Transactions on Neural Networks
Hi-index | 12.05 |
In this paper we give evidence that it is possible to characterize and detect those potential users of false invoices in a given year, depending on the information in their tax payment, their historical performance and characteristics, using different types of data mining techniques. First, clustering algorithms like SOM and neural gas are used to identify groups of similar behaviour in the universe of taxpayers. Then decision trees, neural networks and Bayesian networks are used to identify those variables that are related to conduct of fraud and/or no fraud, detect patterns of associated behaviour and establishing to what extent cases of fraud and/or no fraud can be detected with the available information. This will help identify patterns of fraud and generate knowledge that can be used in the audit work performed by the Tax Administration of Chile (in Spanish Servicio de Impuestos Internos (SII)) to detect this type of tax crime.