PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Bonchi F., Giannotti F., Mainetto G., Pedreschi D. Using data mining techniques in fiscal fraud detection. In: 1st Int. Conf. on Data Warehousing and Knowledge Discovery, Florence - Italy (Florence (Italy), August 30 - September 1 1999). Proceedings, pp. 369 - 376. (Lecture Notes in Computer Science). Springer, 1999.
 
 
Abstract
(English)
Planning adequate audit strategies is a key success factor in "a posteriori" fraud detection, e.g., in the fiscal and insurance domains, where audits are intended to detect tax evasion and fraudulent claims. A case study is presented in this paper, which illustrates how techniques based on classification can be used to support the task of planning audit strategies. The proposed approach is sensible to some conflicting issues of audit planning, e.g., the trade-off between maximizing audit benefits vs. minimizing audit costs
Subject Data mining
H.2.8 Database applications. Data mining


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