Self-organizing maps for fraud profiling in leasing (CROSBI ID 664064)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Pejić Bach, Mirjana ; Vlahović, Nikola ; Pivar, Jasmina
engleski
Self-organizing maps for fraud profiling in leasing
Fraud is intended and planned activity aimed at achieving material or immaterial gains against interests of an organization or a person. It often occurs in financial industries, such as banking, insurance, and leasing. The goal of this paper is to present a novel approach to profiling fraudulent behavior in leasing companies, using self-organizing maps. Dataset of one leasing company that consists of both fraudulent and non-fraudulent transactions has been analyzed. Cluster analysis has been applied using the self-organizing maps algorithm, with the support of Viscovery SOMine software. Five clusters were identified, that have a different structure according to an industry of the client, previous experience with a client, type of a leasing object, and status of a leasing object (new or used). The clusters were compared using chi-square test according to proportion of fraudulent and non-fraudulent transactions, resulting in profiles of clients and leasing objects that are more prone to fraudulent behavior.
Companies, Banking, Insurance, Self-organizing feature maps, Clustering algorithms
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Podaci o prilogu
1203-1208.
2018.
objavljeno
10.23919/MIPRO.2018.8400218
Podaci o matičnoj publikaciji
Proceedings of the 41st International Convention on Information and Communication Technology, Electronics and Microelectronics MIPRO 2018
Skala, Karolj
Opatija: Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO
978-953-233-095-3
Podaci o skupu
MIPRO 2018
predavanje
21.05.2018-25.05.2018
Opatija, Hrvatska
Povezanost rada
Ekonomija, Informacijske i komunikacijske znanosti